[INFO] fetching crate neuro-divergent 0.1.0...
[INFO] checking neuro-divergent-0.1.0 against master#82310651b93a594a3fd69015e1562186a080d94c for pr-145770
[INFO] extracting crate neuro-divergent 0.1.0 into /workspace/builds/worker-2-tc1/source
[INFO] started tweaking crates.io crate neuro-divergent 0.1.0
[INFO] removed 0 missing examples
[INFO] removed 0 missing tests
[INFO] finished tweaking crates.io crate neuro-divergent 0.1.0
[INFO] tweaked toml for crates.io crate neuro-divergent 0.1.0 written to /workspace/builds/worker-2-tc1/source/Cargo.toml
[INFO] validating manifest of crates.io crate neuro-divergent 0.1.0 on toolchain 82310651b93a594a3fd69015e1562186a080d94c
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+82310651b93a594a3fd69015e1562186a080d94c" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }`
[INFO] crate crates.io crate neuro-divergent 0.1.0 already has a lockfile, it will not be regenerated
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+82310651b93a594a3fd69015e1562186a080d94c" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] [stderr]     Updating crates.io index
[INFO] [stderr]  Downloading crates ...
[INFO] [stderr]   Downloaded plotly_derive v0.8.4
[INFO] [stderr]   Downloaded polars-json v0.35.4
[INFO] [stderr]   Downloaded rust-ini v0.20.0
[INFO] [stderr]   Downloaded neuro-divergent-registry v0.1.0
[INFO] [stderr]   Downloaded candle-nn v0.3.3
[INFO] [stderr]   Downloaded jemalloc-ctl v0.5.4
[INFO] [stderr]   Downloaded neuro-divergent-core v0.1.0
[INFO] [stderr]   Downloaded ruv-fann v0.1.2
[INFO] [stderr]   Downloaded pprof v0.13.0
[INFO] [stderr]   Downloaded simd-json v0.13.11
[INFO] [stderr]   Downloaded yaml-rust2 v0.8.1
[INFO] [stderr]   Downloaded neuro-divergent-models v0.1.0
[INFO] [stderr]   Downloaded candle-core v0.3.3
[INFO] [stderr]   Downloaded plotly v0.8.4
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:7ad1b28ee6f5f7f699f6cf7015098d6ccdd96d6f2d78dd06228f5b4c9faf309c" "/opt/rustwide/cargo-home/bin/cargo" "+82310651b93a594a3fd69015e1562186a080d94c" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }`
[INFO] [stdout] 5f2924f922a1855bbdfb3ee54f1fb8705a68a029bec030f451cc769d639deaee
[INFO] running `Command { std: "docker" "start" "-a" "5f2924f922a1855bbdfb3ee54f1fb8705a68a029bec030f451cc769d639deaee", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "inspect" "5f2924f922a1855bbdfb3ee54f1fb8705a68a029bec030f451cc769d639deaee", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "5f2924f922a1855bbdfb3ee54f1fb8705a68a029bec030f451cc769d639deaee", kill_on_drop: false }`
[INFO] [stdout] 5f2924f922a1855bbdfb3ee54f1fb8705a68a029bec030f451cc769d639deaee
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "RUSTDOCFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:7ad1b28ee6f5f7f699f6cf7015098d6ccdd96d6f2d78dd06228f5b4c9faf309c" "/opt/rustwide/cargo-home/bin/cargo" "+82310651b93a594a3fd69015e1562186a080d94c" "check" "--frozen" "--all" "--all-targets" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] a1af7fc580c26ecc7d256fa8ad2afe6844d61f4492fe6fe1841341f52b06b106
[INFO] running `Command { std: "docker" "start" "-a" "a1af7fc580c26ecc7d256fa8ad2afe6844d61f4492fe6fe1841341f52b06b106", kill_on_drop: false }`
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[INFO] [stderr]     Checking polars-parquet v0.35.4
[INFO] [stderr]     Checking polars-time v0.35.4
[INFO] [stderr]     Checking polars-io v0.35.4
[INFO] [stderr]     Checking neuro-divergent-core v0.1.0
[INFO] [stderr]     Checking neuro-divergent-models v0.1.0
[INFO] [stderr]     Checking neuro-divergent v0.1.0 (/opt/rustwide/workdir)
[INFO] [stdout] warning: field `model_type` is never read
[INFO] [stdout]   --> src/builders.rs:29:5
[INFO] [stdout]    |
[INFO] [stdout] 28 | pub struct GenericModelBuilder<T: Float> {
[INFO] [stdout]    |            ------------------- field in this struct
[INFO] [stdout] 29 |     model_type: String,
[INFO] [stdout]    |     ^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `GenericModelBuilder` has derived impls for the traits `Clone` and `Debug`, but these are intentionally ignored during dead code analysis
[INFO] [stdout]    = note: `#[warn(dead_code)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:115:1
[INFO] [stdout]     |
[INFO] [stdout] 115 | pub const VERSION: &str = env!("CARGO_PKG_VERSION");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] note: the lint level is defined here
[INFO] [stdout]    --> src/lib.rs:61:9
[INFO] [stdout]     |
[INFO] [stdout] 61  | #![warn(missing_docs)]
[INFO] [stdout]     |         ^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:116:1
[INFO] [stdout]     |
[INFO] [stdout] 116 | pub const PACKAGE_NAME: &str = env!("CARGO_PKG_NAME");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:117:1
[INFO] [stdout]     |
[INFO] [stdout] 117 | pub const DESCRIPTION: &str = env!("CARGO_PKG_DESCRIPTION");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a trait
[INFO] [stdout]   --> src/neural_forecast.rs:21:1
[INFO] [stdout]    |
[INFO] [stdout] 21 | pub trait BaseModel<T: Float + Send + Sync>: Send + Sync + std::fmt::Debug {
[INFO] [stdout]    | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:90:5
[INFO] [stdout]    |
[INFO] [stdout] 90 |     Float(T),
[INFO] [stdout]    |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:91:5
[INFO] [stdout]    |
[INFO] [stdout] 91 |     Int(i64),
[INFO] [stdout]    |     ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:92:5
[INFO] [stdout]    |
[INFO] [stdout] 92 |     String(String),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:93:5
[INFO] [stdout]    |
[INFO] [stdout] 93 |     Bool(bool),
[INFO] [stdout]    |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:94:5
[INFO] [stdout]    |
[INFO] [stdout] 94 |     FloatVec(Vec<T>),
[INFO] [stdout]    |     ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:95:5
[INFO] [stdout]    |
[INFO] [stdout] 95 |     IntVec(Vec<i64>),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:96:5
[INFO] [stdout]    |
[INFO] [stdout] 96 |     StringVec(Vec<String>),
[INFO] [stdout]    |     ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:439:5
[INFO] [stdout]     |
[INFO] [stdout] 439 |     pub horizon: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:440:5
[INFO] [stdout]     |
[INFO] [stdout] 440 |     pub input_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:441:5
[INFO] [stdout]     |
[INFO] [stdout] 441 |     pub hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:442:5
[INFO] [stdout]     |
[INFO] [stdout] 442 |     pub num_layers: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:443:5
[INFO] [stdout]     |
[INFO] [stdout] 443 |     pub dropout: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:444:5
[INFO] [stdout]     |
[INFO] [stdout] 444 |     pub bidirectional: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:445:5
[INFO] [stdout]     |
[INFO] [stdout] 445 |     pub encoder_hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:446:5
[INFO] [stdout]     |
[INFO] [stdout] 446 |     pub decoder_hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:447:5
[INFO] [stdout]     |
[INFO] [stdout] 447 |     pub max_steps: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:448:5
[INFO] [stdout]     |
[INFO] [stdout] 448 |     pub learning_rate: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:449:5
[INFO] [stdout]     |
[INFO] [stdout] 449 |     pub weight_decay: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:450:5
[INFO] [stdout]     |
[INFO] [stdout] 450 |     pub gradient_clip_val: Option<T>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:451:5
[INFO] [stdout]     |
[INFO] [stdout] 451 |     pub scaler_type: ScalerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:452:5
[INFO] [stdout]     |
[INFO] [stdout] 452 |     pub static_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:453:5
[INFO] [stdout]     |
[INFO] [stdout] 453 |     pub hist_exog_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:454:5
[INFO] [stdout]     |
[INFO] [stdout] 454 |     pub futr_exog_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:455:5
[INFO] [stdout]     |
[INFO] [stdout] 455 |     pub loss_function: LossFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:456:5
[INFO] [stdout]     |
[INFO] [stdout] 456 |     pub optimizer: OptimizerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:457:5
[INFO] [stdout]     |
[INFO] [stdout] 457 |     pub scheduler: Option<SchedulerConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:458:5
[INFO] [stdout]     |
[INFO] [stdout] 458 |     pub early_stopping: Option<EarlyStoppingConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:459:5
[INFO] [stdout]     |
[INFO] [stdout] 459 |     pub prediction_intervals: Option<PredictionIntervals>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:460:5
[INFO] [stdout]     |
[INFO] [stdout] 460 |     pub num_samples: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:461:5
[INFO] [stdout]     |
[INFO] [stdout] 461 |     pub device: Device,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:518:5
[INFO] [stdout]     |
[INFO] [stdout] 518 |     Generic,
[INFO] [stdout]     |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:519:5
[INFO] [stdout]     |
[INFO] [stdout] 519 |     Trend,
[INFO] [stdout]     |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:520:5
[INFO] [stdout]     |
[INFO] [stdout] 520 |     Seasonality,
[INFO] [stdout]     |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:526:5
[INFO] [stdout]     |
[INFO] [stdout] 526 |     ReLU,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:527:5
[INFO] [stdout]     |
[INFO] [stdout] 527 |     Tanh,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:528:5
[INFO] [stdout]     |
[INFO] [stdout] 528 |     Sigmoid,
[INFO] [stdout]     |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:529:5
[INFO] [stdout]     |
[INFO] [stdout] 529 |     Swish,
[INFO] [stdout]     |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:530:5
[INFO] [stdout]     |
[INFO] [stdout] 530 |     GELU,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:698:5
[INFO] [stdout]     |
[INFO] [stdout] 698 |     pub horizon: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:699:5
[INFO] [stdout]     |
[INFO] [stdout] 699 |     pub input_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:700:5
[INFO] [stdout]     |
[INFO] [stdout] 700 |     pub stack_types: Vec<StackType>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:701:5
[INFO] [stdout]     |
[INFO] [stdout] 701 |     pub n_blocks: Vec<usize>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:702:5
[INFO] [stdout]     |
[INFO] [stdout] 702 |     pub mlp_units: Vec<Vec<usize>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:703:5
[INFO] [stdout]     |
[INFO] [stdout] 703 |     pub shared_weights: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:704:5
[INFO] [stdout]     |
[INFO] [stdout] 704 |     pub activation: ActivationFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:705:5
[INFO] [stdout]     |
[INFO] [stdout] 705 |     pub max_steps: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:706:5
[INFO] [stdout]     |
[INFO] [stdout] 706 |     pub learning_rate: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:707:5
[INFO] [stdout]     |
[INFO] [stdout] 707 |     pub weight_decay: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:708:5
[INFO] [stdout]     |
[INFO] [stdout] 708 |     pub loss_function: LossFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:709:5
[INFO] [stdout]     |
[INFO] [stdout] 709 |     pub scaler_type: ScalerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:710:5
[INFO] [stdout]     |
[INFO] [stdout] 710 |     pub static_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:711:5
[INFO] [stdout]     |
[INFO] [stdout] 711 |     pub include_trend: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:712:5
[INFO] [stdout]     |
[INFO] [stdout] 712 |     pub include_seasonality: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:713:5
[INFO] [stdout]     |
[INFO] [stdout] 713 |     pub seasonality_period: Option<usize>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:714:5
[INFO] [stdout]     |
[INFO] [stdout] 714 |     pub optimizer: OptimizerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:715:5
[INFO] [stdout]     |
[INFO] [stdout] 715 |     pub scheduler: Option<SchedulerConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:716:5
[INFO] [stdout]     |
[INFO] [stdout] 716 |     pub early_stopping: Option<EarlyStoppingConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:717:5
[INFO] [stdout]     |
[INFO] [stdout] 717 |     pub device: Device,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:16:5
[INFO] [stdout]    |
[INFO] [stdout] 16 |     Nanosecond,
[INFO] [stdout]    |     ^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:18:5
[INFO] [stdout]    |
[INFO] [stdout] 18 |     Microsecond,
[INFO] [stdout]    |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:20:5
[INFO] [stdout]    |
[INFO] [stdout] 20 |     Millisecond,
[INFO] [stdout]    |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:22:5
[INFO] [stdout]    |
[INFO] [stdout] 22 |     Second,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:24:5
[INFO] [stdout]    |
[INFO] [stdout] 24 |     Minute,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:28:5
[INFO] [stdout]    |
[INFO] [stdout] 28 |     Hourly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:30:5
[INFO] [stdout]    |
[INFO] [stdout] 30 |     Daily,
[INFO] [stdout]    |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:32:5
[INFO] [stdout]    |
[INFO] [stdout] 32 |     Weekly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:34:5
[INFO] [stdout]    |
[INFO] [stdout] 34 |     Monthly,
[INFO] [stdout]    |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:36:5
[INFO] [stdout]    |
[INFO] [stdout] 36 |     Quarterly,
[INFO] [stdout]    |     ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:38:5
[INFO] [stdout]    |
[INFO] [stdout] 38 |     Yearly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:42:5
[INFO] [stdout]    |
[INFO] [stdout] 42 |     BusinessDaily,
[INFO] [stdout]    |     ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:44:5
[INFO] [stdout]    |
[INFO] [stdout] 44 |     BusinessMonthly,
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:46:5
[INFO] [stdout]    |
[INFO] [stdout] 46 |     BusinessQuarterly,
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:50:5
[INFO] [stdout]    |
[INFO] [stdout] 50 |     Custom(String),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:523:9
[INFO] [stdout]     |
[INFO] [stdout] 523 |         pub errors: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:524:9
[INFO] [stdout]     |
[INFO] [stdout] 524 |         pub warnings: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:525:9
[INFO] [stdout]     |
[INFO] [stdout] 525 |         pub info: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:529:9
[INFO] [stdout]     |
[INFO] [stdout] 529 |         pub fn new() -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:537:9
[INFO] [stdout]     |
[INFO] [stdout] 537 |         pub fn add_error(&mut self, error: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:541:9
[INFO] [stdout]     |
[INFO] [stdout] 541 |         pub fn add_warning(&mut self, warning: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:545:9
[INFO] [stdout]     |
[INFO] [stdout] 545 |         pub fn add_info(&mut self, info: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:549:9
[INFO] [stdout]     |
[INFO] [stdout] 549 |         pub fn has_errors(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:553:9
[INFO] [stdout]     |
[INFO] [stdout] 553 |         pub fn has_warnings(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:557:9
[INFO] [stdout]     |
[INFO] [stdout] 557 |         pub fn is_valid(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:575:9
[INFO] [stdout]     |
[INFO] [stdout] 575 |         pub fn new(label: impl Into<String>) -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:582:9
[INFO] [stdout]     |
[INFO] [stdout] 582 |         pub fn elapsed(&self) -> Duration {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:586:9
[INFO] [stdout]     |
[INFO] [stdout] 586 |         pub fn elapsed_ms(&self) -> u128 {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:590:9
[INFO] [stdout]     |
[INFO] [stdout] 590 |         pub fn elapsed_secs(&self) -> f64 {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:594:9
[INFO] [stdout]     |
[INFO] [stdout] 594 |         pub fn log_elapsed(&self) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:613:9
[INFO] [stdout]     |
[INFO] [stdout] 613 |         pub fn new() -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:617:9
[INFO] [stdout]     |
[INFO] [stdout] 617 |         pub fn track_allocation(&mut self, size: usize) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:624:9
[INFO] [stdout]     |
[INFO] [stdout] 624 |         pub fn track_deallocation(&mut self, size: usize) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:628:9
[INFO] [stdout]     |
[INFO] [stdout] 628 |         pub fn current_usage(&self) -> usize {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:632:9
[INFO] [stdout]     |
[INFO] [stdout] 632 |         pub fn peak_usage(&self) -> usize {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:636:9
[INFO] [stdout]     |
[INFO] [stdout] 636 |         pub fn reset(&mut self) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]   --> src/errors.rs:65:15
[INFO] [stdout]    |
[INFO] [stdout] 65 |     Generic { message: String },
[INFO] [stdout]    |               ^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]   --> src/errors.rs:69:16
[INFO] [stdout]    |
[INFO] [stdout] 69 |     Multiple { errors: Vec<NeuroDivergentError> },
[INFO] [stdout]    |                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a function
[INFO] [stdout]    --> src/lib.rs:145:5
[INFO] [stdout]     |
[INFO] [stdout] 145 |     pub fn has_gpu_support() -> bool {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a function
[INFO] [stdout]    --> src/lib.rs:156:5
[INFO] [stdout]     |
[INFO] [stdout] 156 |     pub fn has_async_support() -> bool {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr]     Checking jemalloc-ctl v0.5.4
[INFO] [stdout] error: expected `,`, found `.`
[INFO] [stdout]   --> examples/advanced_features.rs:32:18
[INFO] [stdout]    |
[INFO] [stdout] 32 |     println!("=" .repeat(60));
[INFO] [stdout]    |                  ^ expected `,`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: expected `,`, found `.`
[INFO] [stdout]   --> examples/ensemble_forecasting.rs:24:18
[INFO] [stdout]    |
[INFO] [stdout] 24 |     println!("=" .repeat(50));
[INFO] [stdout]    |                  ^ expected `,`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: argument never used
[INFO] [stdout]   --> examples/advanced_features.rs:32:19
[INFO] [stdout]    |
[INFO] [stdout] 32 |     println!("=" .repeat(60));
[INFO] [stdout]    |              ---  ^^^^^^^^^^ argument never used
[INFO] [stdout]    |              |
[INFO] [stdout]    |              formatting specifier missing
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: argument never used
[INFO] [stdout]   --> examples/ensemble_forecasting.rs:24:19
[INFO] [stdout]    |
[INFO] [stdout] 24 |     println!("=" .repeat(50));
[INFO] [stdout]    |              ---  ^^^^^^^^^^ argument never used
[INFO] [stdout]    |              |
[INFO] [stdout]    |              formatting specifier missing
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: expected `,`, found `.`
[INFO] [stdout]   --> examples/complete_workflow.rs:32:18
[INFO] [stdout]    |
[INFO] [stdout] 32 |     println!("=" .repeat(50));
[INFO] [stdout]    |                  ^ expected `,`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: argument never used
[INFO] [stdout]   --> examples/complete_workflow.rs:32:19
[INFO] [stdout]    |
[INFO] [stdout] 32 |     println!("=" .repeat(50));
[INFO] [stdout]    |              ---  ^^^^^^^^^^ argument never used
[INFO] [stdout]    |              |
[INFO] [stdout]    |              formatting specifier missing
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0428]: the name `main` is defined multiple times
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:523:1
[INFO] [stdout]     |
[INFO] [stdout] 523 | criterion_main!(benches);
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^ `main` redefined here
[INFO] [stdout] ...
[INFO] [stdout] 527 | fn main() {
[INFO] [stdout]     | --------- previous definition of the value `main` here
[INFO] [stdout]     |
[INFO] [stdout]     = note: `main` must be defined only once in the value namespace of this module
[INFO] [stdout]     = note: this error originates in the macro `criterion_main` (in Nightly builds, run with -Z macro-backtrace for more info)
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]   --> benches/comparison_benchmarks.rs:12:22
[INFO] [stdout]    |
[INFO] [stdout] 12 | use neuro_divergent::data::*;
[INFO] [stdout]    |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::training`
[INFO] [stdout]   --> benches/comparison_benchmarks.rs:13:22
[INFO] [stdout]    |
[INFO] [stdout] 13 | use neuro_divergent::training::*;
[INFO] [stdout]    |                      ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/performance/memory_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::*;
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::training`
[INFO] [stdout]  --> tests/performance/memory_tests.rs:9:22
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent::training::*;
[INFO] [stdout]   |                      ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::training`
[INFO] [stdout]  --> benches/training_benchmarks.rs:9:22
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent::training::*;
[INFO] [stdout]   |                      ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: could not find `data` in `neuro_divergent`
[INFO] [stdout]  --> benches/data_processing_benchmarks.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::preprocessing::*;
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> benches/inference_benchmarks.rs:9:22
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]   --> benches/training_benchmarks.rs:10:22
[INFO] [stdout]    |
[INFO] [stdout] 10 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]    |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: could not find `data` in `neuro_divergent`
[INFO] [stdout]  --> benches/data_processing_benchmarks.rs:9:22
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent::data::features::*;
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: could not find `data` in `neuro_divergent`
[INFO] [stdout]   --> benches/data_processing_benchmarks.rs:10:22
[INFO] [stdout]    |
[INFO] [stdout] 10 | use neuro_divergent::data::validation::*;
[INFO] [stdout]    |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: could not find `data` in `neuro_divergent`
[INFO] [stdout]   --> benches/data_processing_benchmarks.rs:11:22
[INFO] [stdout]    |
[INFO] [stdout] 11 | use neuro_divergent::data::transforms::*;
[INFO] [stdout]    |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: could not find `data` in `neuro_divergent`
[INFO] [stdout]   --> benches/data_processing_benchmarks.rs:12:22
[INFO] [stdout]    |
[INFO] [stdout] 12 | use neuro_divergent::data::loaders::*;
[INFO] [stdout]    |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> benches/data_processing_benchmarks.rs:7:22
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::data::*;
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> benches/model_benchmarks.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/performance/scaling_tests.rs:7:22
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::data::*;
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::training`
[INFO] [stdout]  --> tests/performance/scaling_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::training::*;
[INFO] [stdout]   |                      ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: no rules expected `;`
[INFO] [stdout]    --> tests/unit/models/specialized_tests.rs:183:41
[INFO] [stdout]     |
[INFO] [stdout] 183 |             vec![1.0, 2.0, 3.0, 4.0, 5.0; 100],
[INFO] [stdout]     |                                         ^ no rules expected this token in macro call
[INFO] [stdout]     |
[INFO] [stdout]     = note: while trying to match sequence start
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: no rules expected `;`
[INFO] [stdout]    --> tests/unit/models/specialized_tests.rs:184:41
[INFO] [stdout]     |
[INFO] [stdout] 184 |             vec![5.0, 4.0, 3.0, 2.0, 1.0; 100],
[INFO] [stdout]     |                                         ^ no rules expected this token in macro call
[INFO] [stdout]     |
[INFO] [stdout]     = note: while trying to match sequence start
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: no rules expected `;`
[INFO] [stdout]    --> tests/unit/models/specialized_tests.rs:185:42
[INFO] [stdout]     |
[INFO] [stdout] 185 |             vec![2.0, 4.0, 6.0, 8.0, 10.0; 100],
[INFO] [stdout]     |                                          ^ no rules expected this token in macro call
[INFO] [stdout]     |
[INFO] [stdout]     = note: while trying to match sequence start
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::TFT`, `neuro_divergent::models::Transformer`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]   --> examples/advanced_features.rs:14:14
[INFO] [stdout]    |
[INFO] [stdout] 14 |     models::{LSTM, NBEATS, DeepAR, TFT, Transformer},
[INFO] [stdout]    |              ^^^^  ^^^^^^  ^^^^^^  ^^^  ^^^^^^^^^^^ no `Transformer` in the root
[INFO] [stdout]    |              |     |       |       |
[INFO] [stdout]    |              |     |       |       no `TFT` in the root
[INFO] [stdout]    |              |     |       no `DeepAR` in the root
[INFO] [stdout]    |              |     no `NBEATS` in the root
[INFO] [stdout]    |              no `LSTM` in the root
[INFO] [stdout] 15 |     data::{
[INFO] [stdout]    |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] ...
[INFO] [stdout] 23 |     training::{HyperparameterTuner, SearchSpace, AccuracyMetrics},
[INFO] [stdout]    |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]    |
[INFO] [stdout]    = help: consider importing this type alias instead:
[INFO] [stdout]            neuro_divergent_models::recurrent::LSTM
[INFO] [stdout]    = help: consider importing this variant instead:
[INFO] [stdout]            neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::MLP`, `neuro_divergent::models::NHITS`, `neuro_divergent::models::Transformer`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]   --> examples/ensemble_forecasting.rs:12:14
[INFO] [stdout]    |
[INFO] [stdout] 12 |     models::{LSTM, NBEATS, DeepAR, MLP, NHITS, Transformer},
[INFO] [stdout]    |              ^^^^  ^^^^^^  ^^^^^^  ^^^  ^^^^^  ^^^^^^^^^^^ no `Transformer` in the root
[INFO] [stdout]    |              |     |       |       |    |
[INFO] [stdout]    |              |     |       |       |    no `NHITS` in the root
[INFO] [stdout]    |              |     |       |       no `MLP` in the root
[INFO] [stdout]    |              |     |       no `DeepAR` in the root
[INFO] [stdout]    |              |     no `NBEATS` in the root
[INFO] [stdout]    |              no `LSTM` in the root
[INFO] [stdout] 13 |     data::{TimeSeriesDataFrame, TimeSeriesSchema},
[INFO] [stdout]    |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 14 |     config::{LossFunction, OptimizerType, PredictionIntervals, IntervalMethod},
[INFO] [stdout] 15 |     training::AccuracyMetrics,
[INFO] [stdout]    |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]    |
[INFO] [stdout]    = help: consider importing this type alias instead:
[INFO] [stdout]            neuro_divergent_models::recurrent::LSTM
[INFO] [stdout]    = help: consider importing this variant instead:
[INFO] [stdout]            neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::MLP`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]   --> examples/complete_workflow.rs:13:14
[INFO] [stdout]    |
[INFO] [stdout] 13 |     models::{LSTM, NBEATS, DeepAR, MLP},
[INFO] [stdout]    |              ^^^^  ^^^^^^  ^^^^^^  ^^^ no `MLP` in the root
[INFO] [stdout]    |              |     |       |
[INFO] [stdout]    |              |     |       no `DeepAR` in the root
[INFO] [stdout]    |              |     no `NBEATS` in the root
[INFO] [stdout]    |              no `LSTM` in the root
[INFO] [stdout] 14 |     data::{
[INFO] [stdout]    |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] ...
[INFO] [stdout] 22 |     training::{AccuracyMetrics, ForecastingMetrics},
[INFO] [stdout]    |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]    |
[INFO] [stdout]    = help: consider importing this type alias instead:
[INFO] [stdout]            neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:803:45
[INFO] [stdout]     |
[INFO] [stdout] 803 |                     let slice = array.slice(s![..rows/2, ..cols/2]);
[INFO] [stdout]     |                                             ^
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 6   + use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/complete_workflow.rs:259:50
[INFO] [stdout]     |
[INFO] [stdout] 259 | fn create_model_ensemble() -> Result<Vec<Box<dyn BaseModel<f32>>>> {
[INFO] [stdout]     |                                                  ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/complete_workflow.rs:260:29
[INFO] [stdout]     |
[INFO] [stdout] 260 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `plotting`
[INFO] [stdout]    --> examples/complete_workflow.rs:409:7
[INFO] [stdout]     |
[INFO] [stdout] 409 | #[cfg(feature = "plotting")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `plotting` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]     = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Device`, `EarlyStoppingConfig`, `EarlyStoppingMode`, and `OptimizerType`
[INFO] [stdout]   --> examples/complete_workflow.rs:19:23
[INFO] [stdout]    |
[INFO] [stdout] 19 |         LossFunction, OptimizerType, Device, CrossValidationConfig,
[INFO] [stdout]    |                       ^^^^^^^^^^^^^  ^^^^^^
[INFO] [stdout] 20 |         EarlyStoppingConfig, EarlyStoppingMode, IntervalMethod,
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^^^^  ^^^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `DateTime` and `NaiveDateTime`
[INFO] [stdout]   --> examples/complete_workflow.rs:25:14
[INFO] [stdout]    |
[INFO] [stdout] 25 | use chrono::{DateTime, Utc, Duration, NaiveDateTime};
[INFO] [stdout]    |              ^^^^^^^^                 ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `plotting`
[INFO] [stdout]    --> examples/complete_workflow.rs:111:11
[INFO] [stdout]     |
[INFO] [stdout] 111 |     #[cfg(feature = "plotting")]
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `plotting` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::RNN`, `neuro_divergent::models::Transformer`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:13:14
[INFO] [stdout]     |
[INFO] [stdout] 13  |     models::{LSTM, NBEATS, RNN, Transformer},
[INFO] [stdout]     |              ^^^^  ^^^^^^  ^^^  ^^^^^^^^^^^ no `Transformer` in the root
[INFO] [stdout]     |              |     |       |
[INFO] [stdout]     |              |     |       no `RNN` in the root
[INFO] [stdout]     |              |     no `NBEATS` in the root
[INFO] [stdout]     |              no `LSTM` in the root
[INFO] [stdout] 14  |     data::{TimeSeriesDataset, StandardScaler, MinMaxScaler},
[INFO] [stdout]     |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 15  |     training::{AccuracyMetrics, ForecastingMetrics},
[INFO] [stdout]     |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]     |
[INFO] [stdout]     = help: consider importing this type alias instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] note: variant `crate::api_compatibility_tests::RNNCellType::LSTM` exists but is inaccessible
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:756:5
[INFO] [stdout]     |
[INFO] [stdout] 756 |     LSTM,
[INFO] [stdout]     |     ^^^^ not accessible
[INFO] [stdout]     = help: consider importing this struct instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::RNN
[INFO] [stdout] note: variant `crate::api_compatibility_tests::RNNCellType::RNN` exists but is inaccessible
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:758:5
[INFO] [stdout]     |
[INFO] [stdout] 758 |     RNN,
[INFO] [stdout]     |     ^^^ not accessible
[INFO] [stdout]     = help: consider importing this variant instead:
[INFO] [stdout]             neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:225:61
[INFO] [stdout]     |
[INFO] [stdout] 225 | fn create_diverse_ensemble() -> Result<Vec<(String, Box<dyn BaseModel<f32>>)>> {
[INFO] [stdout]     |                                                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:238:22
[INFO] [stdout]     |
[INFO] [stdout] 238 |         ) as Box<dyn BaseModel<f32>>),
[INFO] [stdout]     |                      ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:322:34
[INFO] [stdout]     |
[INFO] [stdout] 322 |     models: Vec<(String, Box<dyn BaseModel<f32>>)>,
[INFO] [stdout]     |                                  ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:423:35
[INFO] [stdout]     |
[INFO] [stdout] 423 |             .build()?) as Box<dyn BaseModel<f32>>,
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:466:35
[INFO] [stdout]     |
[INFO] [stdout] 466 |             .build()?) as Box<dyn BaseModel<f32>>,
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/ensemble_forecasting.rs:493:35
[INFO] [stdout]     |
[INFO] [stdout] 493 |             .build()?) as Box<dyn BaseModel<f32>>,
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `LossFunction`, `OptimizerType`, and `ScalerType`
[INFO] [stdout]   --> examples/ensemble_forecasting.rs:11:32
[INFO] [stdout]    |
[INFO] [stdout] 11 |     NeuralForecast, Frequency, ScalerType,
[INFO] [stdout]    |                                ^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 14 |     config::{LossFunction, OptimizerType, PredictionIntervals, IntervalMethod},
[INFO] [stdout]    |              ^^^^^^^^^^^^  ^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Context`
[INFO] [stdout]   --> examples/ensemble_forecasting.rs:20:22
[INFO] [stdout]    |
[INFO] [stdout] 20 | use anyhow::{Result, Context};
[INFO] [stdout]    |                      ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::RNN`, `neuro_divergent::models::Transformer`, `neuro_divergent::models::MLP`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:12:14
[INFO] [stdout]     |
[INFO] [stdout] 12  |     models::{LSTM, NBEATS, DeepAR, RNN, Transformer, MLP},
[INFO] [stdout]     |              ^^^^  ^^^^^^  ^^^^^^  ^^^  ^^^^^^^^^^^  ^^^ no `MLP` in the root
[INFO] [stdout]     |              |     |       |       |    |
[INFO] [stdout]     |              |     |       |       |    no `Transformer` in the root
[INFO] [stdout]     |              |     |       |       no `RNN` in the root
[INFO] [stdout]     |              |     |       no `DeepAR` in the root
[INFO] [stdout]     |              |     no `NBEATS` in the root
[INFO] [stdout]     |              no `LSTM` in the root
[INFO] [stdout] 13  |     data::{TimeSeriesDataset, TimeSeriesDataFrame},
[INFO] [stdout]     |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 14  |     training::{AccuracyMetrics, ForecastingMetrics},
[INFO] [stdout]     |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]     |
[INFO] [stdout]     = help: consider importing this type alias instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::LSTM
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:756:5
[INFO] [stdout]     |
[INFO] [stdout] 756 |     LSTM,
[INFO] [stdout]     |     ^^^^ `crate::api_compatibility_tests::RNNCellType::LSTM`: not accessible
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::NBEATS` exists but is inaccessible
[INFO] [stdout]     = help: consider importing this struct instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::RNN
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::RNN
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:758:5
[INFO] [stdout]     |
[INFO] [stdout] 758 |     RNN,
[INFO] [stdout]     |     ^^^ `crate::api_compatibility_tests::RNNCellType::RNN`: not accessible
[INFO] [stdout]     = help: consider importing this variant instead:
[INFO] [stdout]             neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::Transformer` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::MLP`, `neuro_divergent::models::RNN`, `neuro_divergent::data`, `neuro_divergent::training`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:12:14
[INFO] [stdout]     |
[INFO] [stdout] 12  |     models::{LSTM, NBEATS, MLP, RNN},
[INFO] [stdout]     |              ^^^^  ^^^^^^  ^^^  ^^^ no `RNN` in the root
[INFO] [stdout]     |              |     |       |
[INFO] [stdout]     |              |     |       no `MLP` in the root
[INFO] [stdout]     |              |     no `NBEATS` in the root
[INFO] [stdout]     |              no `LSTM` in the root
[INFO] [stdout] 13  |     data::{TimeSeriesDataFrame, TimeSeriesSchema},
[INFO] [stdout]     |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 14  |     config::{CrossValidationConfig, LossFunction, OptimizerType},
[INFO] [stdout] 15  |     training::AccuracyMetrics,
[INFO] [stdout]     |     ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout]     |
[INFO] [stdout]     = help: consider importing this type alias instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::LSTM
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:756:5
[INFO] [stdout]     |
[INFO] [stdout] 756 |     LSTM,
[INFO] [stdout]     |     ^^^^ `crate::api_compatibility_tests::RNNCellType::LSTM`: not accessible
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::NBEATS` exists but is inaccessible
[INFO] [stdout]     = help: consider importing this struct instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::RNN
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::RNN
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:758:5
[INFO] [stdout]     |
[INFO] [stdout] 758 |     RNN,
[INFO] [stdout]     |     ^^^ `crate::api_compatibility_tests::RNNCellType::RNN`: not accessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::MLP`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::Transformer`, `neuro_divergent::data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:12:14
[INFO] [stdout]     |
[INFO] [stdout] 12  |     models::{LSTM, NBEATS, MLP, DeepAR, Transformer},
[INFO] [stdout]     |              ^^^^  ^^^^^^  ^^^  ^^^^^^  ^^^^^^^^^^^ no `Transformer` in the root
[INFO] [stdout]     |              |     |       |    |
[INFO] [stdout]     |              |     |       |    no `DeepAR` in the root
[INFO] [stdout]     |              |     |       no `MLP` in the root
[INFO] [stdout]     |              |     no `NBEATS` in the root
[INFO] [stdout]     |              no `LSTM` in the root
[INFO] [stdout] 13  |     data::{TimeSeriesDataFrame, TimeSeriesSchema},
[INFO] [stdout]     |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout]     |
[INFO] [stdout]     = help: consider importing this type alias instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::LSTM
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:756:5
[INFO] [stdout]     |
[INFO] [stdout] 756 |     LSTM,
[INFO] [stdout]     |     ^^^^ `crate::api_compatibility_tests::RNNCellType::LSTM`: not accessible
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::NBEATS` exists but is inaccessible
[INFO] [stdout]     = help: consider importing this variant instead:
[INFO] [stdout]             neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::Transformer` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `polars::prelude::*`
[INFO] [stdout]    --> src/results.rs:638:9
[INFO] [stdout]     |
[INFO] [stdout] 638 |     use polars::prelude::*;
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0405, E0432.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0405`.
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MinMaxScaler`
[INFO] [stdout]    --> examples/advanced_features.rs:274:89
[INFO] [stdout]     |
[INFO] [stdout] 274 |             .add_group("marketing_features", vec!["discount_pct", "advertising_spend"], MinMaxScaler::new(0.0, 1.0)))
[INFO] [stdout]     |                                                                                         ^^^^^^^^^^^^ use of undeclared type `MinMaxScaler`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this struct
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_models::utils::preprocessing::MinMaxScaler;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/advanced_features.rs:331:51
[INFO] [stdout]     |
[INFO] [stdout] 331 | fn create_advanced_models() -> Result<Vec<Box<dyn BaseModel<f32>>>> {
[INFO] [stdout]     |                                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:12:14
[INFO] [stdout]     |
[INFO] [stdout] 12  |     models::{LSTM, NBEATS},
[INFO] [stdout]     |              ^^^^  ^^^^^^ no `NBEATS` in the root
[INFO] [stdout]     |              |
[INFO] [stdout]     |              no `LSTM` in the root
[INFO] [stdout] 13  |     data::{
[INFO] [stdout]     |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout]     |
[INFO] [stdout]     = help: consider importing this type alias instead:
[INFO] [stdout]             neuro_divergent_models::recurrent::LSTM
[INFO] [stdout] note: these items exist but are inaccessible:
[INFO] [stdout]       crate::workflow_tests::benchmarks::LSTM
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:756:5
[INFO] [stdout]     |
[INFO] [stdout] 756 |     LSTM,
[INFO] [stdout]     |     ^^^^ `crate::api_compatibility_tests::RNNCellType::LSTM`: not accessible
[INFO] [stdout]     = note: unresolved item `crate::workflow_tests::benchmarks::NBEATS` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/advanced_features.rs:332:29
[INFO] [stdout]     |
[INFO] [stdout] 332 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `EarlyStoppingMode`
[INFO] [stdout]    --> examples/advanced_features.rs:357:17
[INFO] [stdout]     |
[INFO] [stdout] 357 |                 EarlyStoppingMode::Min,
[INFO] [stdout]     |                 ^^^^^^^^^^^^^^^^^ use of undeclared type `EarlyStoppingMode`
[INFO] [stdout]     |
[INFO] [stdout] help: a struct with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 357 -                 EarlyStoppingMode::Min,
[INFO] [stdout] 357 +                 EarlyStoppingConfig::Min,
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent::config::EarlyStoppingMode;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0405, E0432.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0405`.
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> examples/advanced_features.rs:421:25
[INFO] [stdout]     |
[INFO] [stdout] 421 |     models: Vec<Box<dyn BaseModel<f32>>>,
[INFO] [stdout]     |                         ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `PredictionConfig`
[INFO] [stdout]    --> examples/advanced_features.rs:461:18
[INFO] [stdout]     |
[INFO] [stdout] 461 |     let config = PredictionConfig::new()
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^^^ use of undeclared type `PredictionConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent::neural_forecast::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 11  + use neuro_divergent_models::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `OptimizerType` and `ScalerType`
[INFO] [stdout]   --> examples/advanced_features.rs:13:32
[INFO] [stdout]    |
[INFO] [stdout] 13 |     NeuralForecast, Frequency, ScalerType, PredictionIntervals,
[INFO] [stdout]    |                                ^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 20 |         LossFunction, OptimizerType, Device, IntervalMethod,
[INFO] [stdout]    |                       ^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Context`
[INFO] [stdout]   --> examples/advanced_features.rs:28:22
[INFO] [stdout]    |
[INFO] [stdout] 28 | use anyhow::{Result, Context};
[INFO] [stdout]    |                      ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (example "ensemble_forecasting") due to 9 previous errors; 2 warnings emitted
[INFO] [stderr] warning: build failed, waiting for other jobs to finish...
[INFO] [stderr] error: could not compile `neuro-divergent` (example "complete_workflow") due to 5 previous errors; 4 warnings emitted
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `ProgressBar`
[INFO] [stdout]    --> examples/advanced_features.rs:438:18
[INFO] [stdout]     |
[INFO] [stdout] 438 |         Box::new(ProgressBar::new()),
[INFO] [stdout]     |                  ^^^^^^^^^^^ use of undeclared type `ProgressBar`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TensorBoard`
[INFO] [stdout]    --> examples/advanced_features.rs:439:18
[INFO] [stdout]     |
[INFO] [stdout] 439 |         Box::new(TensorBoard::new("./logs")),
[INFO] [stdout]     |                  ^^^^^^^^^^^ use of undeclared type `TensorBoard`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `ModelCheckpoint`
[INFO] [stdout]    --> examples/advanced_features.rs:440:18
[INFO] [stdout]     |
[INFO] [stdout] 440 |         Box::new(ModelCheckpoint::new("./checkpoints")
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^^ use of undeclared type `ModelCheckpoint`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LearningRateMonitor`
[INFO] [stdout]    --> examples/advanced_features.rs:443:18
[INFO] [stdout]     |
[INFO] [stdout] 443 |         Box::new(LearningRateMonitor::new()),
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^^^^^^ use of undeclared type `LearningRateMonitor`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `EarlyStopping`
[INFO] [stdout]    --> examples/advanced_features.rs:444:18
[INFO] [stdout]     |
[INFO] [stdout] 444 |         Box::new(EarlyStopping::new()
[INFO] [stdout]     |                  ^^^^^^^^^^^^^ use of undeclared type `EarlyStopping`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> examples/advanced_features.rs:511:21
[INFO] [stdout]     |
[INFO] [stdout] 511 |         let model = MLP::builder()
[INFO] [stdout]     |                     ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0405, E0432, E0433.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0405`.
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved imports `neuro_divergent::models::LSTM`, `neuro_divergent::models::NBEATS`, `neuro_divergent::models::DeepAR`, `neuro_divergent::models::RNN`, `neuro_divergent::models::Transformer`, `neuro_divergent::models::MLP`, `neuro_divergent::models::NHITS`, `neuro_divergent::models::TFT`, `neuro_divergent::data`
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:12:14
[INFO] [stdout]    |
[INFO] [stdout] 12 |     models::{LSTM, NBEATS, DeepAR, RNN, Transformer, MLP, NHITS, TFT},
[INFO] [stdout]    |              ^^^^  ^^^^^^  ^^^^^^  ^^^  ^^^^^^^^^^^  ^^^  ^^^^^  ^^^ no `TFT` in the root
[INFO] [stdout]    |              |     |       |       |    |            |    |
[INFO] [stdout]    |              |     |       |       |    |            |    no `NHITS` in the root
[INFO] [stdout]    |              |     |       |       |    |            no `MLP` in the root
[INFO] [stdout]    |              |     |       |       |    no `Transformer` in the root
[INFO] [stdout]    |              |     |       |       no `RNN` in the root
[INFO] [stdout]    |              |     |       no `DeepAR` in the root
[INFO] [stdout]    |              |     no `NBEATS` in the root
[INFO] [stdout]    |              no `LSTM` in the root
[INFO] [stdout] 13 |     data::{TimeSeriesDataFrame, TimeSeriesSchema},
[INFO] [stdout]    |     ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout]    |
[INFO] [stdout]    = help: consider importing one of these items instead:
[INFO] [stdout]            crate::api_compatibility_tests::RNNCellType::LSTM
[INFO] [stdout]            neuro_divergent_models::recurrent::LSTM
[INFO] [stdout]    = note: unresolved item `crate::workflow_tests::benchmarks::LSTM` exists but is inaccessible
[INFO] [stdout]    = note: unresolved item `crate::workflow_tests::benchmarks::NBEATS` exists but is inaccessible
[INFO] [stdout]    = help: consider importing one of these items instead:
[INFO] [stdout]            crate::api_compatibility_tests::RNNCellType::RNN
[INFO] [stdout]            neuro_divergent_models::recurrent::RNN
[INFO] [stdout]    = note: unresolved item `crate::workflow_tests::benchmarks::RNN` exists but is inaccessible
[INFO] [stdout]    = help: consider importing this variant instead:
[INFO] [stdout]            neuro_divergent_registry::ModelCategory::Transformer
[INFO] [stdout]    = note: unresolved item `crate::workflow_tests::benchmarks::Transformer` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (example "advanced_features") due to 15 previous errors; 2 warnings emitted
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::AccuracyMetrics`
[INFO] [stdout]  --> tests/unit/core_tests.rs:7:23
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::{AccuracyMetrics, NeuroDivergentError, NeuroDivergentResult};
[INFO] [stdout]   |                       ^^^^^^^^^^^^^^^ no `AccuracyMetrics` in the root
[INFO] [stdout]   |
[INFO] [stdout]   = help: consider importing this struct instead:
[INFO] [stdout]           neuro_divergent::results::AccuracyMetrics
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/unit/core_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::AccuracyMetrics`
[INFO] [stdout]  --> tests/unit/models/basic_tests.rs:7:23
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::{AccuracyMetrics, NeuroDivergentError, NeuroDivergentResult};
[INFO] [stdout]   |                       ^^^^^^^^^^^^^^^ no `AccuracyMetrics` in the root
[INFO] [stdout]   |
[INFO] [stdout]   = help: consider importing this struct instead:
[INFO] [stdout]           neuro_divergent::results::AccuracyMetrics
[INFO] [stdout]   = note: unresolved item `crate::unit::core_tests::integration_tests::AccuracyMetrics` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/unit/models/basic_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::core`
[INFO] [stdout]  --> tests/unit/models/recurrent_tests.rs:7:29
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent_models::core::*;
[INFO] [stdout]   |                             ^^^^ could not find `core` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::advanced`
[INFO] [stdout]  --> tests/unit/models/advanced_tests.rs:6:29
[INFO] [stdout]   |
[INFO] [stdout] 6 | use neuro_divergent_models::advanced::*;
[INFO] [stdout]   |                             ^^^^^^^^ could not find `advanced` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::core`
[INFO] [stdout]  --> tests/unit/models/advanced_tests.rs:7:29
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent_models::core::*;
[INFO] [stdout]   |                             ^^^^ could not find `core` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::transformer`
[INFO] [stdout]  --> tests/unit/models/transformer_tests.rs:6:29
[INFO] [stdout]   |
[INFO] [stdout] 6 | use neuro_divergent_models::transformer::*;
[INFO] [stdout]   |                             ^^^^^^^^^^^ could not find `transformer` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::core`
[INFO] [stdout]  --> tests/unit/models/transformer_tests.rs:7:29
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent_models::core::*;
[INFO] [stdout]   |                             ^^^^ could not find `core` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::specialized`
[INFO] [stdout]  --> tests/unit/models/specialized_tests.rs:6:29
[INFO] [stdout]   |
[INFO] [stdout] 6 | use neuro_divergent_models::specialized::*;
[INFO] [stdout]   |                             ^^^^^^^^^^^ could not find `specialized` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::sync::Mutex`
[INFO] [stdout]   --> tests/performance/memory_tests.rs:12:5
[INFO] [stdout]    |
[INFO] [stdout] 12 | use std::sync::Mutex;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/performance/memory_tests.rs:13:5
[INFO] [stdout]    |
[INFO] [stdout] 13 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent_models::core`
[INFO] [stdout]  --> tests/unit/models/specialized_tests.rs:7:29
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent_models::core::*;
[INFO] [stdout]   |                             ^^^^ could not find `core` in `neuro_divergent_models`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::AccuracyMetrics`
[INFO] [stdout]  --> tests/unit/training_tests.rs:7:23
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::{AccuracyMetrics, NeuroDivergentError, NeuroDivergentResult};
[INFO] [stdout]   |                       ^^^^^^^^^^^^^^^ no `AccuracyMetrics` in the root
[INFO] [stdout]   |
[INFO] [stdout]   = help: consider importing this struct instead:
[INFO] [stdout]           neuro_divergent::results::AccuracyMetrics
[INFO] [stdout]   = note: unresolved item `crate::unit::models::basic_tests::integration_tests::AccuracyMetrics` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/unit/training_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::training`
[INFO] [stdout]  --> tests/unit/training_tests.rs:9:22
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent::training::*;
[INFO] [stdout]   |                      ^^^^^^^^ could not find `training` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::AccuracyMetrics`
[INFO] [stdout]  --> tests/unit/data_tests.rs:7:23
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::{AccuracyMetrics, NeuroDivergentError, NeuroDivergentResult};
[INFO] [stdout]   |                       ^^^^^^^^^^^^^^^ no `AccuracyMetrics` in the root
[INFO] [stdout]   |
[INFO] [stdout]   = help: consider importing this struct instead:
[INFO] [stdout]           neuro_divergent::results::AccuracyMetrics
[INFO] [stdout]   = note: unresolved item `crate::unit::training_tests::integration_tests::AccuracyMetrics` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/unit/data_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::AccuracyMetrics`
[INFO] [stdout]  --> tests/unit/registry_tests.rs:7:23
[INFO] [stdout]   |
[INFO] [stdout] 7 | use neuro_divergent::{AccuracyMetrics, NeuroDivergentError, NeuroDivergentResult};
[INFO] [stdout]   |                       ^^^^^^^^^^^^^^^ no `AccuracyMetrics` in the root
[INFO] [stdout]   |
[INFO] [stdout]   = help: consider importing this struct instead:
[INFO] [stdout]           neuro_divergent::results::AccuracyMetrics
[INFO] [stdout]   = note: unresolved item `crate::unit::data_tests::integration_tests::AccuracyMetrics` exists but is inaccessible
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `neuro_divergent::data`
[INFO] [stdout]  --> tests/unit/registry_tests.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent::data::{TimeSeriesDataFrame, TimeSeriesSchema};
[INFO] [stdout]   |                      ^^^^ could not find `data` in `neuro_divergent`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::fs`
[INFO] [stdout]   --> benches/comparison_benchmarks.rs:17:5
[INFO] [stdout]    |
[INFO] [stdout] 17 | use std::fs;
[INFO] [stdout]    |     ^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:394:49
[INFO] [stdout]     |
[INFO] [stdout] 394 |             let weight_sum: f64 = weights.slice(s![batch_idx, ..]).sum();
[INFO] [stdout]     |                                                 ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 371 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:615:53
[INFO] [stdout]     |
[INFO] [stdout] 615 |                 let weight_sum: f64 = weights.slice(s![b, ..]).sum();
[INFO] [stdout]     |                                                     ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 555 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/advanced_tests.rs:671:48
[INFO] [stdout]     |
[INFO] [stdout] 671 |             let first_basis = poly_basis.slice(s![0, ..]);
[INFO] [stdout]     |                                                ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 623 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/advanced_tests.rs:862:52
[INFO] [stdout]     |
[INFO] [stdout] 862 |                 let dot_product: f64 = basis.slice(s![i, ..])
[INFO] [stdout]     |                                                    ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 826 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/advanced_tests.rs:864:38
[INFO] [stdout]     |
[INFO] [stdout] 864 |                     .zip(basis.slice(s![j, ..]).iter())
[INFO] [stdout]     |                                      ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 826 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Array1`
[INFO] [stdout]   --> benches/data_processing_benchmarks.rs:18:15
[INFO] [stdout]    |
[INFO] [stdout] 18 | use ndarray::{Array1, Array2};
[INFO] [stdout]    |               ^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:571:15
[INFO] [stdout]     |
[INFO] [stdout] 571 |         #[cfg(feature = "parallel")]
[INFO] [stdout]     |               ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]     = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:72:29
[INFO] [stdout]    |
[INFO] [stdout] 72 |             let mut model = LSTM::new(config).unwrap();
[INFO] [stdout]    |                             ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]    |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]    |
[INFO] [stdout] 7  + use crate::recurrent::LSTM;
[INFO] [stdout]    |
[INFO] [stdout] 7  + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSConfig`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:83:26
[INFO] [stdout]    |
[INFO] [stdout] 83 |             let config = NBEATSConfig::new(24, 12).with_num_stacks(2).with_num_blocks(2);
[INFO] [stdout]    |                          ^^^^^^^^^^^^ use of undeclared type `NBEATSConfig`
[INFO] [stdout]    |
[INFO] [stdout] help: consider importing this struct
[INFO] [stdout]    |
[INFO] [stdout] 7  + use neuro_divergent::builders::NBEATSConfig;
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:133:29
[INFO] [stdout]     |
[INFO] [stdout] 133 |             let mut model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                             ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `GRU`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:139:29
[INFO] [stdout]     |
[INFO] [stdout] 139 |             let mut model = GRU::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `GRU`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:196:29
[INFO] [stdout]     |
[INFO] [stdout] 196 |             let mut model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                             ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:269:29
[INFO] [stdout]     |
[INFO] [stdout] 269 |             let mut model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                             ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:274:26
[INFO] [stdout]     |
[INFO] [stdout] 274 |             let config = NBEATSConfig::new(48, 24)
[INFO] [stdout]     |                          ^^^^^^^^^^^^ use of undeclared type `NBEATSConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this struct
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent::builders::NBEATSConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:438:20
[INFO] [stdout]     |
[INFO] [stdout] 438 |         ("NBEATS", NBEATSConfig::new(24, 12).with_num_stacks(3)),
[INFO] [stdout]     |                    ^^^^^^^^^^^^ use of undeclared type `NBEATSConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this struct
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent::builders::NBEATSConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:458:49
[INFO] [stdout]     |
[INFO] [stdout] 458 | ...                   let mut model = LSTM::new(config.clone()).unwrap();
[INFO] [stdout]     |                                       ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:491:37
[INFO] [stdout]     |
[INFO] [stdout] 491 |                         let mut m = LSTM::new(config.clone()).unwrap();
[INFO] [stdout]     |                                     ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:546:37
[INFO] [stdout]     |
[INFO] [stdout] 546 |                     let mut model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                                     ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `GRU`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:558:37
[INFO] [stdout]     |
[INFO] [stdout] 558 |                     let mut model = GRU::new(config).unwrap();
[INFO] [stdout]     |                                     ^^^ use of undeclared type `GRU`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 7   + use crate::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 7   + use neuro_divergent_models::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]   --> benches/comparison_benchmarks.rs:71:22
[INFO] [stdout]    |
[INFO] [stdout] 71 |         .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]    |                      ^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:320:7
[INFO] [stdout]     |
[INFO] [stdout] 320 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]     = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:642:7
[INFO] [stdout]     |
[INFO] [stdout] 642 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:648:11
[INFO] [stdout]     |
[INFO] [stdout] 648 | #[cfg(not(feature = "parallel"))]
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:651:7
[INFO] [stdout]     |
[INFO] [stdout] 651 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:10:14
[INFO] [stdout]    |
[INFO] [stdout] 10 | use chrono::{DateTime, Utc, TimeZone};
[INFO] [stdout]    |              ^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:597:15
[INFO] [stdout]     |
[INFO] [stdout] 597 |         #[cfg(feature = "parallel")]
[INFO] [stdout]     |               ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]   --> tests/unit/models/transformer_tests.rs:46:53
[INFO] [stdout]    |
[INFO] [stdout] 46 |                 let weight_sum: f64 = weights.slice(s![b, i, ..]).sum();
[INFO] [stdout]    |                                                     ^
[INFO] [stdout]    |
[INFO] [stdout]    = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]    |
[INFO] [stdout] 23 +     use ndarray::s;
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:139:29
[INFO] [stdout]     |
[INFO] [stdout] 139 | ...                   validation_frequency: 10,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:140:29
[INFO] [stdout]     |
[INFO] [stdout] 140 | ...                   patience: Some(5),
[INFO] [stdout]     |                       ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:141:29
[INFO] [stdout]     |
[INFO] [stdout] 141 | ...                   gradient_clip: Some(1.0),
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 141 |                             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:142:29
[INFO] [stdout]     |
[INFO] [stdout] 142 | ...                   mixed_precision: false,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:143:29
[INFO] [stdout]     |
[INFO] [stdout] 143 | ...                   seed: Some(42),
[INFO] [stdout]     |                       ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:144:29
[INFO] [stdout]     |
[INFO] [stdout] 144 | ...                   device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                       ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:145:29
[INFO] [stdout]     |
[INFO] [stdout] 145 | ...                   checkpoint: CheckpointConfig {
[INFO] [stdout]     |                       ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:14:7
[INFO] [stdout]    |
[INFO] [stdout] 14 | #[cfg(feature = "parallel")]
[INFO] [stdout]    |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]    = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]    = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]    = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:234:7
[INFO] [stdout]     |
[INFO] [stdout] 234 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::sync::Arc`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:10:5
[INFO] [stdout]    |
[INFO] [stdout] 10 | use std::sync::Arc;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::thread`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:11:5
[INFO] [stdout]    |
[INFO] [stdout] 11 | use std::thread;
[INFO] [stdout]    |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/transformer_tests.rs:531:49
[INFO] [stdout]     |
[INFO] [stdout] 531 |             let weight_sum: f64 = weights.slice(s![b, ..]).sum();
[INFO] [stdout]     |                                                 ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 494 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]   --> benches/data_processing_benchmarks.rs:32:26
[INFO] [stdout]    |
[INFO] [stdout] 32 |     let start_time = Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap();
[INFO] [stdout]    |                          ^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0107]: missing generics for struct `neuro_divergent::neuro_divergent_models::TimeSeriesDataFrame`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:27:10
[INFO] [stdout]    |
[INFO] [stdout] 27 | ) -> Vec<TimeSeriesDataFrame> {
[INFO] [stdout]    |          ^^^^^^^^^^^^^^^^^^^ expected 1 generic argument
[INFO] [stdout]    |
[INFO] [stdout] note: struct defined here, with 1 generic parameter: `T`
[INFO] [stdout]   --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/data.rs:54:12
[INFO] [stdout]    |
[INFO] [stdout] 54 | pub struct TimeSeriesDataFrame<T: Float + Send + Sync + std::fmt::Debug + std::iter::Sum + 'static> {
[INFO] [stdout]    |            ^^^^^^^^^^^^^^^^^^^ -
[INFO] [stdout] help: add missing generic argument
[INFO] [stdout]    |
[INFO] [stdout] 27 | ) -> Vec<TimeSeriesDataFrame<T>> {
[INFO] [stdout]    |                             +++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error: cannot find macro `s` in this scope
[INFO] [stdout]    --> tests/unit/models/transformer_tests.rs:706:42
[INFO] [stdout]     |
[INFO] [stdout] 706 |                 let slice = output.slice(s![b, t, ..]);
[INFO] [stdout]     |                                          ^
[INFO] [stdout]     |
[INFO] [stdout]     = note: macro `crate::unit::models::specialized_tests::integration_tests::s` exists but is inaccessible
[INFO] [stdout] help: consider importing this macro
[INFO] [stdout]     |
[INFO] [stdout] 643 +     use ndarray::s;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> tests/performance/memory_tests.rs:149:34
[INFO] [stdout]     |
[INFO] [stdout] 149 |         let config = LSTMConfig::new(100, 50)
[INFO] [stdout]     |                                  ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:205:17
[INFO] [stdout]     |
[INFO] [stdout] 205 |                 validation_frequency: 5,
[INFO] [stdout]     |                 ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:206:17
[INFO] [stdout]     |
[INFO] [stdout] 206 |                 patience: None,
[INFO] [stdout]     |                 ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:207:17
[INFO] [stdout]     |
[INFO] [stdout] 207 |                 gradient_clip: Some(1.0),
[INFO] [stdout]     |                 ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 207 |                 gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                              ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:208:17
[INFO] [stdout]     |
[INFO] [stdout] 208 |                 mixed_precision: false,
[INFO] [stdout]     |                 ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:209:17
[INFO] [stdout]     |
[INFO] [stdout] 209 |                 seed: Some(42),
[INFO] [stdout]     |                 ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:210:17
[INFO] [stdout]     |
[INFO] [stdout] 210 |                 device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                 ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> tests/performance/memory_tests.rs:211:17
[INFO] [stdout]     |
[INFO] [stdout] 211 |                 checkpoint: CheckpointConfig {
[INFO] [stdout]     |                 ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0422]: cannot find struct, variant or union type `TimeSeriesSchema` in this scope
[INFO] [stdout]   --> tests/integration/workflow_tests.rs:86:9
[INFO] [stdout]    |
[INFO] [stdout] 86 |         TimeSeriesSchema {
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^ not found in this scope
[INFO] [stdout]    |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]    |
[INFO] [stdout] 10 + use neuro_divergent::results::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 10 + use neuro_divergent_core::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 10 + use neuro_divergent_models::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0422]: cannot find struct, variant or union type `TimeSeriesSchema` in this scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:272:18
[INFO] [stdout]     |
[INFO] [stdout] 272 |     let schema = TimeSeriesSchema {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::results::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_core::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_models::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `IntervalMethod`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:316:9
[INFO] [stdout]     |
[INFO] [stdout] 316 |         IntervalMethod::Quantile,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^ use of undeclared type `IntervalMethod`
[INFO] [stdout]     |
[INFO] [stdout] note: enum `crate::api_compatibility_tests::IntervalMethod` exists but is inaccessible
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:774:1
[INFO] [stdout]     |
[INFO] [stdout] 774 | enum IntervalMethod {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^ not accessible
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::config::IntervalMethod;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `PredictionConfig`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:339:9
[INFO] [stdout]     |
[INFO] [stdout] 339 |         PredictionConfig::new()
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ use of undeclared type `PredictionConfig`
[INFO] [stdout]     |
[INFO] [stdout] note: struct `crate::api_compatibility_tests::PredictionConfig` exists but is inaccessible
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:767:1
[INFO] [stdout]     |
[INFO] [stdout] 767 | struct PredictionConfig;
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^ not accessible
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::neural_forecast::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_models::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TimeSeriesSchema`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:469:9
[INFO] [stdout]     |
[INFO] [stdout] 469 |         TimeSeriesSchema::default(),
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ use of undeclared type `TimeSeriesSchema`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::results::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_core::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent_models::TimeSeriesSchema;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:498:9
[INFO] [stdout]     |
[INFO] [stdout] 498 |         LossFunction::MSE,
[INFO] [stdout]     |         ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:499:9
[INFO] [stdout]     |
[INFO] [stdout] 499 |         LossFunction::MAE,
[INFO] [stdout]     |         ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:500:9
[INFO] [stdout]     |
[INFO] [stdout] 500 |         LossFunction::MAPE,
[INFO] [stdout]     |         ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `RNN`
[INFO] [stdout]    --> benches/model_benchmarks.rs:164:33
[INFO] [stdout]     |
[INFO] [stdout] 164 |                     let model = RNN::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^ use of undeclared type `RNN`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::RNN;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::RNN;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/model_benchmarks.rs:181:33
[INFO] [stdout]     |
[INFO] [stdout] 181 |                     let model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `GRU`
[INFO] [stdout]    --> benches/model_benchmarks.rs:197:33
[INFO] [stdout]     |
[INFO] [stdout] 197 |                     let model = GRU::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^ use of undeclared type `GRU`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:501:9
[INFO] [stdout]     |
[INFO] [stdout] 501 |         LossFunction::Huber,
[INFO] [stdout]     |         ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 10  + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:300:34
[INFO] [stdout]     |
[INFO] [stdout] 300 |                     let config = NBEATSConfig::new(horizon * 2, horizon)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^ use of undeclared type `NBEATSConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this struct
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent::builders::NBEATSConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/model_benchmarks.rs:461:33
[INFO] [stdout]     |
[INFO] [stdout] 461 |                     let model = LSTM::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TimeSeriesSchema`
[INFO] [stdout]   --> tests/integration/ensemble_tests.rs:61:9
[INFO] [stdout]    |
[INFO] [stdout] 61 |         TimeSeriesSchema::default(),
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^ use of undeclared type `TimeSeriesSchema`
[INFO] [stdout]    |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]    |
[INFO] [stdout] 9  + use neuro_divergent::results::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 9  + use neuro_divergent_core::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 9  + use neuro_divergent_models::TimeSeriesSchema;
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:204:50
[INFO] [stdout]     |
[INFO] [stdout] 204 |                         let config = LSTMConfig::new(seq_len, 12)
[INFO] [stdout]     |                                                  ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LSTM`
[INFO] [stdout]    --> benches/model_benchmarks.rs:498:54
[INFO] [stdout]     |
[INFO] [stdout] 498 | ...                   models.push(Box::new(LSTM::new(config).unwrap()));
[INFO] [stdout]     |                                            ^^^^ use of undeclared type `LSTM`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::LSTM;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:219:29
[INFO] [stdout]     |
[INFO] [stdout] 219 | ...                   validation_frequency: 5,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `GRU`
[INFO] [stdout]    --> benches/model_benchmarks.rs:506:54
[INFO] [stdout]     |
[INFO] [stdout] 506 | ...                   models.push(Box::new(GRU::new(config).unwrap()));
[INFO] [stdout]     |                                            ^^^ use of undeclared type `GRU`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these type aliases
[INFO] [stdout]     |
[INFO] [stdout] 6   + use crate::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 6   + use neuro_divergent_models::recurrent::GRU;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:122:29
[INFO] [stdout]     |
[INFO] [stdout] 122 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]  --> benches/model_benchmarks.rs:9:14
[INFO] [stdout]   |
[INFO] [stdout] 9 | use chrono::{DateTime, Utc, TimeZone};
[INFO] [stdout]   |              ^^^^^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:220:29
[INFO] [stdout]     |
[INFO] [stdout] 220 | ...                   patience: Some(5),
[INFO] [stdout]     |                       ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:221:29
[INFO] [stdout]     |
[INFO] [stdout] 221 | ...                   gradient_clip: Some(1.0),
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 221 |                             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:222:29
[INFO] [stdout]     |
[INFO] [stdout] 222 | ...                   mixed_precision: false,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:223:29
[INFO] [stdout]     |
[INFO] [stdout] 223 | ...                   seed: Some(42),
[INFO] [stdout]     |                       ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:224:29
[INFO] [stdout]     |
[INFO] [stdout] 224 | ...                   device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                       ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:225:29
[INFO] [stdout]     |
[INFO] [stdout] 225 | ...                   checkpoint: CheckpointConfig {
[INFO] [stdout]     |                       ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:194:35
[INFO] [stdout]     |
[INFO] [stdout] 194 |             .build()?) as Box<dyn BaseModel<f32>>),
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:285:29
[INFO] [stdout]     |
[INFO] [stdout] 285 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:365:29
[INFO] [stdout]     |
[INFO] [stdout] 365 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:371:28
[INFO] [stdout]     |
[INFO] [stdout] 371 |             .loss_function(LossFunction::Huber)
[INFO] [stdout]     |                            ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:378:28
[INFO] [stdout]     |
[INFO] [stdout] 378 |             .loss_function(LossFunction::MSE)
[INFO] [stdout]     |                            ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:384:28
[INFO] [stdout]     |
[INFO] [stdout] 384 |             .loss_function(LossFunction::MAE)
[INFO] [stdout]     |                            ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:423:29
[INFO] [stdout]     |
[INFO] [stdout] 423 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `CrossValidationConfig`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:441:21
[INFO] [stdout]     |
[INFO] [stdout] 441 |     let cv_config = CrossValidationConfig::new(3, 14)
[INFO] [stdout]     |                     ^^^^^^^^^^^^^^^^^^^^^ use of undeclared type `CrossValidationConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::config::CrossValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::CrossValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::CrossValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:492:35
[INFO] [stdout]     |
[INFO] [stdout] 492 |             .build()?) as Box<dyn BaseModel<f32>>),
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:571:33
[INFO] [stdout]     |
[INFO] [stdout] 571 |         let models: Vec<Box<dyn BaseModel<f32>>> = (0..size)
[INFO] [stdout]     |                                 ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:579:43
[INFO] [stdout]     |
[INFO] [stdout] 579 |                     .unwrap()) as Box<dyn BaseModel<f32>>
[INFO] [stdout]     |                                           ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:633:29
[INFO] [stdout]     |
[INFO] [stdout] 633 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `PredictionConfig`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:663:9
[INFO] [stdout]     |
[INFO] [stdout] 663 |         PredictionConfig::new()
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ use of undeclared type `PredictionConfig`
[INFO] [stdout]     |
[INFO] [stdout] note: struct `crate::api_compatibility_tests::PredictionConfig` exists but is inaccessible
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:767:1
[INFO] [stdout]     |
[INFO] [stdout] 767 | struct PredictionConfig;
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^ not accessible
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::PredictionConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:692:29
[INFO] [stdout]     |
[INFO] [stdout] 692 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `ValidationConfig`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:716:9
[INFO] [stdout]     |
[INFO] [stdout] 716 |         ValidationConfig::new()
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ use of undeclared type `ValidationConfig`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these structs
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::ValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::ValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::ValidationConfig;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:139:29
[INFO] [stdout]     |
[INFO] [stdout] 139 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:262:35
[INFO] [stdout]     |
[INFO] [stdout] 262 |             .build()?) as Box<dyn BaseModel<f32>>),
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:495:29
[INFO] [stdout]     |
[INFO] [stdout] 495 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:128:29
[INFO] [stdout]     |
[INFO] [stdout] 128 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:563:35
[INFO] [stdout]     |
[INFO] [stdout] 563 |             .build()?) as Box<dyn BaseModel<f32>>),
[INFO] [stdout]     |                                   ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `LossFunction`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:268:24
[INFO] [stdout]     |
[INFO] [stdout] 268 |         .loss_function(LossFunction::Huber) // Robust loss
[INFO] [stdout]     |                        ^^^^^^^^^^^^ use of undeclared type `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing this enum
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::config::LossFunction;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:443:29
[INFO] [stdout]     |
[INFO] [stdout] 443 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `scan_csv` found for struct `neuro_divergent::neuro_divergent_core::LazyFrame` in the current scope
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:83:41
[INFO] [stdout]     |
[INFO] [stdout] 83  |                     let df = LazyFrame::scan_csv(
[INFO] [stdout]     |                                         ^^^^^^^^ function or associated item not found in `neuro_divergent::neuro_divergent_core::LazyFrame`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_core::LazyFrame` consider using one of the following associated functions:
[INFO] [stdout]       polars::polars_lazy::scan::anonymous_scan::<impl neuro_divergent::neuro_divergent_core::LazyFrame>::anonymous_scan
[INFO] [stdout]       polars::polars_lazy::scan::parquet::<impl neuro_divergent::neuro_divergent_core::LazyFrame>::scan_parquet
[INFO] [stdout]       polars::polars_lazy::scan::parquet::<impl neuro_divergent::neuro_divergent_core::LazyFrame>::scan_parquet_files
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/polars-lazy-0.35.4/src/scan/parquet.rs:142:5
[INFO] [stdout]     |
[INFO] [stdout] 142 |       pub fn scan_parquet(path: impl AsRef<Path>, args: ScanArgsParquet) -> PolarsResult<Self> {
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 147 |       pub fn scan_parquet_files(paths: Arc<[PathBuf]>, args: ScanArgsParquet) -> PolarsResult<Self> {
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/polars-lazy-0.35.4/src/scan/anonymous_scan.rs:29:5
[INFO] [stdout]     |
[INFO] [stdout] 29  | /     pub fn anonymous_scan(
[INFO] [stdout] 30  | |         function: Arc<dyn AnonymousScan>,
[INFO] [stdout] 31  | |         args: ScanArgsAnonymous,
[INFO] [stdout] 32  | |     ) -> PolarsResult<Self> {
[INFO] [stdout]     | |___________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `randomize_weights` found for mutable reference `&mut M` in the current scope
[INFO] [stdout]   --> benches/inference_benchmarks.rs:19:11
[INFO] [stdout]    |
[INFO] [stdout] 19 |     model.randomize_weights(-0.1, 0.1, Some(42));
[INFO] [stdout]    |           ^^^^^^^^^^^^^^^^^ method not found in `&mut M`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:193:29
[INFO] [stdout]     |
[INFO] [stdout] 193 |     let models: Vec<Box<dyn BaseModel<f32>>> = vec![
[INFO] [stdout]     |                             ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0405]: cannot find trait `BaseModel` in this scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:270:36
[INFO] [stdout]     |
[INFO] [stdout] 270 |     let models: Vec<(&str, Box<dyn BaseModel<f32>>)> = vec![
[INFO] [stdout]     |                                    ^^^^^^^^^ not found in this scope
[INFO] [stdout]     |
[INFO] [stdout] help: consider importing one of these traits
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent::neural_forecast::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_core::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 9   + use neuro_divergent_registry::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]   --> benches/inference_benchmarks.rs:31:30
[INFO] [stdout]    |
[INFO] [stdout] 31 |         let start_time = Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap();
[INFO] [stdout]    |                              ^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::path::Path`
[INFO] [stdout]   --> tests/integration/workflow_tests.rs:17:5
[INFO] [stdout]    |
[INFO] [stdout] 17 | use std::path::Path;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::fs`
[INFO] [stdout]   --> tests/integration/workflow_tests.rs:18:5
[INFO] [stdout]    |
[INFO] [stdout] 18 | use std::fs;
[INFO] [stdout]    |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `ScalerType`
[INFO] [stdout]   --> tests/integration/ensemble_tests.rs:11:32
[INFO] [stdout]    |
[INFO] [stdout] 11 |     NeuralForecast, Frequency, ScalerType,
[INFO] [stdout]    |                                ^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]   --> tests/integration/ensemble_tests.rs:18:14
[INFO] [stdout]    |
[INFO] [stdout] 18 | use chrono::{DateTime, Utc, Duration};
[INFO] [stdout]    |              ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `OptimizerType` and `ScalerType`
[INFO] [stdout]   --> tests/integration/cross_validation_tests.rs:11:32
[INFO] [stdout]    |
[INFO] [stdout] 11 |     NeuralForecast, Frequency, ScalerType,
[INFO] [stdout]    |                                ^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 14 |     config::{CrossValidationConfig, LossFunction, OptimizerType},
[INFO] [stdout]    |                                                   ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]   --> tests/integration/cross_validation_tests.rs:19:14
[INFO] [stdout]    |
[INFO] [stdout] 19 | use chrono::{DateTime, Utc, Duration};
[INFO] [stdout]    |              ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `PathBuf` and `Path`
[INFO] [stdout]   --> tests/integration/persistence_tests.rs:16:17
[INFO] [stdout]    |
[INFO] [stdout] 16 | use std::path::{Path, PathBuf};
[INFO] [stdout]    |                 ^^^^  ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]   --> tests/integration/preprocessing_tests.rs:21:14
[INFO] [stdout]    |
[INFO] [stdout] 21 | use chrono::{DateTime, Utc, Duration};
[INFO] [stdout]    |              ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Device` and `ScalerType`
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:11:32
[INFO] [stdout]    |
[INFO] [stdout] 11 |     NeuralForecast, Frequency, ScalerType, PredictionIntervals,
[INFO] [stdout]    |                                ^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 15 |         LossFunction, OptimizerType, Device, CrossValidationConfig,
[INFO] [stdout]    |                                      ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:273:38
[INFO] [stdout]     |
[INFO] [stdout] 273 |             let config = LSTMConfig::new(24, 12).with_hidden_size(128);
[INFO] [stdout]     |                                      ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `DateTime`
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:20:14
[INFO] [stdout]    |
[INFO] [stdout] 20 | use chrono::{DateTime, Utc, Duration};
[INFO] [stdout]    |              ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:23:5
[INFO] [stdout]    |
[INFO] [stdout] 23 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:272:26
[INFO] [stdout]     |
[INFO] [stdout] 272 |             .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]     |                          ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> tests/performance/memory_tests.rs:446:26
[INFO] [stdout]     |
[INFO] [stdout] 446 |             .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]     |                          ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0107]: missing generics for struct `neuro_divergent::neuro_divergent_models::TimeSeriesDataFrame`
[INFO] [stdout]   --> benches/model_benchmarks.rs:17:6
[INFO] [stdout]    |
[INFO] [stdout] 17 | ) -> TimeSeriesDataFrame {
[INFO] [stdout]    |      ^^^^^^^^^^^^^^^^^^^ expected 1 generic argument
[INFO] [stdout]    |
[INFO] [stdout] note: struct defined here, with 1 generic parameter: `T`
[INFO] [stdout]   --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/data.rs:54:12
[INFO] [stdout]    |
[INFO] [stdout] 54 | pub struct TimeSeriesDataFrame<T: Float + Send + Sync + std::fmt::Debug + std::iter::Sum + 'static> {
[INFO] [stdout]    |            ^^^^^^^^^^^^^^^^^^^ -
[INFO] [stdout] help: add missing generic argument
[INFO] [stdout]    |
[INFO] [stdout] 17 | ) -> TimeSeriesDataFrame<T> {
[INFO] [stdout]    |                         +++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:297:17
[INFO] [stdout]     |
[INFO] [stdout] 297 |             |b, series| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 300 |                     let lag_features = generate_lag_features(&series.values(), &lags);
[INFO] [stdout]     |                                                                      ------ type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 297 |             |b, series: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:310:17
[INFO] [stdout]     |
[INFO] [stdout] 310 |             |b, series| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 316 |                         features.push(rolling_mean(&series.values(), window));
[INFO] [stdout]     |                                                            ------ type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 310 |             |b, series: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]   --> benches/model_benchmarks.rs:18:26
[INFO] [stdout]    |
[INFO] [stdout] 18 |     let start_time = Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap();
[INFO] [stdout]    |                          ^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:331:17
[INFO] [stdout]     |
[INFO] [stdout] 331 |             |b, series| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] 332 |                 b.iter(|| {
[INFO] [stdout] 333 |                     let temporal_features = extract_temporal_features(&series.timestamps());
[INFO] [stdout]     |                                                                               ---------- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 331 |             |b, series: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:298:21
[INFO] [stdout]     |
[INFO] [stdout] 298 |                 |b, data| {
[INFO] [stdout]     |                     ^^^^
[INFO] [stdout] 299 |                     b.iter(|| {
[INFO] [stdout] 300 |                         let predictions: Vec<_> = data.iter()
[INFO] [stdout]     |                                                        ---- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 298 |                 |b, data: &I| {
[INFO] [stdout]     |                         ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:73:13
[INFO] [stdout]    |
[INFO] [stdout] 73 |             validation_frequency: 5,
[INFO] [stdout]    |             ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:74:13
[INFO] [stdout]    |
[INFO] [stdout] 74 |             patience: None,
[INFO] [stdout]    |             ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:75:13
[INFO] [stdout]    |
[INFO] [stdout] 75 |             gradient_clip: Some(1.0),
[INFO] [stdout]    |             ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]    |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]    |
[INFO] [stdout] 75 |             gradient_clip_val: Some(1.0),
[INFO] [stdout]    |                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:343:17
[INFO] [stdout]     |
[INFO] [stdout] 343 |             |b, series| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 346 |                     let fourier_features = generate_fourier_features(series.len(), &periods, 3);
[INFO] [stdout]     |                                                                             --- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 343 |             |b, series: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:76:13
[INFO] [stdout]    |
[INFO] [stdout] 76 |             mixed_precision: false,
[INFO] [stdout]    |             ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:77:13
[INFO] [stdout]    |
[INFO] [stdout] 77 |             seed: Some(42),
[INFO] [stdout]    |             ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]   --> benches/inference_benchmarks.rs:49:13
[INFO] [stdout]    |
[INFO] [stdout] 49 |             format!("series_{}", i),
[INFO] [stdout]    |             ^^^^^^^^^^^^^^^^^^^^^^^ expected `TimeSeriesSchema`, found `String`
[INFO] [stdout]    |
[INFO] [stdout]    = note: this error originates in the macro `format` (in Nightly builds, run with -Z macro-backtrace for more info)
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:78:13
[INFO] [stdout]    |
[INFO] [stdout] 78 |             device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]    |             ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]   --> tests/performance/scaling_tests.rs:79:13
[INFO] [stdout]    |
[INFO] [stdout] 79 |             checkpoint: CheckpointConfig {
[INFO] [stdout]    |             ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]    |
[INFO] [stdout]    = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 1 argument but 4 arguments were supplied
[INFO] [stdout]   --> benches/inference_benchmarks.rs:48:26
[INFO] [stdout]    |
[INFO] [stdout] 48 |         data_frames.push(TimeSeriesDataFrame::new(
[INFO] [stdout]    |                          ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 49 |             format!("series_{}", i),
[INFO] [stdout] 50 |             timestamps,
[INFO] [stdout]    |             ---------- unexpected argument #2 of type `Vec<chrono::DateTime<Utc>>`
[INFO] [stdout] 51 |             values,
[INFO] [stdout]    |             ------ unexpected argument #3 of type `Vec<Vec<f64>>`
[INFO] [stdout] 52 |             (0..features).map(|f| format!("feature_{}", f)).collect(),
[INFO] [stdout]    |             --------------------------------------------------------- unexpected argument #4
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/data.rs:62:12
[INFO] [stdout]    |
[INFO] [stdout] 62 |     pub fn new(schema: TimeSeriesSchema) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: remove the extra arguments
[INFO] [stdout]    |
[INFO] [stdout] 49 -             format!("series_{}", i),
[INFO] [stdout] 50 -             timestamps,
[INFO] [stdout] 49 +             format!("series_{}", i),
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:65:26
[INFO] [stdout]    |
[INFO] [stdout] 65 |             let config = MLPConfig::new(24, 12);
[INFO] [stdout]    |                          ^^^^^^^^^
[INFO] [stdout]    |                          |
[INFO] [stdout]    |                          use of undeclared type `MLPConfig`
[INFO] [stdout]    |                          help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:66:29
[INFO] [stdout]    |
[INFO] [stdout] 66 |             let mut model = MLP::new(config).unwrap();
[INFO] [stdout]    |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:391:36
[INFO] [stdout]     |
[INFO] [stdout] 391 |                     let base = Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap();
[INFO] [stdout]     |                                    ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:171:13
[INFO] [stdout]     |
[INFO] [stdout] 171 |             validation_frequency: 5,
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:172:13
[INFO] [stdout]     |
[INFO] [stdout] 172 |             patience: None,
[INFO] [stdout]     |             ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:173:13
[INFO] [stdout]     |
[INFO] [stdout] 173 |             gradient_clip: Some(1.0),
[INFO] [stdout]     |             ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 173 |             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:174:13
[INFO] [stdout]     |
[INFO] [stdout] 174 |             mixed_precision: false,
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:175:13
[INFO] [stdout]     |
[INFO] [stdout] 175 |             seed: Some(42),
[INFO] [stdout]     |             ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:176:13
[INFO] [stdout]     |
[INFO] [stdout] 176 |             device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |             ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:177:13
[INFO] [stdout]     |
[INFO] [stdout] 177 |             checkpoint: CheckpointConfig {
[INFO] [stdout]     |             ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0432, E0560, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0432`.
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:510:30
[INFO] [stdout]     |
[INFO] [stdout] 510 |                 .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]     |                              ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/comparison_benchmarks.rs:360:50
[INFO] [stdout]     |
[INFO] [stdout] 360 |                         let config = LSTMConfig::new(100, 10)
[INFO] [stdout]     |                                                  ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&(_, _)`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:533:17
[INFO] [stdout]     |
[INFO] [stdout] 533 |             |b, (dataset, batch_size)| {
[INFO] [stdout]     |                 ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 534 |                 b.iter(|| {
[INFO] [stdout] 535 |                     let loader = DataLoader::new(dataset.clone())
[INFO] [stdout]     |                                                          ----- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the placeholders `_` are specified
[INFO] [stdout]     |
[INFO] [stdout] 533 |             |b, (dataset, batch_size): &(_, _)| {
[INFO] [stdout]     |                                      +++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&(_, _)`
[INFO] [stdout]    --> benches/data_processing_benchmarks.rs:553:17
[INFO] [stdout]     |
[INFO] [stdout] 553 |             |b, (dataset, batch_size)| {
[INFO] [stdout]     |                 ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 554 |                 b.iter(|| {
[INFO] [stdout] 555 |                     let loader = DataLoader::new(dataset.clone())
[INFO] [stdout]     |                                                          ----- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the placeholders `_` are specified
[INFO] [stdout]     |
[INFO] [stdout] 553 |             |b, (dataset, batch_size): &(_, _)| {
[INFO] [stdout]     |                                      +++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:71:38
[INFO] [stdout]     |
[INFO] [stdout] 71  |             let config = LSTMConfig::new(24, 12).with_hidden_size(64);
[INFO] [stdout]     |                                      ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinearConfig`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:77:26
[INFO] [stdout]    |
[INFO] [stdout] 77 |             let config = DLinearConfig::new(24, 12);
[INFO] [stdout]    |                          ^^^^^^^^^^^^^ use of undeclared type `DLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinear`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:78:29
[INFO] [stdout]    |
[INFO] [stdout] 78 |             let mut model = DLinear::new(config).unwrap();
[INFO] [stdout]    |                             ^^^^^^^ use of undeclared type `DLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATS`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:84:29
[INFO] [stdout]    |
[INFO] [stdout] 84 |             let mut model = NBEATS::new(config).unwrap();
[INFO] [stdout]    |                             ^^^^^^ use of undeclared type `NBEATS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:126:26
[INFO] [stdout]     |
[INFO] [stdout] 126 |             let config = MLPConfig::new(24, 12).with_hidden_layers(vec![64, 32]);
[INFO] [stdout]     |                          ^^^^^^^^^
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          use of undeclared type `MLPConfig`
[INFO] [stdout]     |                          help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:127:29
[INFO] [stdout]     |
[INFO] [stdout] 127 |             let mut model = MLP::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (test "memory_tests") due to 10 previous errors; 3 warnings emitted
[INFO] [stdout] error[E0061]: this function takes 1 argument but 4 arguments were supplied
[INFO] [stdout]   --> benches/model_benchmarks.rs:51:5
[INFO] [stdout]    |
[INFO] [stdout] 51 |     TimeSeriesDataFrame::new(
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 52 |         "benchmark_series".to_string(),
[INFO] [stdout]    |         ------------------------------ expected `TimeSeriesSchema`, found `String`
[INFO] [stdout] 53 |         timestamps,
[INFO] [stdout]    |         ---------- unexpected argument #2 of type `Vec<chrono::DateTime<Utc>>`
[INFO] [stdout] 54 |         values,
[INFO] [stdout]    |         ------ unexpected argument #3 of type `Vec<Vec<f64>>`
[INFO] [stdout] 55 |         vec!["target".to_string()],
[INFO] [stdout]    |         -------------------------- unexpected argument #4 of type `Vec<std::string::String>`
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/data.rs:62:12
[INFO] [stdout]    |
[INFO] [stdout] 62 |     pub fn new(schema: TimeSeriesSchema) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: remove the extra arguments
[INFO] [stdout]    |
[INFO] [stdout] 52 -         "benchmark_series".to_string(),
[INFO] [stdout] 52 +         /* neuro_divergent::neuro_divergent_models::TimeSeriesSchema */,
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]   --> benches/model_benchmarks.rs:81:34
[INFO] [stdout]    |
[INFO] [stdout] 81 |                     let config = MLPConfig::new(24, 12)
[INFO] [stdout]    |                                  ^^^^^^^^^
[INFO] [stdout]    |                                  |
[INFO] [stdout]    |                                  use of undeclared type `MLPConfig`
[INFO] [stdout]    |                                  help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:132:38
[INFO] [stdout]     |
[INFO] [stdout] 132 |             let config = LSTMConfig::new(24, 12).with_hidden_size(64);
[INFO] [stdout]     |                                      ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]   --> benches/model_benchmarks.rs:84:33
[INFO] [stdout]    |
[INFO] [stdout] 84 |                     let model = MLP::new(config).unwrap();
[INFO] [stdout]    |                                 ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinearConfig`
[INFO] [stdout]   --> benches/model_benchmarks.rs:96:34
[INFO] [stdout]    |
[INFO] [stdout] 96 |                     let config = DLinearConfig::new(24, 12)
[INFO] [stdout]    |                                  ^^^^^^^^^^^^^ use of undeclared type `DLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinear`
[INFO] [stdout]   --> benches/model_benchmarks.rs:99:33
[INFO] [stdout]    |
[INFO] [stdout] 99 |                     let model = DLinear::new(config).unwrap();
[INFO] [stdout]    |                                 ^^^^^^^ use of undeclared type `DLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NLinearConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:111:34
[INFO] [stdout]     |
[INFO] [stdout] 111 |                     let config = NLinearConfig::new(24, 12)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^ use of undeclared type `NLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NLinear`
[INFO] [stdout]    --> benches/model_benchmarks.rs:113:33
[INFO] [stdout]     |
[INFO] [stdout] 113 |                     let model = NLinear::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^ use of undeclared type `NLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPMultivariateConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:125:34
[INFO] [stdout]     |
[INFO] [stdout] 125 |                     let config = MLPMultivariateConfig::new(3, 24, 12)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^^^^^^^^ use of undeclared type `MLPMultivariateConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPMultivariate`
[INFO] [stdout]    --> benches/model_benchmarks.rs:128:33
[INFO] [stdout]     |
[INFO] [stdout] 128 |                     let model = MLPMultivariate::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^^^^^^^^^ use of undeclared type `MLPMultivariate`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:357:13
[INFO] [stdout]     |
[INFO] [stdout] 357 |             validation_frequency: 5,
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:358:13
[INFO] [stdout]     |
[INFO] [stdout] 358 |             patience: None,
[INFO] [stdout]     |             ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:359:13
[INFO] [stdout]     |
[INFO] [stdout] 359 |             gradient_clip: Some(1.0),
[INFO] [stdout]     |             ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 359 |             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:360:13
[INFO] [stdout]     |
[INFO] [stdout] 360 |             mixed_precision: false,
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:361:13
[INFO] [stdout]     |
[INFO] [stdout] 361 |             seed: Some(42),
[INFO] [stdout]     |             ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:362:13
[INFO] [stdout]     |
[INFO] [stdout] 362 |             device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |             ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:363:13
[INFO] [stdout]     |
[INFO] [stdout] 363 |             checkpoint: CheckpointConfig {
[INFO] [stdout]     |             ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::GRUConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:138:37
[INFO] [stdout]     |
[INFO] [stdout] 138 |             let config = GRUConfig::new(24, 12).with_hidden_size(64);
[INFO] [stdout]     |                                     ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::GRUConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::GRUConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:238:5
[INFO] [stdout]     |
[INFO] [stdout] 238 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TCNConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:144:26
[INFO] [stdout]     |
[INFO] [stdout] 144 |             let config = TCNConfig::new(24, 12).with_num_channels(vec![32, 64]);
[INFO] [stdout]     |                          ^^^^^^^^^
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          use of undeclared type `TCNConfig`
[INFO] [stdout]     |                          help: a struct with a similar name exists: `RNNConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `path`
[INFO] [stdout]   --> benches/comparison_benchmarks.rs:32:24
[INFO] [stdout]    |
[INFO] [stdout] 32 | fn load_python_results(path: &str) -> Vec<PythonBenchmarkResult> {
[INFO] [stdout]    |                        ^^^^ help: if this is intentional, prefix it with an underscore: `_path`
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_variables)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TCN`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:145:29
[INFO] [stdout]     |
[INFO] [stdout] 145 |             let mut model = TCN::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `TCN`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:159:21
[INFO] [stdout]     |
[INFO] [stdout] 159 |                 |b, data| {
[INFO] [stdout]     |                     ^^^^
[INFO] [stdout] 160 |                     b.iter(|| {
[INFO] [stdout] 161 |                         let predictions: Vec<_> = data.iter()
[INFO] [stdout]     |                                                        ---- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 159 |                 |b, data: &I| {
[INFO] [stdout]     |                         ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:187:26
[INFO] [stdout]     |
[INFO] [stdout] 187 |             let config = MLPConfig::new(window_size, 1);
[INFO] [stdout]     |                          ^^^^^^^^^
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          use of undeclared type `MLPConfig`
[INFO] [stdout]     |                          help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:188:29
[INFO] [stdout]     |
[INFO] [stdout] 188 |             let mut model = MLP::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:528:22
[INFO] [stdout]     |
[INFO] [stdout] 528 |         .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]     |                      ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(deprecated)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: use of deprecated method `chrono::TimeZone::ymd_opt`: use `with_ymd_and_hms()` instead
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:560:26
[INFO] [stdout]     |
[INFO] [stdout] 560 |             .map(|i| Utc.ymd_opt(2023, 1, 1).unwrap().and_hms_opt(0, 0, 0).unwrap() + chrono::Duration::hours(i as i64))
[INFO] [stdout]     |                          ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0282, E0432, E0433, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0282`.
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:193:38
[INFO] [stdout]     |
[INFO] [stdout] 193 |             let config = LSTMConfig::new(window_size, 1)
[INFO] [stdout]     |                                      ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinearConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:201:26
[INFO] [stdout]     |
[INFO] [stdout] 201 |             let config = DLinearConfig::new(window_size, 1);
[INFO] [stdout]     |                          ^^^^^^^^^^^^^ use of undeclared type `DLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinear`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:202:29
[INFO] [stdout]     |
[INFO] [stdout] 202 |             let mut model = DLinear::new(config).unwrap();
[INFO] [stdout]     |                             ^^^^^^^ use of undeclared type `DLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:160:45
[INFO] [stdout]     |
[INFO] [stdout] 160 |                     let config = RNNConfig::new(24, 12)
[INFO] [stdout]     |                                             ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0282, E0428, E0432, E0560, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0282`.
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (bench "data_processing_benchmarks") due to 14 previous errors; 6 warnings emitted
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:217:21
[INFO] [stdout]     |
[INFO] [stdout] 217 |                 |b, data| {
[INFO] [stdout]     |                     ^^^^
[INFO] [stdout] ...
[INFO] [stdout] 224 |                             let window_data = data.slice(i, i + window_size);
[INFO] [stdout]     |                                                    ----- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 217 |                 |b, data: &I| {
[INFO] [stdout]     |                         ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:260:26
[INFO] [stdout]     |
[INFO] [stdout] 260 |             let config = MLPConfig::new(48, 24); // Direct multi-step
[INFO] [stdout]     |                          ^^^^^^^^^
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          use of undeclared type `MLPConfig`
[INFO] [stdout]     |                          help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:261:29
[INFO] [stdout]     |
[INFO] [stdout] 261 |             let mut model = MLP::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:176:46
[INFO] [stdout]     |
[INFO] [stdout] 176 |                     let config = LSTMConfig::new(24, 12)
[INFO] [stdout]     |                                              ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:266:38
[INFO] [stdout]     |
[INFO] [stdout] 266 |             let config = LSTMConfig::new(48, 24)
[INFO] [stdout]     |                                      ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATS`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:277:29
[INFO] [stdout]     |
[INFO] [stdout] 277 |             let mut model = NBEATS::new(config).unwrap();
[INFO] [stdout]     |                             ^^^^^^ use of undeclared type `NBEATS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TFTConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:282:26
[INFO] [stdout]     |
[INFO] [stdout] 282 |             let config = TFTConfig::new(48, 24)
[INFO] [stdout]     |                          ^^^^^^^^^
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          use of undeclared type `TFTConfig`
[INFO] [stdout]     |                          help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TFT`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:285:29
[INFO] [stdout]     |
[INFO] [stdout] 285 |             let mut model = TFT::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `TFT`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (bench "comparison_benchmarks") due to 21 previous errors; 3 warnings emitted
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:302:21
[INFO] [stdout]     |
[INFO] [stdout] 302 |                 |b, data| {
[INFO] [stdout]     |                     ^^^^
[INFO] [stdout] 303 |                     b.iter(|| {
[INFO] [stdout] 304 |                         let predictions: Vec<_> = data.iter()
[INFO] [stdout]     |                                                        ---- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 302 |                 |b, data: &I| {
[INFO] [stdout]     |                         ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0034]: multiple applicable items in scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:56:32
[INFO] [stdout]     |
[INFO] [stdout] 56  |             let mut value = T::from(rng.gen_range(10.0..20.0));
[INFO] [stdout]     |                                ^^^^ multiple `from` found
[INFO] [stdout]     |
[INFO] [stdout] note: candidate #1 is defined in the trait `From`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/convert/mod.rs:592:5
[INFO] [stdout] note: candidate #2 is defined in the trait `NumCast`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/num-traits-0.2.19/src/cast.rs:666:5
[INFO] [stdout]     |
[INFO] [stdout] 666 |     fn from<T: ToPrimitive>(n: T) -> Option<Self>;
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] help: use fully-qualified syntax to disambiguate
[INFO] [stdout]     |
[INFO] [stdout] 56  -             let mut value = T::from(rng.gen_range(10.0..20.0));
[INFO] [stdout] 56  +             let mut value = <T as From>::from(rng.gen_range(10.0..20.0));
[INFO] [stdout]     |
[INFO] [stdout] 56  -             let mut value = T::from(rng.gen_range(10.0..20.0));
[INFO] [stdout] 56  +             let mut value = <T as NumCast>::from(rng.gen_range(10.0..20.0));
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0034]: multiple applicable items in scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:60:36
[INFO] [stdout]     |
[INFO] [stdout] 60  |                 value = value + T::from(i as f64 * 0.1);
[INFO] [stdout]     |                                    ^^^^ multiple `from` found
[INFO] [stdout]     |
[INFO] [stdout] note: candidate #1 is defined in the trait `From`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/convert/mod.rs:592:5
[INFO] [stdout] note: candidate #2 is defined in the trait `NumCast`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/num-traits-0.2.19/src/cast.rs:666:5
[INFO] [stdout]     |
[INFO] [stdout] 666 |     fn from<T: ToPrimitive>(n: T) -> Option<Self>;
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] help: use fully-qualified syntax to disambiguate
[INFO] [stdout]     |
[INFO] [stdout] 60  -                 value = value + T::from(i as f64 * 0.1);
[INFO] [stdout] 60  +                 value = value + <T as From>::from(i as f64 * 0.1);
[INFO] [stdout]     |
[INFO] [stdout] 60  -                 value = value + T::from(i as f64 * 0.1);
[INFO] [stdout] 60  +                 value = value + <T as NumCast>::from(i as f64 * 0.1);
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0034]: multiple applicable items in scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:65:45
[INFO] [stdout]     |
[INFO] [stdout] 65  |                 let seasonal_component = T::from((i as f64 * 2.0 * std::f64::consts::PI / 7.0).sin() * 5.0);
[INFO] [stdout]     |                                             ^^^^ multiple `from` found
[INFO] [stdout]     |
[INFO] [stdout] note: candidate #1 is defined in the trait `From`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/convert/mod.rs:592:5
[INFO] [stdout] note: candidate #2 is defined in the trait `NumCast`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/num-traits-0.2.19/src/cast.rs:666:5
[INFO] [stdout]     |
[INFO] [stdout] 666 |     fn from<T: ToPrimitive>(n: T) -> Option<Self>;
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] help: use fully-qualified syntax to disambiguate
[INFO] [stdout]     |
[INFO] [stdout] 65  -                 let seasonal_component = T::from((i as f64 * 2.0 * std::f64::consts::PI / 7.0).sin() * 5.0);
[INFO] [stdout] 65  +                 let seasonal_component = <T as From>::from((i as f64 * 2.0 * std::f64::consts::PI / 7.0).sin() * 5.0);
[INFO] [stdout]     |
[INFO] [stdout] 65  -                 let seasonal_component = T::from((i as f64 * 2.0 * std::f64::consts::PI / 7.0).sin() * 5.0);
[INFO] [stdout] 65  +                 let seasonal_component = <T as NumCast>::from((i as f64 * 2.0 * std::f64::consts::PI / 7.0).sin() * 5.0);
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0034]: multiple applicable items in scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:70:28
[INFO] [stdout]     |
[INFO] [stdout] 70  |             let noise = T::from(rng.gen_range(-1.0..1.0));
[INFO] [stdout]     |                            ^^^^ multiple `from` found
[INFO] [stdout]     |
[INFO] [stdout] note: candidate #1 is defined in the trait `From`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/convert/mod.rs:592:5
[INFO] [stdout] note: candidate #2 is defined in the trait `NumCast`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/num-traits-0.2.19/src/cast.rs:666:5
[INFO] [stdout]     |
[INFO] [stdout] 666 |     fn from<T: ToPrimitive>(n: T) -> Option<Self>;
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] help: use fully-qualified syntax to disambiguate
[INFO] [stdout]     |
[INFO] [stdout] 70  -             let noise = T::from(rng.gen_range(-1.0..1.0));
[INFO] [stdout] 70  +             let noise = <T as From>::from(rng.gen_range(-1.0..1.0));
[INFO] [stdout]     |
[INFO] [stdout] 70  -             let noise = T::from(rng.gen_range(-1.0..1.0));
[INFO] [stdout] 70  +             let noise = <T as NumCast>::from(rng.gen_range(-1.0..1.0));
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `count_parameters` found for reference `&M` in the current scope
[INFO] [stdout]    --> tests/performance/scaling_tests.rs:633:30
[INFO] [stdout]     |
[INFO] [stdout] 633 |     let param_memory = model.count_parameters() * std::mem::size_of::<f64>();
[INFO] [stdout]     |                              ^^^^^^^^^^^^^^^^ method not found in `&M`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::GRUConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:193:45
[INFO] [stdout]     |
[INFO] [stdout] 193 |                     let config = GRUConfig::new(24, 12)
[INFO] [stdout]     |                                             ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::GRUConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::GRUConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:238:5
[INFO] [stdout]     |
[INFO] [stdout] 238 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TFTConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:229:34
[INFO] [stdout]     |
[INFO] [stdout] 229 |                     let config = TFTConfig::new(seq_len, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^
[INFO] [stdout]     |                                  |
[INFO] [stdout]     |                                  use of undeclared type `TFTConfig`
[INFO] [stdout]     |                                  help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TFT`
[INFO] [stdout]    --> benches/model_benchmarks.rs:234:33
[INFO] [stdout]     |
[INFO] [stdout] 234 |                     let model = TFT::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^ use of undeclared type `TFT`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `AutoformerConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:246:34
[INFO] [stdout]     |
[INFO] [stdout] 246 |                     let config = AutoformerConfig::new(seq_len, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^^^ use of undeclared type `AutoformerConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `Autoformer`
[INFO] [stdout]    --> benches/model_benchmarks.rs:251:33
[INFO] [stdout]     |
[INFO] [stdout] 251 |                     let model = Autoformer::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^^^^ use of undeclared type `Autoformer`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `InformerConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:263:34
[INFO] [stdout]     |
[INFO] [stdout] 263 |                     let config = InformerConfig::new(seq_len, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^ use of undeclared type `InformerConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `Informer`
[INFO] [stdout]    --> benches/model_benchmarks.rs:268:33
[INFO] [stdout]     |
[INFO] [stdout] 268 |                     let model = Informer::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^^ use of undeclared type `Informer`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATS`
[INFO] [stdout]    --> benches/model_benchmarks.rs:305:33
[INFO] [stdout]     |
[INFO] [stdout] 305 |                     let model = NBEATS::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^ use of undeclared type `NBEATS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NHiTSConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:317:34
[INFO] [stdout]     |
[INFO] [stdout] 317 |                     let config = NHiTSConfig::new(horizon * 2, horizon)
[INFO] [stdout]     |                                  ^^^^^^^^^^^ use of undeclared type `NHiTSConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NHiTS`
[INFO] [stdout]    --> benches/model_benchmarks.rs:323:33
[INFO] [stdout]     |
[INFO] [stdout] 323 |                     let model = NHiTS::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^ use of undeclared type `NHiTS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSxConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:335:34
[INFO] [stdout]     |
[INFO] [stdout] 335 |                     let config = NBEATSxConfig::new(horizon * 2, horizon)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^ use of undeclared type `NBEATSxConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATSx`
[INFO] [stdout]    --> benches/model_benchmarks.rs:339:33
[INFO] [stdout]     |
[INFO] [stdout] 339 |                     let model = NBEATSx::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^ use of undeclared type `NBEATSx`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TCNConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:370:34
[INFO] [stdout]     |
[INFO] [stdout] 370 |                     let config = TCNConfig::new(input_size, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^
[INFO] [stdout]     |                                  |
[INFO] [stdout]     |                                  use of undeclared type `TCNConfig`
[INFO] [stdout]     |                                  help: a struct with a similar name exists: `RNNConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TCN`
[INFO] [stdout]    --> benches/model_benchmarks.rs:374:33
[INFO] [stdout]     |
[INFO] [stdout] 374 |                     let model = TCN::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^ use of undeclared type `TCN`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `BiTCNConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:386:34
[INFO] [stdout]     |
[INFO] [stdout] 386 |                     let config = BiTCNConfig::new(input_size, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^^^ use of undeclared type `BiTCNConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `BiTCN`
[INFO] [stdout]    --> benches/model_benchmarks.rs:390:33
[INFO] [stdout]     |
[INFO] [stdout] 390 |                     let model = BiTCN::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^ use of undeclared type `BiTCN`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TimesNetConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:402:34
[INFO] [stdout]     |
[INFO] [stdout] 402 |                     let config = TimesNetConfig::new(input_size, 24)
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^ use of undeclared type `TimesNetConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `TimesNet`
[INFO] [stdout]    --> benches/model_benchmarks.rs:406:33
[INFO] [stdout]     |
[INFO] [stdout] 406 |                     let model = TimesNet::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^^^^^^ use of undeclared type `TimesNet`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:435:34
[INFO] [stdout]     |
[INFO] [stdout] 435 |                     let config = MLPConfig::new(24, 12)
[INFO] [stdout]     |                                  ^^^^^^^^^
[INFO] [stdout]     |                                  |
[INFO] [stdout]     |                                  use of undeclared type `MLPConfig`
[INFO] [stdout]     |                                  help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0432, E0560, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0432`.
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:388:22
[INFO] [stdout]     |
[INFO] [stdout] 388 |         let config = MLPConfig::new(24, 12);
[INFO] [stdout]     |                      ^^^^^^^^^
[INFO] [stdout]     |                      |
[INFO] [stdout]     |                      use of undeclared type `MLPConfig`
[INFO] [stdout]     |                      help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:389:29
[INFO] [stdout]     |
[INFO] [stdout] 389 |         let mut model_f32 = MLP::<f32>::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:395:17
[INFO] [stdout]     |
[INFO] [stdout] 395 |             |b, data| {
[INFO] [stdout]     |                 ^^^^
[INFO] [stdout] 396 |                 b.iter(|| {
[INFO] [stdout] 397 |                     let predictions: Vec<_> = data.iter()
[INFO] [stdout]     |                                                    ---- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 395 |             |b, data: &I| {
[INFO] [stdout]     |                     ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:408:22
[INFO] [stdout]     |
[INFO] [stdout] 408 |         let config = MLPConfig::new(24, 12);
[INFO] [stdout]     |                      ^^^^^^^^^
[INFO] [stdout]     |                      |
[INFO] [stdout]     |                      use of undeclared type `MLPConfig`
[INFO] [stdout]     |                      help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:409:29
[INFO] [stdout]     |
[INFO] [stdout] 409 |         let mut model_f64 = MLP::<f64>::new(config).unwrap();
[INFO] [stdout]     |                             ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:415:17
[INFO] [stdout]     |
[INFO] [stdout] 415 |             |b, data| {
[INFO] [stdout]     |                 ^^^^
[INFO] [stdout] 416 |                 b.iter(|| {
[INFO] [stdout] 417 |                     let predictions: Vec<_> = data.iter()
[INFO] [stdout]     |                                                    ---- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 415 |             |b, data: &I| {
[INFO] [stdout]     |                     ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:435:23
[INFO] [stdout]     |
[INFO] [stdout] 435 |         ("MLP_small", MLPConfig::new(24, 12).with_hidden_layers(vec![32])),
[INFO] [stdout]     |                       ^^^^^^^^^
[INFO] [stdout]     |                       |
[INFO] [stdout]     |                       use of undeclared type `MLPConfig`
[INFO] [stdout]     |                       help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:436:23
[INFO] [stdout]     |
[INFO] [stdout] 436 |         ("MLP_large", MLPConfig::new(24, 12).with_hidden_layers(vec![256, 128, 64])),
[INFO] [stdout]     |                       ^^^^^^^^^
[INFO] [stdout]     |                       |
[INFO] [stdout]     |                       use of undeclared type `MLPConfig`
[INFO] [stdout]     |                       help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (test "scaling_tests") due to 24 previous errors; 6 warnings emitted
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/model_benchmarks.rs:437:33
[INFO] [stdout]     |
[INFO] [stdout] 437 |                     let model = MLP::new(config).unwrap();
[INFO] [stdout]     |                                 ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:437:30
[INFO] [stdout]     |
[INFO] [stdout] 437 |         ("LSTM", LSTMConfig::new(24, 12).with_hidden_size(128)),
[INFO] [stdout]     |                              ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:453:49
[INFO] [stdout]     |
[INFO] [stdout] 453 | ...                   let mut model = MLP::new(config.clone()).unwrap();
[INFO] [stdout]     |                                       ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:447:17
[INFO] [stdout]     |
[INFO] [stdout] 447 |             |b, config| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 453 |                                 let mut model = MLP::new(config.clone()).unwrap();
[INFO] [stdout]     |                                                                 ----- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 447 |             |b, config: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATS`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:463:49
[INFO] [stdout]     |
[INFO] [stdout] 463 | ...                   let mut model = NBEATS::new(config.clone()).unwrap();
[INFO] [stdout]     |                                       ^^^^^^ use of undeclared type `NBEATS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:486:37
[INFO] [stdout]     |
[INFO] [stdout] 486 |                         let mut m = MLP::new(config.clone()).unwrap();
[INFO] [stdout]     |                                     ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0282]: type annotations needed for `&_`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:483:17
[INFO] [stdout]     |
[INFO] [stdout] 483 |             |b, config| {
[INFO] [stdout]     |                 ^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 486 |                         let mut m = MLP::new(config.clone()).unwrap();
[INFO] [stdout]     |                                                     ----- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout] help: consider giving this closure parameter an explicit type, where the type for type parameter `I` is specified
[INFO] [stdout]     |
[INFO] [stdout] 483 |             |b, config: &I| {
[INFO] [stdout]     |                       ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `NBEATS`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:496:37
[INFO] [stdout]     |
[INFO] [stdout] 496 |                         let mut m = NBEATS::new(config.clone()).unwrap();
[INFO] [stdout]     |                                     ^^^^^^ use of undeclared type `NBEATS`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:539:34
[INFO] [stdout]     |
[INFO] [stdout] 539 |                     let config = MLPConfig::new(24, 12).with_hidden_layers(vec![64, 32]);
[INFO] [stdout]     |                                  ^^^^^^^^^
[INFO] [stdout]     |                                  |
[INFO] [stdout]     |                                  use of undeclared type `MLPConfig`
[INFO] [stdout]     |                                  help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:540:37
[INFO] [stdout]     |
[INFO] [stdout] 540 |                     let mut model = MLP::new(config).unwrap();
[INFO] [stdout]     |                                     ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:458:46
[INFO] [stdout]     |
[INFO] [stdout] 458 |                     let config = LSTMConfig::new(24, 12)
[INFO] [stdout]     |                                              ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:545:46
[INFO] [stdout]     |
[INFO] [stdout] 545 |                     let config = LSTMConfig::new(24, 12).with_hidden_size(64);
[INFO] [stdout]     |                                              ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinearConfig`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:551:34
[INFO] [stdout]     |
[INFO] [stdout] 551 |                     let config = DLinearConfig::new(24, 12);
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^ use of undeclared type `DLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinear`
[INFO] [stdout]    --> benches/inference_benchmarks.rs:552:37
[INFO] [stdout]     |
[INFO] [stdout] 552 |                     let mut model = DLinear::new(config).unwrap();
[INFO] [stdout]     |                                     ^^^^^^^ use of undeclared type `DLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLPConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:493:46
[INFO] [stdout]     |
[INFO] [stdout] 493 | ...                   let config = MLPConfig::new(24, 12);
[INFO] [stdout]     |                                    ^^^^^^^^^
[INFO] [stdout]     |                                    |
[INFO] [stdout]     |                                    use of undeclared type `MLPConfig`
[INFO] [stdout]     |                                    help: a struct with a similar name exists: `GRUConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `MLP`
[INFO] [stdout]    --> benches/model_benchmarks.rs:494:54
[INFO] [stdout]     |
[INFO] [stdout] 494 | ...                   models.push(Box::new(MLP::new(config).unwrap()));
[INFO] [stdout]     |                                            ^^^ use of undeclared type `MLP`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:84:29
[INFO] [stdout]     |
[INFO] [stdout] 84  |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::GRUConfig` in the current scope
[INFO] [stdout]    --> benches/inference_benchmarks.rs:557:45
[INFO] [stdout]     |
[INFO] [stdout] 557 |                     let config = GRUConfig::new(24, 12).with_hidden_size(64);
[INFO] [stdout]     |                                             ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::GRUConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::GRUConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:238:5
[INFO] [stdout]     |
[INFO] [stdout] 238 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `num_traits::Float`
[INFO] [stdout]   --> benches/inference_benchmarks.rs:12:5
[INFO] [stdout]    |
[INFO] [stdout] 12 | use num_traits::Float;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::LSTMConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:497:58
[INFO] [stdout]     |
[INFO] [stdout] 497 | ...                   let config = LSTMConfig::new(24, 12);
[INFO] [stdout]     |                                                ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::LSTMConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::LSTMConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:130:5
[INFO] [stdout]     |
[INFO] [stdout] 130 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinearConfig`
[INFO] [stdout]    --> benches/model_benchmarks.rs:501:46
[INFO] [stdout]     |
[INFO] [stdout] 501 | ...                   let config = DLinearConfig::new(24, 12);
[INFO] [stdout]     |                                    ^^^^^^^^^^^^^ use of undeclared type `DLinearConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0433]: failed to resolve: use of undeclared type `DLinear`
[INFO] [stdout]    --> benches/model_benchmarks.rs:502:54
[INFO] [stdout]     |
[INFO] [stdout] 502 | ...                   models.push(Box::new(DLinear::new(config).unwrap()));
[INFO] [stdout]     |                                            ^^^^^^^ use of undeclared type `DLinear`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:101:42
[INFO] [stdout]     |
[INFO] [stdout] 101 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0061, E0107, E0282, E0308, E0432, E0433, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0061`.
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::neuro_divergent_models::GRUConfig` in the current scope
[INFO] [stdout]    --> benches/model_benchmarks.rs:505:57
[INFO] [stdout]     |
[INFO] [stdout] 505 | ...                   let config = GRUConfig::new(24, 12);
[INFO] [stdout]     |                                               ^^^ function or associated item not found in `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::neuro_divergent_models::GRUConfig<_>`, consider using `neuro_divergent::neuro_divergent_models::GRUConfig::<T>::default_with_horizon` which returns `neuro_divergent::neuro_divergent_models::GRUConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:238:5
[INFO] [stdout]     |
[INFO] [stdout] 238 |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (bench "inference_benchmarks") due to 64 previous errors; 8 warnings emitted
[INFO] [stdout] Some errors have detailed explanations: E0061, E0107, E0432, E0433, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0061`.
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/training_benchmarks.rs:446:7
[INFO] [stdout]     |
[INFO] [stdout] 446 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]     = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/training_benchmarks.rs:573:7
[INFO] [stdout]     |
[INFO] [stdout] 573 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/training_benchmarks.rs:579:11
[INFO] [stdout]     |
[INFO] [stdout] 579 | #[cfg(not(feature = "parallel"))]
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:134:26
[INFO] [stdout]     |
[INFO] [stdout] 134 |     assert_eq!(forecasts.horizon(), 7);
[INFO] [stdout]     |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `parallel`
[INFO] [stdout]    --> benches/training_benchmarks.rs:582:7
[INFO] [stdout]     |
[INFO] [stdout] 582 | #[cfg(feature = "parallel")]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]     = help: consider adding `parallel` as a feature in `Cargo.toml`
[INFO] [stdout]     = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `DateTime`, `TimeZone`, and `Utc`
[INFO] [stdout]   --> benches/training_benchmarks.rs:11:14
[INFO] [stdout]    |
[INFO] [stdout] 11 | use chrono::{DateTime, Utc, TimeZone};
[INFO] [stdout]    |              ^^^^^^^^  ^^^  ^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (bench "model_benchmarks") due to 47 previous errors; 2 warnings emitted
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:135:26
[INFO] [stdout]     |
[INFO] [stdout] 135 |     assert_eq!(forecasts.model_names(), vec!["LSTM"]);
[INFO] [stdout]     |                          ^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:144:42
[INFO] [stdout]     |
[INFO] [stdout] 144 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> benches/training_benchmarks.rs:117:29
[INFO] [stdout]     |
[INFO] [stdout] 117 | ...                   validation_frequency: 5,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> benches/training_benchmarks.rs:118:29
[INFO] [stdout]     |
[INFO] [stdout] 118 | ...                   patience: None,
[INFO] [stdout]     |                       ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> benches/training_benchmarks.rs:119:29
[INFO] [stdout]     |
[INFO] [stdout] 119 | ...                   gradient_clip: Some(1.0),
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 119 |                             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> benches/training_benchmarks.rs:120:29
[INFO] [stdout]     |
[INFO] [stdout] 120 | ...                   mixed_precision: false,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> benches/training_benchmarks.rs:121:29
[INFO] [stdout]     |
[INFO] [stdout] 121 | ...                   seed: Some(42),
[INFO] [stdout]     |                       ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> benches/training_benchmarks.rs:122:29
[INFO] [stdout]     |
[INFO] [stdout] 122 | ...                   device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                       ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> benches/training_benchmarks.rs:123:29
[INFO] [stdout]     |
[INFO] [stdout] 123 | ...                   checkpoint: CheckpointConfig {
[INFO] [stdout]     |                       ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> benches/training_benchmarks.rs:302:25
[INFO] [stdout]     |
[INFO] [stdout] 302 |                         validation_frequency: 10,
[INFO] [stdout]     |                         ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> benches/training_benchmarks.rs:303:25
[INFO] [stdout]     |
[INFO] [stdout] 303 |                         patience: None,
[INFO] [stdout]     |                         ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> benches/training_benchmarks.rs:304:25
[INFO] [stdout]     |
[INFO] [stdout] 304 |                         gradient_clip: Some(1.0),
[INFO] [stdout]     |                         ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 304 |                         gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                                      ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> benches/training_benchmarks.rs:305:25
[INFO] [stdout]     |
[INFO] [stdout] 305 |                         mixed_precision: false,
[INFO] [stdout]     |                         ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> benches/training_benchmarks.rs:306:25
[INFO] [stdout]     |
[INFO] [stdout] 306 |                         seed: Some(42),
[INFO] [stdout]     |                         ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> benches/training_benchmarks.rs:307:25
[INFO] [stdout]     |
[INFO] [stdout] 307 |                         device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                         ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> benches/training_benchmarks.rs:308:25
[INFO] [stdout]     |
[INFO] [stdout] 308 |                         checkpoint: CheckpointConfig {
[INFO] [stdout]     |                         ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:190:26
[INFO] [stdout]     |
[INFO] [stdout] 190 |     assert_eq!(forecasts.model_names().len(), 3);
[INFO] [stdout]     |                          ^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `validation_frequency`
[INFO] [stdout]    --> benches/training_benchmarks.rs:535:29
[INFO] [stdout]     |
[INFO] [stdout] 535 | ...                   validation_frequency: 10,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `patience`
[INFO] [stdout]    --> benches/training_benchmarks.rs:536:29
[INFO] [stdout]     |
[INFO] [stdout] 536 | ...                   patience: None,
[INFO] [stdout]     |                       ^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `gradient_clip`
[INFO] [stdout]    --> benches/training_benchmarks.rs:537:29
[INFO] [stdout]     |
[INFO] [stdout] 537 | ...                   gradient_clip: Some(1.0),
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout] help: a field with a similar name exists
[INFO] [stdout]     |
[INFO] [stdout] 537 |                             gradient_clip_val: Some(1.0),
[INFO] [stdout]     |                                          ++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `mixed_precision`
[INFO] [stdout]    --> benches/training_benchmarks.rs:538:29
[INFO] [stdout]     |
[INFO] [stdout] 538 | ...                   mixed_precision: false,
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `seed`
[INFO] [stdout]    --> benches/training_benchmarks.rs:539:29
[INFO] [stdout]     |
[INFO] [stdout] 539 | ...                   seed: Some(42),
[INFO] [stdout]     |                       ^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `device`
[INFO] [stdout]    --> benches/training_benchmarks.rs:540:29
[INFO] [stdout]     |
[INFO] [stdout] 540 | ...                   device: DeviceConfig::Cpu { num_threads: None },
[INFO] [stdout]     |                       ^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0560]: struct `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` has no field named `checkpoint`
[INFO] [stdout]    --> benches/training_benchmarks.rs:541:29
[INFO] [stdout]     |
[INFO] [stdout] 541 | ...                   checkpoint: CheckpointConfig {
[INFO] [stdout]     |                       ^^^^^^^^^^ `neuro_divergent::neuro_divergent_models::TrainingConfig<_>` does not have this field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `learning_rate`, `weight_decay`, `gradient_clip_val`, `validation_split`, `shuffle` ... and 2 others
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:191:23
[INFO] [stdout]     |
[INFO] [stdout] 191 |     assert!(forecasts.model_names().contains(&"LSTM".to_string()));
[INFO] [stdout]     |                       ^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0432, E0560.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0432`.
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (bench "training_benchmarks") due to 23 previous errors; 5 warnings emitted
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:192:23
[INFO] [stdout]     |
[INFO] [stdout] 192 |     assert!(forecasts.model_names().contains(&"NBEATS".to_string()));
[INFO] [stdout]     |                       ^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:193:23
[INFO] [stdout]     |
[INFO] [stdout] 193 |     assert!(forecasts.model_names().contains(&"RNN".to_string()));
[INFO] [stdout]     |                       ^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:202:46
[INFO] [stdout]     |
[INFO] [stdout] 202 |     let mut data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                              ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:244:46
[INFO] [stdout]     |
[INFO] [stdout] 244 |     let mut data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                              ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:253:23
[INFO] [stdout]     |
[INFO] [stdout] 253 |     let mut df = data.to_polars()?;
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:280:47
[INFO] [stdout]     |
[INFO] [stdout] 280 |     let data_with_exog = TimeSeriesDataFrame::new(df, schema, Some(Frequency::Daily));
[INFO] [stdout]     |                                               ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:305:42
[INFO] [stdout]     |
[INFO] [stdout] 305 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_intervals` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:345:23
[INFO] [stdout]     |
[INFO] [stdout] 345 |     assert!(forecasts.has_intervals());
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `confidence_levels` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:346:26
[INFO] [stdout]     |
[INFO] [stdout] 346 |     assert_eq!(forecasts.confidence_levels(), Some(vec![0.80, 0.95]));
[INFO] [stdout]     |                          ^^^^^^^^^^^^^^^^^-- help: remove the arguments
[INFO] [stdout]     |                          |
[INFO] [stdout]     |                          field, not a method
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:356:42
[INFO] [stdout]     |
[INFO] [stdout] 356 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:402:42
[INFO] [stdout]     |
[INFO] [stdout] 402 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:435:26
[INFO] [stdout]     |
[INFO] [stdout] 435 |     assert_eq!(forecasts.horizon(), 7);
[INFO] [stdout]     |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:467:43
[INFO] [stdout]     |
[INFO] [stdout] 467 |     let empty_data = TimeSeriesDataFrame::new(
[INFO] [stdout]     |                                           ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:488:42
[INFO] [stdout]     |
[INFO] [stdout] 488 |     let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                          ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:522:30
[INFO] [stdout]     |
[INFO] [stdout] 522 |         assert_eq!(forecasts.horizon(), 7);
[INFO] [stdout]     |                              ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:532:47
[INFO] [stdout]     |
[INFO] [stdout] 532 |     let full_data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                               ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: field `model_type` is never read
[INFO] [stdout]   --> src/builders.rs:29:5
[INFO] [stdout]    |
[INFO] [stdout] 28 | pub struct GenericModelBuilder<T: Float> {
[INFO] [stdout]    |            ------------------- field in this struct
[INFO] [stdout] 29 |     model_type: String,
[INFO] [stdout]    |     ^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `GenericModelBuilder` has derived impls for the traits `Clone` and `Debug`, but these are intentionally ignored during dead code analysis
[INFO] [stdout]    = note: `#[warn(dead_code)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:115:1
[INFO] [stdout]     |
[INFO] [stdout] 115 | pub const VERSION: &str = env!("CARGO_PKG_VERSION");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] note: the lint level is defined here
[INFO] [stdout]    --> src/lib.rs:61:9
[INFO] [stdout]     |
[INFO] [stdout] 61  | #![warn(missing_docs)]
[INFO] [stdout]     |         ^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:116:1
[INFO] [stdout]     |
[INFO] [stdout] 116 | pub const PACKAGE_NAME: &str = env!("CARGO_PKG_NAME");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a constant
[INFO] [stdout]    --> src/lib.rs:117:1
[INFO] [stdout]     |
[INFO] [stdout] 117 | pub const DESCRIPTION: &str = env!("CARGO_PKG_DESCRIPTION");
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a trait
[INFO] [stdout]   --> src/neural_forecast.rs:21:1
[INFO] [stdout]    |
[INFO] [stdout] 21 | pub trait BaseModel<T: Float + Send + Sync>: Send + Sync + std::fmt::Debug {
[INFO] [stdout]    | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:90:5
[INFO] [stdout]    |
[INFO] [stdout] 90 |     Float(T),
[INFO] [stdout]    |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:91:5
[INFO] [stdout]    |
[INFO] [stdout] 91 |     Int(i64),
[INFO] [stdout]    |     ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:92:5
[INFO] [stdout]    |
[INFO] [stdout] 92 |     String(String),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:93:5
[INFO] [stdout]    |
[INFO] [stdout] 93 |     Bool(bool),
[INFO] [stdout]    |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:94:5
[INFO] [stdout]    |
[INFO] [stdout] 94 |     FloatVec(Vec<T>),
[INFO] [stdout]    |     ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:95:5
[INFO] [stdout]    |
[INFO] [stdout] 95 |     IntVec(Vec<i64>),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/builders.rs:96:5
[INFO] [stdout]    |
[INFO] [stdout] 96 |     StringVec(Vec<String>),
[INFO] [stdout]    |     ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:439:5
[INFO] [stdout]     |
[INFO] [stdout] 439 |     pub horizon: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:440:5
[INFO] [stdout]     |
[INFO] [stdout] 440 |     pub input_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:441:5
[INFO] [stdout]     |
[INFO] [stdout] 441 |     pub hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:442:5
[INFO] [stdout]     |
[INFO] [stdout] 442 |     pub num_layers: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:443:5
[INFO] [stdout]     |
[INFO] [stdout] 443 |     pub dropout: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:444:5
[INFO] [stdout]     |
[INFO] [stdout] 444 |     pub bidirectional: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:445:5
[INFO] [stdout]     |
[INFO] [stdout] 445 |     pub encoder_hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:446:5
[INFO] [stdout]     |
[INFO] [stdout] 446 |     pub decoder_hidden_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:447:5
[INFO] [stdout]     |
[INFO] [stdout] 447 |     pub max_steps: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:448:5
[INFO] [stdout]     |
[INFO] [stdout] 448 |     pub learning_rate: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:449:5
[INFO] [stdout]     |
[INFO] [stdout] 449 |     pub weight_decay: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:450:5
[INFO] [stdout]     |
[INFO] [stdout] 450 |     pub gradient_clip_val: Option<T>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:451:5
[INFO] [stdout]     |
[INFO] [stdout] 451 |     pub scaler_type: ScalerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:452:5
[INFO] [stdout]     |
[INFO] [stdout] 452 |     pub static_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:453:5
[INFO] [stdout]     |
[INFO] [stdout] 453 |     pub hist_exog_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:454:5
[INFO] [stdout]     |
[INFO] [stdout] 454 |     pub futr_exog_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:455:5
[INFO] [stdout]     |
[INFO] [stdout] 455 |     pub loss_function: LossFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:456:5
[INFO] [stdout]     |
[INFO] [stdout] 456 |     pub optimizer: OptimizerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:457:5
[INFO] [stdout]     |
[INFO] [stdout] 457 |     pub scheduler: Option<SchedulerConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:458:5
[INFO] [stdout]     |
[INFO] [stdout] 458 |     pub early_stopping: Option<EarlyStoppingConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:459:5
[INFO] [stdout]     |
[INFO] [stdout] 459 |     pub prediction_intervals: Option<PredictionIntervals>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:460:5
[INFO] [stdout]     |
[INFO] [stdout] 460 |     pub num_samples: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:461:5
[INFO] [stdout]     |
[INFO] [stdout] 461 |     pub device: Device,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:518:5
[INFO] [stdout]     |
[INFO] [stdout] 518 |     Generic,
[INFO] [stdout]     |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:519:5
[INFO] [stdout]     |
[INFO] [stdout] 519 |     Trend,
[INFO] [stdout]     |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:520:5
[INFO] [stdout]     |
[INFO] [stdout] 520 |     Seasonality,
[INFO] [stdout]     |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:526:5
[INFO] [stdout]     |
[INFO] [stdout] 526 |     ReLU,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:527:5
[INFO] [stdout]     |
[INFO] [stdout] 527 |     Tanh,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:528:5
[INFO] [stdout]     |
[INFO] [stdout] 528 |     Sigmoid,
[INFO] [stdout]     |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:529:5
[INFO] [stdout]     |
[INFO] [stdout] 529 |     Swish,
[INFO] [stdout]     |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]    --> src/builders.rs:530:5
[INFO] [stdout]     |
[INFO] [stdout] 530 |     GELU,
[INFO] [stdout]     |     ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:698:5
[INFO] [stdout]     |
[INFO] [stdout] 698 |     pub horizon: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:699:5
[INFO] [stdout]     |
[INFO] [stdout] 699 |     pub input_size: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:700:5
[INFO] [stdout]     |
[INFO] [stdout] 700 |     pub stack_types: Vec<StackType>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:701:5
[INFO] [stdout]     |
[INFO] [stdout] 701 |     pub n_blocks: Vec<usize>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:702:5
[INFO] [stdout]     |
[INFO] [stdout] 702 |     pub mlp_units: Vec<Vec<usize>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:703:5
[INFO] [stdout]     |
[INFO] [stdout] 703 |     pub shared_weights: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:704:5
[INFO] [stdout]     |
[INFO] [stdout] 704 |     pub activation: ActivationFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:705:5
[INFO] [stdout]     |
[INFO] [stdout] 705 |     pub max_steps: usize,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:706:5
[INFO] [stdout]     |
[INFO] [stdout] 706 |     pub learning_rate: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:707:5
[INFO] [stdout]     |
[INFO] [stdout] 707 |     pub weight_decay: T,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:708:5
[INFO] [stdout]     |
[INFO] [stdout] 708 |     pub loss_function: LossFunction,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:709:5
[INFO] [stdout]     |
[INFO] [stdout] 709 |     pub scaler_type: ScalerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:710:5
[INFO] [stdout]     |
[INFO] [stdout] 710 |     pub static_features: Option<Vec<String>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:711:5
[INFO] [stdout]     |
[INFO] [stdout] 711 |     pub include_trend: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:712:5
[INFO] [stdout]     |
[INFO] [stdout] 712 |     pub include_seasonality: bool,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:713:5
[INFO] [stdout]     |
[INFO] [stdout] 713 |     pub seasonality_period: Option<usize>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:714:5
[INFO] [stdout]     |
[INFO] [stdout] 714 |     pub optimizer: OptimizerType,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:715:5
[INFO] [stdout]     |
[INFO] [stdout] 715 |     pub scheduler: Option<SchedulerConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:716:5
[INFO] [stdout]     |
[INFO] [stdout] 716 |     pub early_stopping: Option<EarlyStoppingConfig<T>>,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/builders.rs:717:5
[INFO] [stdout]     |
[INFO] [stdout] 717 |     pub device: Device,
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:16:5
[INFO] [stdout]    |
[INFO] [stdout] 16 |     Nanosecond,
[INFO] [stdout]    |     ^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:18:5
[INFO] [stdout]    |
[INFO] [stdout] 18 |     Microsecond,
[INFO] [stdout]    |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:20:5
[INFO] [stdout]    |
[INFO] [stdout] 20 |     Millisecond,
[INFO] [stdout]    |     ^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:22:5
[INFO] [stdout]    |
[INFO] [stdout] 22 |     Second,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:24:5
[INFO] [stdout]    |
[INFO] [stdout] 24 |     Minute,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:28:5
[INFO] [stdout]    |
[INFO] [stdout] 28 |     Hourly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:30:5
[INFO] [stdout]    |
[INFO] [stdout] 30 |     Daily,
[INFO] [stdout]    |     ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:32:5
[INFO] [stdout]    |
[INFO] [stdout] 32 |     Weekly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:34:5
[INFO] [stdout]    |
[INFO] [stdout] 34 |     Monthly,
[INFO] [stdout]    |     ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:36:5
[INFO] [stdout]    |
[INFO] [stdout] 36 |     Quarterly,
[INFO] [stdout]    |     ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:38:5
[INFO] [stdout]    |
[INFO] [stdout] 38 |     Yearly,
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:42:5
[INFO] [stdout]    |
[INFO] [stdout] 42 |     BusinessDaily,
[INFO] [stdout]    |     ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `train_test_split` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:542:45
[INFO] [stdout]     |
[INFO] [stdout] 542 |     let (train_data, test_data) = full_data.train_test_split(train_size)?;
[INFO] [stdout]     |                                             ^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:44:5
[INFO] [stdout]    |
[INFO] [stdout] 44 |     BusinessMonthly,
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:46:5
[INFO] [stdout]    |
[INFO] [stdout] 46 |     BusinessQuarterly,
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a variant
[INFO] [stdout]   --> src/config.rs:50:5
[INFO] [stdout]    |
[INFO] [stdout] 50 |     Custom(String),
[INFO] [stdout]    |     ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:523:9
[INFO] [stdout]     |
[INFO] [stdout] 523 |         pub errors: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:524:9
[INFO] [stdout]     |
[INFO] [stdout] 524 |         pub warnings: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]    --> src/utils.rs:525:9
[INFO] [stdout]     |
[INFO] [stdout] 525 |         pub info: Vec<String>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:529:9
[INFO] [stdout]     |
[INFO] [stdout] 529 |         pub fn new() -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:537:9
[INFO] [stdout]     |
[INFO] [stdout] 537 |         pub fn add_error(&mut self, error: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:541:9
[INFO] [stdout]     |
[INFO] [stdout] 541 |         pub fn add_warning(&mut self, warning: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:545:9
[INFO] [stdout]     |
[INFO] [stdout] 545 |         pub fn add_info(&mut self, info: String) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:549:9
[INFO] [stdout]     |
[INFO] [stdout] 549 |         pub fn has_errors(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:553:9
[INFO] [stdout]     |
[INFO] [stdout] 553 |         pub fn has_warnings(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:557:9
[INFO] [stdout]     |
[INFO] [stdout] 557 |         pub fn is_valid(&self) -> bool {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:575:9
[INFO] [stdout]     |
[INFO] [stdout] 575 |         pub fn new(label: impl Into<String>) -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:582:9
[INFO] [stdout]     |
[INFO] [stdout] 582 |         pub fn elapsed(&self) -> Duration {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:586:9
[INFO] [stdout]     |
[INFO] [stdout] 586 |         pub fn elapsed_ms(&self) -> u128 {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:590:9
[INFO] [stdout]     |
[INFO] [stdout] 590 |         pub fn elapsed_secs(&self) -> f64 {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:594:9
[INFO] [stdout]     |
[INFO] [stdout] 594 |         pub fn log_elapsed(&self) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for an associated function
[INFO] [stdout]    --> src/utils.rs:613:9
[INFO] [stdout]     |
[INFO] [stdout] 613 |         pub fn new() -> Self {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:617:9
[INFO] [stdout]     |
[INFO] [stdout] 617 |         pub fn track_allocation(&mut self, size: usize) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:624:9
[INFO] [stdout]     |
[INFO] [stdout] 624 |         pub fn track_deallocation(&mut self, size: usize) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:628:9
[INFO] [stdout]     |
[INFO] [stdout] 628 |         pub fn current_usage(&self) -> usize {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:632:9
[INFO] [stdout]     |
[INFO] [stdout] 632 |         pub fn peak_usage(&self) -> usize {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a method
[INFO] [stdout]    --> src/utils.rs:636:9
[INFO] [stdout]     |
[INFO] [stdout] 636 |         pub fn reset(&mut self) {
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]   --> src/errors.rs:65:15
[INFO] [stdout]    |
[INFO] [stdout] 65 |     Generic { message: String },
[INFO] [stdout]    |               ^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a struct field
[INFO] [stdout]   --> src/errors.rs:69:16
[INFO] [stdout]    |
[INFO] [stdout] 69 |     Multiple { errors: Vec<NeuroDivergentError> },
[INFO] [stdout]    |                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a function
[INFO] [stdout]    --> src/lib.rs:145:5
[INFO] [stdout]     |
[INFO] [stdout] 145 |     pub fn has_gpu_support() -> bool {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: missing documentation for a function
[INFO] [stdout]    --> src/lib.rs:156:5
[INFO] [stdout]     |
[INFO] [stdout] 156 |     pub fn has_async_support() -> bool {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:591:50
[INFO] [stdout]     |
[INFO] [stdout] 591 |             let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:628:46
[INFO] [stdout]     |
[INFO] [stdout] 628 |         let data = generate_synthetic_data::<f32>(
[INFO] [stdout]     |                                              ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `workflow_tests::generate_synthetic_data`
[INFO] [stdout]    --> tests/integration/workflow_tests.rs:33:8
[INFO] [stdout]     |
[INFO] [stdout] 25  | fn generate_synthetic_data<T: Float>(
[INFO] [stdout]     |    ----------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 33  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:59:29
[INFO] [stdout]     |
[INFO] [stdout] 59  |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0034]: multiple applicable items in scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:94:12
[INFO] [stdout]     |
[INFO] [stdout] 94  |         T::from(value)
[INFO] [stdout]     |            ^^^^ multiple `from` found
[INFO] [stdout]     |
[INFO] [stdout] note: candidate #1 is defined in the trait `From`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/convert/mod.rs:592:5
[INFO] [stdout] note: candidate #2 is defined in the trait `NumCast`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/num-traits-0.2.19/src/cast.rs:666:5
[INFO] [stdout]     |
[INFO] [stdout] 666 |     fn from<T: ToPrimitive>(n: T) -> Option<Self>;
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] help: use fully-qualified syntax to disambiguate
[INFO] [stdout]     |
[INFO] [stdout] 94  -         T::from(value)
[INFO] [stdout] 94  +         <T as From>::from(value)
[INFO] [stdout]     |
[INFO] [stdout] 94  -         T::from(value)
[INFO] [stdout] 94  +         <T as NumCast>::from(value)
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:119:50
[INFO] [stdout]     |
[INFO] [stdout] 119 |     let data = generate_complex_synthetic_data::<f32>(4, 200, patterns)?;
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:173:50
[INFO] [stdout]     |
[INFO] [stdout] 173 |     let data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `train_test_split` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:186:39
[INFO] [stdout]     |
[INFO] [stdout] 186 |     let (train_data, val_data) = data.train_test_split(120)?;
[INFO] [stdout]     |                                       ^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:282:50
[INFO] [stdout]     |
[INFO] [stdout] 282 |     let data = generate_complex_synthetic_data::<f32>(6, 300, patterns)?;
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:336:54
[INFO] [stdout]     |
[INFO] [stdout] 336 |     let mut data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                      ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:349:23
[INFO] [stdout]     |
[INFO] [stdout] 349 |     let mut df = data.to_polars()?;
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:410:50
[INFO] [stdout]     |
[INFO] [stdout] 410 |     let data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:484:50
[INFO] [stdout]     |
[INFO] [stdout] 484 |     let data = generate_complex_synthetic_data::<f32>(10, 200, patterns)?;
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:555:50
[INFO] [stdout]     |
[INFO] [stdout] 555 |     let data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:620:50
[INFO] [stdout]     |
[INFO] [stdout] 620 |     let data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:679:50
[INFO] [stdout]     |
[INFO] [stdout] 679 |     let data = generate_complex_synthetic_data::<f32>(
[INFO] [stdout]     |                                                  ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_complex_synthetic_data`
[INFO] [stdout]    --> tests/integration/ensemble_tests.rs:29:8
[INFO] [stdout]     |
[INFO] [stdout] 23  | fn generate_complex_synthetic_data<T: Float>(
[INFO] [stdout]     |    ------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 29  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_complex_synthetic_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:72:29
[INFO] [stdout]     |
[INFO] [stdout] 72  |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]   --> tests/integration/cross_validation_tests.rs:83:40
[INFO] [stdout]    |
[INFO] [stdout] 83 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]    |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]    |
[INFO] [stdout]    = help: the following other types implement trait `From<T>`:
[INFO] [stdout]              `f32` implements `From<bool>`
[INFO] [stdout]              `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]              `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]              `f32` implements `From<half::bf16>`
[INFO] [stdout]              `f32` implements `From<half::f16>`
[INFO] [stdout]              `f32` implements `From<i16>`
[INFO] [stdout]              `f32` implements `From<i8>`
[INFO] [stdout]              `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]            and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]   --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]    |
[INFO] [stdout] 24 | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]    |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31 |     T: From<f64> + Into<f64>,
[INFO] [stdout]    |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `n_windows` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:112:27
[INFO] [stdout]     |
[INFO] [stdout] 112 |     assert_eq!(cv_results.n_windows(), 5);
[INFO] [stdout]     |                           ^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `model_names` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:113:27
[INFO] [stdout]     |
[INFO] [stdout] 113 |     assert_eq!(cv_results.model_names(), vec!["LSTM"]);
[INFO] [stdout]     |                           ^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:116:30
[INFO] [stdout]     |
[INFO] [stdout] 116 |     let metrics = cv_results.calculate_metrics()?;
[INFO] [stdout]     |                              ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:131:40
[INFO] [stdout]     |
[INFO] [stdout] 131 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:204:40
[INFO] [stdout]     |
[INFO] [stdout] 204 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_seasonal_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:234:40
[INFO] [stdout]     |
[INFO] [stdout] 234 |     let metrics_by_season = cv_results.calculate_seasonal_metrics()?;
[INFO] [stdout]     |                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:248:40
[INFO] [stdout]     |
[INFO] [stdout] 248 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:338:40
[INFO] [stdout]     |
[INFO] [stdout] 338 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:382:46
[INFO] [stdout]     |
[INFO] [stdout] 382 |                     let metrics = cv_results.calculate_metrics()?;
[INFO] [stdout]     |                                              ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:412:44
[INFO] [stdout]     |
[INFO] [stdout] 412 |     let mut data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                            ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:420:23
[INFO] [stdout]     |
[INFO] [stdout] 420 |     let mut df = data.to_polars()?;
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:465:34
[INFO] [stdout]     |
[INFO] [stdout] 465 |         let metrics = cv_results.calculate_metrics()?;
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `LossFunction: Hash` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:467:26
[INFO] [stdout]     |
[INFO] [stdout] 467 |         loss_performance.insert(loss_fn, metrics["LSTM"].clone());
[INFO] [stdout]     |                          ^^^^^^ the trait `Hash` is not implemented for `LossFunction`
[INFO] [stdout]     |
[INFO] [stdout] note: required by a bound in `HashMap::<K, V, S>::insert`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/std/src/collections/hash/map.rs:1203:5
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:487:40
[INFO] [stdout]     |
[INFO] [stdout] 487 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:547:40
[INFO] [stdout]     |
[INFO] [stdout] 547 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:577:34
[INFO] [stdout]     |
[INFO] [stdout] 577 |         let metrics = cv_results.calculate_metrics()?;
[INFO] [stdout]     |                                  ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:608:40
[INFO] [stdout]     |
[INFO] [stdout] 608 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:656:36
[INFO] [stdout]     |
[INFO] [stdout] 656 |     let metrics_es = cv_results_es.calculate_metrics()?;
[INFO] [stdout]     |                                    ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:657:42
[INFO] [stdout]     |
[INFO] [stdout] 657 |     let metrics_no_es = cv_results_no_es.calculate_metrics()?;
[INFO] [stdout]     |                                          ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:677:40
[INFO] [stdout]     |
[INFO] [stdout] 677 |     let data = generate_cv_test_data::<f32>(
[INFO] [stdout]     |                                        ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_cv_test_data`
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 24  | fn generate_cv_test_data<T: Float>(
[INFO] [stdout]     |    --------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_cv_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_metrics` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:702:30
[INFO] [stdout]     |
[INFO] [stdout] 702 |     let metrics = cv_results.calculate_metrics()?;
[INFO] [stdout]     |                              ^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_directional_accuracy` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:714:43
[INFO] [stdout]     |
[INFO] [stdout] 714 |     let directional_accuracy = cv_results.calculate_directional_accuracy()?;
[INFO] [stdout]     |                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_intervals` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:718:19
[INFO] [stdout]     |
[INFO] [stdout] 718 |     if cv_results.has_intervals() {
[INFO] [stdout]     |                   ^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `calculate_interval_coverage` found for struct `CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/cross_validation_tests.rs:719:35
[INFO] [stdout]     |
[INFO] [stdout] 719 |         let coverage = cv_results.calculate_interval_coverage()?;
[INFO] [stdout]     |                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^ method not found in `CrossValidationDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:61:29
[INFO] [stdout]     |
[INFO] [stdout] 61  |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]   --> tests/integration/persistence_tests.rs:75:37
[INFO] [stdout]    |
[INFO] [stdout] 75 |     let data = generate_test_data::<f32>(3, 100)?;
[INFO] [stdout]    |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]    |
[INFO] [stdout]    = help: the following other types implement trait `From<T>`:
[INFO] [stdout]              `f32` implements `From<bool>`
[INFO] [stdout]              `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]              `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]              `f32` implements `From<half::bf16>`
[INFO] [stdout]              `f32` implements `From<half::f16>`
[INFO] [stdout]              `f32` implements `From<i16>`
[INFO] [stdout]              `f32` implements `From<i8>`
[INFO] [stdout]              `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]            and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]   --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]    |
[INFO] [stdout] 26 | fn generate_test_data<T: Float>(
[INFO] [stdout]    |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31 |     T: From<f64> + Into<f64>,
[INFO] [stdout]    |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:113:32
[INFO] [stdout]     |
[INFO] [stdout] 113 |     assert_eq!(forecast_before.horizon(), forecast_after.horizon());
[INFO] [stdout]     |                                ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:113:58
[INFO] [stdout]     |
[INFO] [stdout] 113 |     assert_eq!(forecast_before.horizon(), forecast_after.horizon());
[INFO] [stdout]     |                                                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:125:37
[INFO] [stdout]     |
[INFO] [stdout] 125 |     let data = generate_test_data::<f32>(2, 150)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:179:37
[INFO] [stdout]     |
[INFO] [stdout] 179 |     let data = generate_test_data::<f32>(2, 100)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `get_model_configs` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:212:27
[INFO] [stdout]     |
[INFO] [stdout] 212 |         model_configs: nf.get_model_configs()?,
[INFO] [stdout]     |                           ^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `get_model` with a similar name, but with different arguments
[INFO] [stdout]    --> /opt/rustwide/workdir/src/neural_forecast.rs:414:5
[INFO] [stdout]     |
[INFO] [stdout] 414 |     pub fn get_model(&self, name: &str) -> Option<&dyn BaseModel<T>> {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0616]: field `num_threads` of struct `neuro_divergent::NeuralForecast` is private
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:227:26
[INFO] [stdout]     |
[INFO] [stdout] 227 |     assert_eq!(loaded_nf.num_threads, Some(4));
[INFO] [stdout]     |                          ^^^^^^^^^^^ private field
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0616]: field `local_scaler_type` of struct `neuro_divergent::NeuralForecast` is private
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:228:26
[INFO] [stdout]     |
[INFO] [stdout] 228 |     assert_eq!(loaded_nf.local_scaler_type, Some(ScalerType::StandardScaler));
[INFO] [stdout]     |                          ^^^^^^^^^^^^^^^^^ private field
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:246:45
[INFO] [stdout]     |
[INFO] [stdout] 246 |     let initial_data = generate_test_data::<f32>(2, 100)?;
[INFO] [stdout]     |                                             ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:266:41
[INFO] [stdout]     |
[INFO] [stdout] 266 |     let new_data = generate_test_data::<f32>(2, 50)?;
[INFO] [stdout]     |                                         ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `fit_incremental` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:272:15
[INFO] [stdout]     |
[INFO] [stdout] 272 |     loaded_nf.fit_incremental(new_data)?;
[INFO] [stdout]     |               ^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:280:26
[INFO] [stdout]     |
[INFO] [stdout] 280 |     assert_eq!(forecasts.horizon(), 7);
[INFO] [stdout]     |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:294:37
[INFO] [stdout]     |
[INFO] [stdout] 294 |     let data = generate_test_data::<f32>(2, 100)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `save_with_version` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:309:11
[INFO] [stdout]     |
[INFO] [stdout] 309 |     nf_v1.save_with_version(&v1_path, "1.0.0")?;
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `save_with_version` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:327:11
[INFO] [stdout]     |
[INFO] [stdout] 327 |     nf_v2.save_with_version(&v2_path, "2.0.0")?;
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `get_version_info` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:334:29
[INFO] [stdout]     |
[INFO] [stdout] 334 |     let v1_info = loaded_v1.get_version_info()?;
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `get_version_info` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:335:29
[INFO] [stdout]     |
[INFO] [stdout] 335 |     let v2_info = loaded_v2.get_version_info()?;
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:351:37
[INFO] [stdout]     |
[INFO] [stdout] 351 |     let data = generate_test_data::<f32>(50, 500)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:403:37
[INFO] [stdout]     |
[INFO] [stdout] 403 |     let data = generate_test_data::<f32>(3, 200)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `load_from_checkpoint` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:443:46
[INFO] [stdout]     |
[INFO] [stdout] 443 |     let restored_nf = NeuralForecast::<f32>::load_from_checkpoint(
[INFO] [stdout]     |                                              ^^^^^^^^^^^^^^^^^^^^ function or associated item not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::NeuralForecast<f32>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::NeuralForecast::<T>::new
[INFO] [stdout]       neuro_divergent::NeuralForecast::<T>::load
[INFO] [stdout]    --> /opt/rustwide/workdir/src/neural_forecast.rs:149:5
[INFO] [stdout]     |
[INFO] [stdout] 149 | /     pub fn new(
[INFO] [stdout] 150 | |         models: Vec<Box<dyn BaseModel<T>>>, 
[INFO] [stdout] 151 | |         frequency: Frequency
[INFO] [stdout] 152 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 476 |       pub fn load<P: AsRef<Path>>(_path: P) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:461:37
[INFO] [stdout]     |
[INFO] [stdout] 461 |     let data = generate_test_data::<f32>(3, 100)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `save_compressed` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:483:8
[INFO] [stdout]     |
[INFO] [stdout] 483 |     nf.save_compressed(&compressed_path)?;
[INFO] [stdout]     |        ^^^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `load_compressed` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:492:44
[INFO] [stdout]     |
[INFO] [stdout] 492 |     let loaded_nf = NeuralForecast::<f32>::load_compressed(&compressed_path)?;
[INFO] [stdout]     |                                            ^^^^^^^^^^^^^^^ function or associated item not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::NeuralForecast<f32>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::NeuralForecast::<T>::new
[INFO] [stdout]       neuro_divergent::NeuralForecast::<T>::load
[INFO] [stdout]    --> /opt/rustwide/workdir/src/neural_forecast.rs:149:5
[INFO] [stdout]     |
[INFO] [stdout] 149 | /     pub fn new(
[INFO] [stdout] 150 | |         models: Vec<Box<dyn BaseModel<T>>>, 
[INFO] [stdout] 151 | |         frequency: Frequency
[INFO] [stdout] 152 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 476 |       pub fn load<P: AsRef<Path>>(_path: P) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:509:37
[INFO] [stdout]     |
[INFO] [stdout] 509 |     let data = generate_test_data::<f32>(2, 100)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `export_onnx` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:529:8
[INFO] [stdout]     |
[INFO] [stdout] 529 |     nf.export_onnx(&onnx_path)?;
[INFO] [stdout]     |        ^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `export_json` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:534:8
[INFO] [stdout]     |
[INFO] [stdout] 534 |     nf.export_json(&json_path)?;
[INFO] [stdout]     |        ^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `export_binary` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:539:8
[INFO] [stdout]     |
[INFO] [stdout] 539 |     nf.export_binary(&bin_path)?;
[INFO] [stdout]     |        ^^^^^^^^^^^^^ method not found in `neuro_divergent::NeuralForecast<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:555:37
[INFO] [stdout]     |
[INFO] [stdout] 555 |     let data = generate_test_data::<f32>(5, 150)?;
[INFO] [stdout]     |                                     ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_test_data`
[INFO] [stdout]    --> tests/integration/persistence_tests.rs:31:8
[INFO] [stdout]     |
[INFO] [stdout] 26  | fn generate_test_data<T: Float>(
[INFO] [stdout]     |    ------------------ required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 31  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:76:29
[INFO] [stdout]     |
[INFO] [stdout] 76  |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]   --> tests/integration/preprocessing_tests.rs:87:51
[INFO] [stdout]    |
[INFO] [stdout] 87 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]    |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]    |
[INFO] [stdout]    = help: the following other types implement trait `From<T>`:
[INFO] [stdout]              `f32` implements `From<bool>`
[INFO] [stdout]              `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]              `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]              `f32` implements `From<half::bf16>`
[INFO] [stdout]              `f32` implements `From<half::f16>`
[INFO] [stdout]              `f32` implements `From<i16>`
[INFO] [stdout]              `f32` implements `From<i8>`
[INFO] [stdout]              `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]            and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]   --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]    |
[INFO] [stdout] 27 | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]    |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34 |     T: From<f64> + Into<f64>,
[INFO] [stdout]    |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:172:51
[INFO] [stdout]     |
[INFO] [stdout] 172 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:235:51
[INFO] [stdout]     |
[INFO] [stdout] 235 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:296:51
[INFO] [stdout]     |
[INFO] [stdout] 296 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `builder` found for struct `FeatureEngineeringPipeline` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:304:56
[INFO] [stdout]     |
[INFO] [stdout] 304 |     let feature_pipeline = FeatureEngineeringPipeline::builder()
[INFO] [stdout]     |                                                        ^^^^^^^ function or associated item not found in `FeatureEngineeringPipeline`
[INFO] [stdout] ...
[INFO] [stdout] 709 | struct FeatureEngineeringPipeline;
[INFO] [stdout]     | --------------------------------- function or associated item `builder` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following trait defines an item `builder`, perhaps you need to implement it:
[INFO] [stdout]             candidate #1: `neuro_divergent::neuro_divergent_core::ModelConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:355:55
[INFO] [stdout]     |
[INFO] [stdout] 355 |     let mut data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                       ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:363:23
[INFO] [stdout]     |
[INFO] [stdout] 363 |     let mut df = data.to_polars()?;
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `from_validation_report` found for struct `DataFixer` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:392:28
[INFO] [stdout]     |
[INFO] [stdout] 392 |     let fixer = DataFixer::from_validation_report(&report);
[INFO] [stdout]     |                            ^^^^^^^^^^^^^^^^^^^^^^ function or associated item not found in `DataFixer`
[INFO] [stdout] ...
[INFO] [stdout] 715 | struct DataFixer;
[INFO] [stdout]     | ---------------- function or associated item `from_validation_report` not found for this struct
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:411:51
[INFO] [stdout]     |
[INFO] [stdout] 411 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `builder` found for struct `PreprocessingPipeline` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:419:43
[INFO] [stdout]     |
[INFO] [stdout] 419 |     let pipeline = PreprocessingPipeline::builder()
[INFO] [stdout]     |                                           ^^^^^^^ function or associated item not found in `PreprocessingPipeline`
[INFO] [stdout] ...
[INFO] [stdout] 710 | struct PreprocessingPipeline;
[INFO] [stdout]     | ---------------------------- function or associated item `builder` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following trait defines an item `builder`, perhaps you need to implement it:
[INFO] [stdout]             candidate #1: `neuro_divergent::neuro_divergent_core::ModelConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `MissingValueImputer` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:423:49
[INFO] [stdout]     |
[INFO] [stdout] 423 |         .add_step(Box::new(MissingValueImputer::new(
[INFO] [stdout]     |                                                 ^^^ function or associated item not found in `MissingValueImputer`
[INFO] [stdout] ...
[INFO] [stdout] 712 | struct MissingValueImputer;
[INFO] [stdout]     | -------------------------- function or associated item `new` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `new`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `HashMapExt`
[INFO] [stdout]             candidate #2: `HashSetExt`
[INFO] [stdout]             candidate #3: `RollingAggWindowNoNulls`
[INFO] [stdout]             candidate #4: `RollingAggWindowNulls`
[INFO] [stdout]             candidate #5: `UniformSampler`
[INFO] [stdout]             candidate #6: `brotli::enc::backward_references::hash_to_binary_tree::Allocable`
[INFO] [stdout]             candidate #7: `brotli::enc::threading::AnyBoxConstructor`
[INFO] [stdout]             candidate #8: `criterion::stats::tuple::TupledDistributionsBuilder`
[INFO] [stdout]             candidate #9: `crypto_common::KeyInit`
[INFO] [stdout]             candidate #10: `crypto_common::KeyIvInit`
[INFO] [stdout]             candidate #11: `digest::VariableOutput`
[INFO] [stdout]             candidate #12: `digest::core_api::VariableOutputCore`
[INFO] [stdout]             candidate #13: `digest::digest::Digest`
[INFO] [stdout]             candidate #14: `gimli::read::lookup::PubStuffEntry`
[INFO] [stdout]             candidate #15: `ndarray::data_traits::DataOwned`
[INFO] [stdout]             candidate #16: `neuro_divergent::neuro_divergent_core::BaseModel`
[INFO] [stdout]             candidate #17: `neuro_divergent::neuro_divergent_core::InitHashMaps`
[INFO] [stdout]             candidate #18: `neuro_divergent::neuro_divergent_core::InitHashMaps2`
[INFO] [stdout]             candidate #19: `neuro_divergent::neuro_divergent_core::NamedFrom`
[INFO] [stdout]             candidate #20: `neuro_divergent::neuro_divergent_core::SerReader`
[INFO] [stdout]             candidate #21: `neuro_divergent::neuro_divergent_core::SerWriter`
[INFO] [stdout]             candidate #22: `parking_lot_core::thread_parker::ThreadParkerT`
[INFO] [stdout]             candidate #23: `plotters::style::font::FontData`
[INFO] [stdout]             candidate #24: `rand::distr::uniform::UniformSampler`
[INFO] [stdout]             candidate #25: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsMap`
[INFO] [stdout]             candidate #26: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsSet`
[INFO] [stdout]             candidate #27: `serde_with::duplicate_key_impls::first_value_wins::DuplicateInsertsFirstWinsMap`
[INFO] [stdout]             candidate #28: `serde_with::duplicate_key_impls::last_value_wins::DuplicateInsertsLastWinsSet`
[INFO] [stdout]             candidate #29: `simdutf8::basic::imp::ChunkedUtf8Validator`
[INFO] [stdout]             candidate #30: `simdutf8::basic::imp::Utf8Validator`
[INFO] [stdout]             candidate #31: `typenum::marker_traits::Bit`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `OutlierHandler` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:427:44
[INFO] [stdout]     |
[INFO] [stdout] 427 |         .add_step(Box::new(OutlierHandler::new(
[INFO] [stdout]     |                                            ^^^ function or associated item not found in `OutlierHandler`
[INFO] [stdout] ...
[INFO] [stdout] 713 | struct OutlierHandler;
[INFO] [stdout]     | --------------------- function or associated item `new` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `new`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `HashMapExt`
[INFO] [stdout]             candidate #2: `HashSetExt`
[INFO] [stdout]             candidate #3: `RollingAggWindowNoNulls`
[INFO] [stdout]             candidate #4: `RollingAggWindowNulls`
[INFO] [stdout]             candidate #5: `UniformSampler`
[INFO] [stdout]             candidate #6: `brotli::enc::backward_references::hash_to_binary_tree::Allocable`
[INFO] [stdout]             candidate #7: `brotli::enc::threading::AnyBoxConstructor`
[INFO] [stdout]             candidate #8: `criterion::stats::tuple::TupledDistributionsBuilder`
[INFO] [stdout]             candidate #9: `crypto_common::KeyInit`
[INFO] [stdout]             candidate #10: `crypto_common::KeyIvInit`
[INFO] [stdout]             candidate #11: `digest::VariableOutput`
[INFO] [stdout]             candidate #12: `digest::core_api::VariableOutputCore`
[INFO] [stdout]             candidate #13: `digest::digest::Digest`
[INFO] [stdout]             candidate #14: `gimli::read::lookup::PubStuffEntry`
[INFO] [stdout]             candidate #15: `ndarray::data_traits::DataOwned`
[INFO] [stdout]             candidate #16: `neuro_divergent::neuro_divergent_core::BaseModel`
[INFO] [stdout]             candidate #17: `neuro_divergent::neuro_divergent_core::InitHashMaps`
[INFO] [stdout]             candidate #18: `neuro_divergent::neuro_divergent_core::InitHashMaps2`
[INFO] [stdout]             candidate #19: `neuro_divergent::neuro_divergent_core::NamedFrom`
[INFO] [stdout]             candidate #20: `neuro_divergent::neuro_divergent_core::SerReader`
[INFO] [stdout]             candidate #21: `neuro_divergent::neuro_divergent_core::SerWriter`
[INFO] [stdout]             candidate #22: `parking_lot_core::thread_parker::ThreadParkerT`
[INFO] [stdout]             candidate #23: `plotters::style::font::FontData`
[INFO] [stdout]             candidate #24: `rand::distr::uniform::UniformSampler`
[INFO] [stdout]             candidate #25: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsMap`
[INFO] [stdout]             candidate #26: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsSet`
[INFO] [stdout]             candidate #27: `serde_with::duplicate_key_impls::first_value_wins::DuplicateInsertsFirstWinsMap`
[INFO] [stdout]             candidate #28: `serde_with::duplicate_key_impls::last_value_wins::DuplicateInsertsLastWinsSet`
[INFO] [stdout]             candidate #29: `simdutf8::basic::imp::ChunkedUtf8Validator`
[INFO] [stdout]             candidate #30: `simdutf8::basic::imp::Utf8Validator`
[INFO] [stdout]             candidate #31: `typenum::marker_traits::Bit`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `FeatureEngineer` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:432:45
[INFO] [stdout]     |
[INFO] [stdout] 432 |         .add_step(Box::new(FeatureEngineer::new()
[INFO] [stdout]     |                                             ^^^ function or associated item not found in `FeatureEngineer`
[INFO] [stdout] ...
[INFO] [stdout] 714 | struct FeatureEngineer;
[INFO] [stdout]     | ---------------------- function or associated item `new` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `new`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `HashMapExt`
[INFO] [stdout]             candidate #2: `HashSetExt`
[INFO] [stdout]             candidate #3: `RollingAggWindowNoNulls`
[INFO] [stdout]             candidate #4: `RollingAggWindowNulls`
[INFO] [stdout]             candidate #5: `UniformSampler`
[INFO] [stdout]             candidate #6: `brotli::enc::backward_references::hash_to_binary_tree::Allocable`
[INFO] [stdout]             candidate #7: `brotli::enc::threading::AnyBoxConstructor`
[INFO] [stdout]             candidate #8: `criterion::stats::tuple::TupledDistributionsBuilder`
[INFO] [stdout]             candidate #9: `crypto_common::KeyInit`
[INFO] [stdout]             candidate #10: `crypto_common::KeyIvInit`
[INFO] [stdout]             candidate #11: `digest::VariableOutput`
[INFO] [stdout]             candidate #12: `digest::core_api::VariableOutputCore`
[INFO] [stdout]             candidate #13: `digest::digest::Digest`
[INFO] [stdout]             candidate #14: `gimli::read::lookup::PubStuffEntry`
[INFO] [stdout]             candidate #15: `ndarray::data_traits::DataOwned`
[INFO] [stdout]             candidate #16: `neuro_divergent::neuro_divergent_core::BaseModel`
[INFO] [stdout]             candidate #17: `neuro_divergent::neuro_divergent_core::InitHashMaps`
[INFO] [stdout]             candidate #18: `neuro_divergent::neuro_divergent_core::InitHashMaps2`
[INFO] [stdout]             candidate #19: `neuro_divergent::neuro_divergent_core::NamedFrom`
[INFO] [stdout]             candidate #20: `neuro_divergent::neuro_divergent_core::SerReader`
[INFO] [stdout]             candidate #21: `neuro_divergent::neuro_divergent_core::SerWriter`
[INFO] [stdout]             candidate #22: `parking_lot_core::thread_parker::ThreadParkerT`
[INFO] [stdout]             candidate #23: `plotters::style::font::FontData`
[INFO] [stdout]             candidate #24: `rand::distr::uniform::UniformSampler`
[INFO] [stdout]             candidate #25: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsMap`
[INFO] [stdout]             candidate #26: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsSet`
[INFO] [stdout]             candidate #27: `serde_with::duplicate_key_impls::first_value_wins::DuplicateInsertsFirstWinsMap`
[INFO] [stdout]             candidate #28: `serde_with::duplicate_key_impls::last_value_wins::DuplicateInsertsLastWinsSet`
[INFO] [stdout]             candidate #29: `simdutf8::basic::imp::ChunkedUtf8Validator`
[INFO] [stdout]             candidate #30: `simdutf8::basic::imp::Utf8Validator`
[INFO] [stdout]             candidate #31: `typenum::marker_traits::Bit`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:477:55
[INFO] [stdout]     |
[INFO] [stdout] 477 |     let mut data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                       ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:485:23
[INFO] [stdout]     |
[INFO] [stdout] 485 |     let mut df = data.to_polars()?;
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `exog_cols` on type `neuro_divergent::results::TimeSeriesSchema`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:517:12
[INFO] [stdout]     |
[INFO] [stdout] 517 |     schema.exog_cols = vec![
[INFO] [stdout]     |            ^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `unique_id_col`, `ds_col`, `y_col`, `static_features`, `exogenous_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:523:33
[INFO] [stdout]     |
[INFO] [stdout] 523 |     data = TimeSeriesDataFrame::new(df, schema, data.frequency);
[INFO] [stdout]     |                                 ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `builder` found for struct `ExogenousPreprocessor` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:526:52
[INFO] [stdout]     |
[INFO] [stdout] 526 |     let exog_preprocessor = ExogenousPreprocessor::builder()
[INFO] [stdout]     |                                                    ^^^^^^^ function or associated item not found in `ExogenousPreprocessor`
[INFO] [stdout] ...
[INFO] [stdout] 711 | struct ExogenousPreprocessor;
[INFO] [stdout]     | ---------------------------- function or associated item `builder` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following trait defines an item `builder`, perhaps you need to implement it:
[INFO] [stdout]             candidate #1: `neuro_divergent::neuro_divergent_core::ModelConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `f32: From<f64>` is not satisfied
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:573:51
[INFO] [stdout]     |
[INFO] [stdout] 573 |     let data = generate_preprocessing_test_data::<f32>(
[INFO] [stdout]     |                                                   ^^^ the trait `From<f64>` is not implemented for `f32`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `f32` implements `From<bool>`
[INFO] [stdout]               `f32` implements `From<ethnum::int::I256>`
[INFO] [stdout]               `f32` implements `From<ethnum::uint::U256>`
[INFO] [stdout]               `f32` implements `From<half::bf16>`
[INFO] [stdout]               `f32` implements `From<half::f16>`
[INFO] [stdout]               `f32` implements `From<i16>`
[INFO] [stdout]               `f32` implements `From<i8>`
[INFO] [stdout]               `f32` implements `From<proptest::num::float_samplers::f32::F32U>`
[INFO] [stdout]             and 3 others
[INFO] [stdout] note: required by a bound in `generate_preprocessing_test_data`
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:34:8
[INFO] [stdout]     |
[INFO] [stdout] 27  | fn generate_preprocessing_test_data<T: Float>(
[INFO] [stdout]     |    -------------------------------- required by a bound in this function
[INFO] [stdout] ...
[INFO] [stdout] 34  |     T: From<f64> + Into<f64>,
[INFO] [stdout]     |        ^^^^^^^^^ required by this bound in `generate_preprocessing_test_data`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `builder` found for struct `PreprocessingPipeline` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:583:43
[INFO] [stdout]     |
[INFO] [stdout] 583 |     let pipeline = PreprocessingPipeline::builder()
[INFO] [stdout]     |                                           ^^^^^^^ function or associated item not found in `PreprocessingPipeline`
[INFO] [stdout] ...
[INFO] [stdout] 710 | struct PreprocessingPipeline;
[INFO] [stdout]     | ---------------------------- function or associated item `builder` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following trait defines an item `builder`, perhaps you need to implement it:
[INFO] [stdout]             candidate #1: `neuro_divergent::neuro_divergent_core::ModelConfig`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `MissingValueImputer` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:584:49
[INFO] [stdout]     |
[INFO] [stdout] 584 |         .add_step(Box::new(MissingValueImputer::new(
[INFO] [stdout]     |                                                 ^^^ function or associated item not found in `MissingValueImputer`
[INFO] [stdout] ...
[INFO] [stdout] 712 | struct MissingValueImputer;
[INFO] [stdout]     | -------------------------- function or associated item `new` not found for this struct
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `new`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `HashMapExt`
[INFO] [stdout]             candidate #2: `HashSetExt`
[INFO] [stdout]             candidate #3: `RollingAggWindowNoNulls`
[INFO] [stdout]             candidate #4: `RollingAggWindowNulls`
[INFO] [stdout]             candidate #5: `UniformSampler`
[INFO] [stdout]             candidate #6: `brotli::enc::backward_references::hash_to_binary_tree::Allocable`
[INFO] [stdout]             candidate #7: `brotli::enc::threading::AnyBoxConstructor`
[INFO] [stdout]             candidate #8: `criterion::stats::tuple::TupledDistributionsBuilder`
[INFO] [stdout]             candidate #9: `crypto_common::KeyInit`
[INFO] [stdout]             candidate #10: `crypto_common::KeyIvInit`
[INFO] [stdout]             candidate #11: `digest::VariableOutput`
[INFO] [stdout]             candidate #12: `digest::core_api::VariableOutputCore`
[INFO] [stdout]             candidate #13: `digest::digest::Digest`
[INFO] [stdout]             candidate #14: `gimli::read::lookup::PubStuffEntry`
[INFO] [stdout]             candidate #15: `ndarray::data_traits::DataOwned`
[INFO] [stdout]             candidate #16: `neuro_divergent::neuro_divergent_core::BaseModel`
[INFO] [stdout]             candidate #17: `neuro_divergent::neuro_divergent_core::InitHashMaps`
[INFO] [stdout]             candidate #18: `neuro_divergent::neuro_divergent_core::InitHashMaps2`
[INFO] [stdout]             candidate #19: `neuro_divergent::neuro_divergent_core::NamedFrom`
[INFO] [stdout]             candidate #20: `neuro_divergent::neuro_divergent_core::SerReader`
[INFO] [stdout]             candidate #21: `neuro_divergent::neuro_divergent_core::SerWriter`
[INFO] [stdout]             candidate #22: `parking_lot_core::thread_parker::ThreadParkerT`
[INFO] [stdout]             candidate #23: `plotters::style::font::FontData`
[INFO] [stdout]             candidate #24: `rand::distr::uniform::UniformSampler`
[INFO] [stdout]             candidate #25: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsMap`
[INFO] [stdout]             candidate #26: `serde_with::duplicate_key_impls::error_on_duplicate::PreventDuplicateInsertsSet`
[INFO] [stdout]             candidate #27: `serde_with::duplicate_key_impls::first_value_wins::DuplicateInsertsFirstWinsMap`
[INFO] [stdout]             candidate #28: `serde_with::duplicate_key_impls::last_value_wins::DuplicateInsertsLastWinsSet`
[INFO] [stdout]             candidate #29: `simdutf8::basic::imp::ChunkedUtf8Validator`
[INFO] [stdout]             candidate #30: `simdutf8::basic::imp::Utf8Validator`
[INFO] [stdout]             candidate #31: `typenum::marker_traits::Bit`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `unique_series_ids` found for reference `&neuro_divergent::TimeSeriesDataFrame<f32>` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:623:27
[INFO] [stdout]     |
[INFO] [stdout] 623 |     for series_id in data.unique_series_ids()? {
[INFO] [stdout]     |                           ^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `unique_ids` with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 623 -     for series_id in data.unique_series_ids()? {
[INFO] [stdout] 623 +     for series_id in data.unique_ids()? {
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `filter_series` found for reference `&neuro_divergent::TimeSeriesDataFrame<f32>` in the current scope
[INFO] [stdout]    --> tests/integration/preprocessing_tests.rs:624:32
[INFO] [stdout]     |
[INFO] [stdout] 624 |         let series_data = data.filter_series(&series_id)?;
[INFO] [stdout]     |                                ^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `n_series` with a similar name, but with different arguments
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:244:5
[INFO] [stdout]     |
[INFO] [stdout] 244 |     pub fn n_series(&self) -> usize {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:62:26
[INFO] [stdout]    |
[INFO] [stdout] 62 |     assert_eq!(forecasts.horizon(), 12);
[INFO] [stdout]    |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]   --> tests/integration/api_compatibility_tests.rs:63:23
[INFO] [stdout]    |
[INFO] [stdout] 63 |     assert!(forecasts.has_column("LSTM"));
[INFO] [stdout]    |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:136:9
[INFO] [stdout]     |
[INFO] [stdout] 134 |     let intervals = PredictionIntervals::new(
[INFO] [stdout]     |                     ------------------------ arguments to this function are incorrect
[INFO] [stdout] 135 |         vec![0.80, 0.90],  // 80% and 90% intervals
[INFO] [stdout] 136 |         IntervalMethod::Quantile,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^ expected `neuro_divergent::config::IntervalMethod`, found `api_compatibility_tests::IntervalMethod`
[INFO] [stdout]     |
[INFO] [stdout]     = note: `api_compatibility_tests::IntervalMethod` and `neuro_divergent::config::IntervalMethod` have similar names, but are actually distinct types
[INFO] [stdout] note: `api_compatibility_tests::IntervalMethod` is defined in the current crate
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:774:1
[INFO] [stdout]     |
[INFO] [stdout] 774 | enum IntervalMethod {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: `neuro_divergent::config::IntervalMethod` is defined in crate `neuro_divergent`
[INFO] [stdout]    --> /opt/rustwide/workdir/src/config.rs:232:1
[INFO] [stdout]     |
[INFO] [stdout] 232 | pub enum IntervalMethod {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]    --> /opt/rustwide/workdir/src/config.rs:193:12
[INFO] [stdout]     |
[INFO] [stdout] 193 |     pub fn new(confidence_levels: Vec<f64>, method: IntervalMethod) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     |            ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:157:9
[INFO] [stdout]     |
[INFO] [stdout] 156 |       let forecasts = nf.predict_with_config(
[INFO] [stdout]     |                          ------------------- arguments to this method are incorrect
[INFO] [stdout] 157 | /         PredictionConfig::new()
[INFO] [stdout] 158 | |             .with_intervals()
[INFO] [stdout] 159 | |             .with_num_samples(100)
[INFO] [stdout]     | |__________________________________^ expected `PredictionConfig`, found a different `PredictionConfig`
[INFO] [stdout]     |
[INFO] [stdout]     = note: `PredictionConfig` and `PredictionConfig` have similar names, but are actually distinct types
[INFO] [stdout] note: `PredictionConfig` is defined in the current crate
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:767:1
[INFO] [stdout]     |
[INFO] [stdout] 767 | struct PredictionConfig;
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: `PredictionConfig` is defined in crate `neuro_divergent`
[INFO] [stdout]    --> /opt/rustwide/workdir/src/neural_forecast.rs:624:1
[INFO] [stdout]     |
[INFO] [stdout] 624 | pub struct PredictionConfig {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/workdir/src/neural_forecast.rs:297:12
[INFO] [stdout]     |
[INFO] [stdout] 297 |     pub fn predict_with_config(
[INFO] [stdout]     |            ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_intervals` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:163:23
[INFO] [stdout]     |
[INFO] [stdout] 163 |     assert!(forecasts.has_intervals());
[INFO] [stdout]     |                       ^^^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:164:23
[INFO] [stdout]     |
[INFO] [stdout] 164 |     assert!(forecasts.has_column("LSTM-lo-80"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:165:23
[INFO] [stdout]     |
[INFO] [stdout] 165 |     assert!(forecasts.has_column("LSTM-hi-80"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:166:23
[INFO] [stdout]     |
[INFO] [stdout] 166 |     assert!(forecasts.has_column("LSTM-lo-90"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:167:23
[INFO] [stdout]     |
[INFO] [stdout] 167 |     assert!(forecasts.has_column("LSTM-hi-90"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `predict_with_exogenous` found for struct `neuro_divergent::NeuralForecast` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:259:24
[INFO] [stdout]     |
[INFO] [stdout] 259 |     let forecasts = nf.predict_with_exogenous(future_df)?;
[INFO] [stdout]     |                        ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `predict_with_config` with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 259 -     let forecasts = nf.predict_with_exogenous(future_df)?;
[INFO] [stdout] 259 +     let forecasts = nf.predict_with_config(future_df)?;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:412:13
[INFO] [stdout]     |
[INFO] [stdout] 408 |         .early_stopping(EarlyStoppingConfig::new(
[INFO] [stdout]     |                         ------------------------ arguments to this function are incorrect
[INFO] [stdout] ...
[INFO] [stdout] 412 |             EarlyStoppingMode::Min,
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^^^ expected `EarlyStoppingMode`, found a different `EarlyStoppingMode`
[INFO] [stdout]     |
[INFO] [stdout]     = note: `EarlyStoppingMode` and `EarlyStoppingMode` have similar names, but are actually distinct types
[INFO] [stdout] note: `EarlyStoppingMode` is defined in the current crate
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:762:1
[INFO] [stdout]     |
[INFO] [stdout] 762 | enum EarlyStoppingMode {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: `EarlyStoppingMode` is defined in crate `neuro_divergent`
[INFO] [stdout]    --> /opt/rustwide/workdir/src/config.rs:423:1
[INFO] [stdout]     |
[INFO] [stdout] 423 | pub enum EarlyStoppingMode {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]    --> /opt/rustwide/workdir/src/config.rs:398:12
[INFO] [stdout]     |
[INFO] [stdout] 398 |     pub fn new(monitor: String, patience: usize, min_delta: T, mode: EarlyStoppingMode) -> Self {
[INFO] [stdout]     |            ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:465:26
[INFO] [stdout]     |
[INFO] [stdout] 465 |     assert_eq!(forecasts.horizon(), 12);
[INFO] [stdout]     |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:466:23
[INFO] [stdout]     |
[INFO] [stdout] 466 |     assert!(forecasts.has_column("LSTM"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `unique_values` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:495:32
[INFO] [stdout]     |
[INFO] [stdout] 495 |     let unique_ids = forecasts.unique_values("unique_id")?;
[INFO] [stdout]     |                                ^^^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `horizon` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:562:26
[INFO] [stdout]     |
[INFO] [stdout] 562 |     assert_eq!(forecasts.horizon(), 14);
[INFO] [stdout]     |                          ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:586:23
[INFO] [stdout]     |
[INFO] [stdout] 586 |     assert!(forecasts.has_column("unique_id"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:587:23
[INFO] [stdout]     |
[INFO] [stdout] 587 |     assert!(forecasts.has_column("ds"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `has_column` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:588:23
[INFO] [stdout]     |
[INFO] [stdout] 588 |     assert!(forecasts.has_column("LSTM"));
[INFO] [stdout]     |                       ^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_pandas_format` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:591:31
[INFO] [stdout]     |
[INFO] [stdout] 591 |     let pandas_df = forecasts.to_pandas_format()?;
[INFO] [stdout]     |                               ^^^^^^^^^^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_json` found for struct `neuro_divergent::ForecastDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:594:33
[INFO] [stdout]     |
[INFO] [stdout] 594 |     let json_output = forecasts.to_json()?;
[INFO] [stdout]     |                                 ^^^^^^^ method not found in `neuro_divergent::ForecastDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:626:29
[INFO] [stdout]     |
[INFO] [stdout] 626 |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `to_polars` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:635:26
[INFO] [stdout]     |
[INFO] [stdout] 635 |     let mut df = base_df.to_polars()?;
[INFO] [stdout]     |                          ^^^^^^^^^ method not found in `neuro_divergent::TimeSeriesDataFrame<f32>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `exog_cols` on type `neuro_divergent::results::TimeSeriesSchema`
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:653:12
[INFO] [stdout]     |
[INFO] [stdout] 653 |     schema.exog_cols = vec!["temperature".to_string(), "holiday".to_string()];
[INFO] [stdout]     |            ^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `unique_id_col`, `ds_col`, `y_col`, `static_features`, `exogenous_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `static_cols` on type `neuro_divergent::results::TimeSeriesSchema`
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:654:12
[INFO] [stdout]     |
[INFO] [stdout] 654 |     schema.static_cols = vec!["location".to_string()];
[INFO] [stdout]     |            ^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `unique_id_col`, `ds_col`, `y_col`, `static_features`, `exogenous_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:656:29
[INFO] [stdout]     |
[INFO] [stdout] 656 |     Ok(TimeSeriesDataFrame::new(df, schema, base_df.frequency))
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:690:29
[INFO] [stdout]     |
[INFO] [stdout] 690 |     Ok(TimeSeriesDataFrame::new(df, schema, Some(Frequency::Daily)))
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:716:29
[INFO] [stdout]     |
[INFO] [stdout] 716 |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent::TimeSeriesDataFrame` in the current scope
[INFO] [stdout]    --> tests/integration/api_compatibility_tests.rs:743:29
[INFO] [stdout]     |
[INFO] [stdout] 743 |     Ok(TimeSeriesDataFrame::new(
[INFO] [stdout]     |                             ^^^ function or associated item not found in `neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent::TimeSeriesDataFrame<_>` consider using one of the following associated functions:
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_polars
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_csv
[INFO] [stdout]       neuro_divergent::TimeSeriesDataFrame::<T>::from_parquet
[INFO] [stdout]    --> /opt/rustwide/workdir/src/results.rs:126:5
[INFO] [stdout]     |
[INFO] [stdout] 126 | /     pub fn from_polars(
[INFO] [stdout] 127 | |         df: DataFrame, 
[INFO] [stdout] 128 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 129 | |         frequency: Option<Frequency>,
[INFO] [stdout] 130 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 143 | /     pub fn from_csv<P: AsRef<Path>>(
[INFO] [stdout] 144 | |         path: P,
[INFO] [stdout] 145 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 146 | |         frequency: Option<Frequency>,
[INFO] [stdout] 147 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] ...
[INFO] [stdout] 157 | /     pub fn from_parquet<P: AsRef<Path>>(
[INFO] [stdout] 158 | |         path: P,
[INFO] [stdout] 159 | |         schema: TimeSeriesSchema,
[INFO] [stdout] 160 | |         frequency: Option<Frequency>,
[INFO] [stdout] 161 | |     ) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     | |___________________________________^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0034, E0277, E0308, E0405, E0422, E0432, E0433, E0599, E0609...
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0034`.
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `neuro-divergent` (test "integration") due to 191 previous errors; 11 warnings emitted
[INFO] [stdout] warning: unexpected `cfg` condition value: `integration-tests`
[INFO] [stdout]   --> tests/lib.rs:33:7
[INFO] [stdout]    |
[INFO] [stdout] 33 | #[cfg(feature = "integration-tests")]
[INFO] [stdout]    |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]    = help: consider adding `integration-tests` as a feature in `Cargo.toml`
[INFO] [stdout]    = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout]    = note: `#[warn(unexpected_cfgs)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unexpected `cfg` condition value: `bench-tests`
[INFO] [stdout]   --> tests/lib.rs:39:7
[INFO] [stdout]    |
[INFO] [stdout] 39 | #[cfg(feature = "bench-tests")]
[INFO] [stdout]    |       ^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected values for `feature` are: `async`, `candle-core`, `candle-nn`, `default`, `futures`, `gpu`, `models`, `python-compat`, `registry`, `std`, `tokio`, and `tracing`
[INFO] [stdout]    = help: consider adding `bench-tests` as a feature in `Cargo.toml`
[INFO] [stdout]    = note: see <https://doc.rust-lang.org/nightly/rustc/check-cfg/cargo-specifics.html> for more information about checking conditional configuration
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `TimeZone` and `Utc`
[INFO] [stdout]  --> tests/unit/core_tests.rs:9:24
[INFO] [stdout]   |
[INFO] [stdout] 9 | use chrono::{DateTime, TimeZone, Utc};
[INFO] [stdout]   |                        ^^^^^^^^  ^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/core_tests.rs:13:5
[INFO] [stdout]    |
[INFO] [stdout] 13 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Deserialize` and `Serialize`
[INFO] [stdout]   --> tests/unit/core_tests.rs:15:13
[INFO] [stdout]    |
[INFO] [stdout] 15 | use serde::{Deserialize, Serialize};
[INFO] [stdout]    |             ^^^^^^^^^^^  ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::errors::*`
[INFO] [stdout]  --> tests/unit/models/recurrent_tests.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent_models::errors::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Array1` and `Axis`
[INFO] [stdout]   --> tests/unit/models/recurrent_tests.rs:11:15
[INFO] [stdout]    |
[INFO] [stdout] 11 | use ndarray::{Array1, Array2, Array3, Axis};
[INFO] [stdout]    |               ^^^^^^                  ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/models/recurrent_tests.rs:15:5
[INFO] [stdout]    |
[INFO] [stdout] 15 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::config::*`
[INFO] [stdout]  --> tests/unit/models/advanced_tests.rs:8:5
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent_models::config::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::errors::*`
[INFO] [stdout]  --> tests/unit/models/advanced_tests.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent_models::errors::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Array1`
[INFO] [stdout]   --> tests/unit/models/advanced_tests.rs:11:15
[INFO] [stdout]    |
[INFO] [stdout] 11 | use ndarray::{Array1, Array2, Array3};
[INFO] [stdout]    |               ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/models/advanced_tests.rs:15:5
[INFO] [stdout]    |
[INFO] [stdout] 15 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::config::*`
[INFO] [stdout]  --> tests/unit/models/transformer_tests.rs:8:5
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent_models::config::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::errors::*`
[INFO] [stdout]  --> tests/unit/models/transformer_tests.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent_models::errors::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Axis`
[INFO] [stdout]   --> tests/unit/models/transformer_tests.rs:11:39
[INFO] [stdout]    |
[INFO] [stdout] 11 | use ndarray::{Array1, Array2, Array3, Axis};
[INFO] [stdout]    |                                       ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/models/transformer_tests.rs:15:5
[INFO] [stdout]    |
[INFO] [stdout] 15 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::config::*`
[INFO] [stdout]  --> tests/unit/models/specialized_tests.rs:8:5
[INFO] [stdout]   |
[INFO] [stdout] 8 | use neuro_divergent_models::config::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent_models::errors::*`
[INFO] [stdout]  --> tests/unit/models/specialized_tests.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 | use neuro_divergent_models::errors::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Array1` and `Axis`
[INFO] [stdout]   --> tests/unit/models/specialized_tests.rs:11:15
[INFO] [stdout]    |
[INFO] [stdout] 11 | use ndarray::{Array1, Array2, Array3, Axis, s};
[INFO] [stdout]    |               ^^^^^^                  ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/models/specialized_tests.rs:15:5
[INFO] [stdout]    |
[INFO] [stdout] 15 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `neuro_divergent::prelude::*`
[INFO] [stdout]  --> tests/unit/training_tests.rs:6:5
[INFO] [stdout]   |
[INFO] [stdout] 6 | use neuro_divergent::prelude::*;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::collections::HashMap`
[INFO] [stdout]   --> tests/unit/training_tests.rs:13:5
[INFO] [stdout]    |
[INFO] [stdout] 13 | use std::collections::HashMap;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `DateTime`, `NaiveDate`, `TimeZone`, and `Utc`
[INFO] [stdout]   --> tests/unit/data_tests.rs:14:14
[INFO] [stdout]    |
[INFO] [stdout] 14 | use chrono::{DateTime, TimeZone, Utc, NaiveDate};
[INFO] [stdout]    |              ^^^^^^^^  ^^^^^^^^  ^^^  ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused imports: `Deserialize` and `Serialize`
[INFO] [stdout]   --> tests/unit/data_tests.rs:15:13
[INFO] [stdout]    |
[INFO] [stdout] 15 | use serde::{Deserialize, Serialize};
[INFO] [stdout]    |             ^^^^^^^^^^^  ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `std::io::Write`
[INFO] [stdout]   --> tests/unit/data_tests.rs:17:5
[INFO] [stdout]    |
[INFO] [stdout] 17 | use std::io::Write;
[INFO] [stdout]    |     ^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Array1`
[INFO] [stdout]   --> tests/lib.rs:47:19
[INFO] [stdout]    |
[INFO] [stdout] 47 |     use ndarray::{Array1, Array2};
[INFO] [stdout]    |                   ^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0107]: missing generics for enum `test_utils::SeriesPattern`
[INFO] [stdout]    --> tests/lib.rs:55:18
[INFO] [stdout]     |
[INFO] [stdout] 55  |         pattern: SeriesPattern,
[INFO] [stdout]     |                  ^^^^^^^^^^^^^ expected 1 generic argument
[INFO] [stdout]     |
[INFO] [stdout] note: enum defined here, with 1 generic parameter: `T`
[INFO] [stdout]    --> tests/lib.rs:101:14
[INFO] [stdout]     |
[INFO] [stdout] 101 |     pub enum SeriesPattern<T: Float> {
[INFO] [stdout]     |              ^^^^^^^^^^^^^ -
[INFO] [stdout] help: add missing generic argument
[INFO] [stdout]     |
[INFO] [stdout] 55  |         pattern: SeriesPattern<T>,
[INFO] [stdout]     |                               +++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0053]: method `validate` has an incompatible type for trait
[INFO] [stdout]   --> tests/unit/models/basic_tests.rs:71:27
[INFO] [stdout]    |
[INFO] [stdout] 71 |     fn validate(&self) -> NeuroDivergentResult<()> {
[INFO] [stdout]    |                           ^^^^^^^^^^^^^^^^^^^^^^^^ expected `NeuroDivergentError`, found `neuro_divergent::NeuroDivergentError`
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected signature `fn(&basic_tests::MockMLPConfig<_>) -> Result<_, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]               found signature `fn(&basic_tests::MockMLPConfig<_>) -> Result<_, neuro_divergent::NeuroDivergentError>`
[INFO] [stdout] help: change the output type to match the trait
[INFO] [stdout]    |
[INFO] [stdout] 71 -     fn validate(&self) -> NeuroDivergentResult<()> {
[INFO] [stdout] 71 +     fn validate(&self) -> Result<(), neuro_divergent_core::NeuroDivergentError> {
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0046]: not all trait items implemented, missing: `output_size`, `exogenous_config`, `to_parameters`, `from_parameters`, `builder`
[INFO] [stdout]   --> tests/unit/models/basic_tests.rs:62:1
[INFO] [stdout]    |
[INFO] [stdout] 62 | impl<T: Float> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]    | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ missing `output_size`, `exogenous_config`, `to_parameters`, `from_parameters`, `builder` in implementation
[INFO] [stdout]    |
[INFO] [stdout]    = help: implement the missing item: `fn output_size(&self) -> usize { todo!() }`
[INFO] [stdout]    = help: implement the missing item: `fn exogenous_config(&self) -> &ExogenousConfig { todo!() }`
[INFO] [stdout]    = help: implement the missing item: `fn to_parameters(&self) -> std::collections::HashMap<std::string::String, ConfigParameter<T>> { todo!() }`
[INFO] [stdout]    = help: implement the missing item: `fn from_parameters<Self>(_: std::collections::HashMap<std::string::String, ConfigParameter<T>>) -> Result<Self, neuro_divergent_core::NeuroDivergentError> { todo!() }`
[INFO] [stdout]    = help: implement the missing item: `fn builder<Self>() -> impl ConfigBuilder<Self, T> { todo!() }`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be shared between threads safely
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:62:16
[INFO] [stdout]     |
[INFO] [stdout] 62  | impl<T: Float> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]     |                ^^^^^^^^^^^^^^ `T` cannot be shared between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required by a bound in `neuro_divergent_core::ModelConfig`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:153:41
[INFO] [stdout]     |
[INFO] [stdout] 153 | pub trait ModelConfig<T: Float + Send + Sync + 'static>: Clone + Send + Sync + 'static {
[INFO] [stdout]     |                                         ^^^^ required by this bound in `ModelConfig`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Sync`
[INFO] [stdout]     |
[INFO] [stdout] 62  | impl<T: Float + std::marker::Sync> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be sent between threads safely
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:62:16
[INFO] [stdout]     |
[INFO] [stdout] 62  | impl<T: Float> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]     |                ^^^^^^^^^^^^^^ `T` cannot be sent between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required by a bound in `neuro_divergent_core::ModelConfig`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:153:34
[INFO] [stdout]     |
[INFO] [stdout] 153 | pub trait ModelConfig<T: Float + Send + Sync + 'static>: Clone + Send + Sync + 'static {
[INFO] [stdout]     |                                  ^^^^ required by this bound in `ModelConfig`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Send`
[INFO] [stdout]     |
[INFO] [stdout] 62  | impl<T: Float + std::marker::Send> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0310]: the parameter type `T` may not live long enough
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:119:19
[INFO] [stdout]     |
[INFO] [stdout] 119 |     type Config = MockMLPConfig<T>;
[INFO] [stdout]     |                   ^^^^^^^^^^^^^^^^
[INFO] [stdout]     |                   |
[INFO] [stdout]     |                   the parameter type `T` must be valid for the static lifetime...
[INFO] [stdout]     |                   ...so that the type `basic_tests::MockMLPConfig<T>` will meet its required lifetime bounds...
[INFO] [stdout]     |
[INFO] [stdout] note: ...that is required by this bound
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:46:18
[INFO] [stdout]     |
[INFO] [stdout] 46  |     type Config: ModelConfig<T>;
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^
[INFO] [stdout] help: consider adding an explicit lifetime bound
[INFO] [stdout]     |
[INFO] [stdout] 118 | impl<T: Float + Send + Sync + 'static> BaseModel<T> for MockMLP<T> {
[INFO] [stdout]     |                             +++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0310]: the parameter type `T` may not live long enough
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:119:19
[INFO] [stdout]     |
[INFO] [stdout] 119 |     type Config = MockMLPConfig<T>;
[INFO] [stdout]     |                   ^^^^^^^^^^^^^^^^
[INFO] [stdout]     |                   |
[INFO] [stdout]     |                   the parameter type `T` must be valid for the static lifetime...
[INFO] [stdout]     |                   ...so that the type `T` will meet its required lifetime bounds...
[INFO] [stdout]     |
[INFO] [stdout] note: ...that is required by this bound
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:46:18
[INFO] [stdout]     |
[INFO] [stdout] 46  |     type Config: ModelConfig<T>;
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^
[INFO] [stdout] help: consider adding an explicit lifetime bound
[INFO] [stdout]     |
[INFO] [stdout] 118 | impl<T: Float + Send + Sync + 'static> BaseModel<T> for MockMLP<T> {
[INFO] [stdout]     |                             +++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0053]: method `new` has an incompatible type for trait
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:121:37
[INFO] [stdout]     |
[INFO] [stdout] 121 |     fn new(config: Self::Config) -> NeuroDivergentResult<Self> {
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^ expected `NeuroDivergentError`, found `neuro_divergent::NeuroDivergentError`
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected signature `fn(basic_tests::MockMLPConfig<_>) -> Result<_, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]                found signature `fn(basic_tests::MockMLPConfig<_>) -> Result<_, neuro_divergent::NeuroDivergentError>`
[INFO] [stdout] help: change the output type to match the trait
[INFO] [stdout]     |
[INFO] [stdout] 121 -     fn new(config: Self::Config) -> NeuroDivergentResult<Self> {
[INFO] [stdout] 121 +     fn new(config: Self::Config) -> Result<basic_tests::MockMLP<T>, neuro_divergent_core::NeuroDivergentError> {
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0053]: method `fit` has an incompatible type for trait
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:130:29
[INFO] [stdout]     |
[INFO] [stdout] 130 |     fn fit(&mut self, data: &TimeSeriesDataFrame<T>) -> NeuroDivergentResult<()> {
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^^^^^^^^ expected `TimeSeriesDataset<T>`, found `neuro_divergent::TimeSeriesDataFrame<T>`
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected signature `fn(&mut basic_tests::MockMLP<_>, &neuro_divergent_core::TimeSeriesDataset<T>) -> Result<_, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]                found signature `fn(&mut basic_tests::MockMLP<_>, &neuro_divergent::TimeSeriesDataFrame<T>) -> Result<_, neuro_divergent::NeuroDivergentError>`
[INFO] [stdout] help: change the parameter type to match the trait
[INFO] [stdout]     |
[INFO] [stdout] 130 -     fn fit(&mut self, data: &TimeSeriesDataFrame<T>) -> NeuroDivergentResult<()> {
[INFO] [stdout] 130 +     fn fit(&mut self, data: &neuro_divergent_core::TimeSeriesDataset<T>) -> NeuroDivergentResult<()> {
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0053]: method `predict` has an incompatible type for trait
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:148:29
[INFO] [stdout]     |
[INFO] [stdout] 148 |     fn predict(&self, data: &TimeSeriesDataFrame<T>) -> NeuroDivergentResult<ForecastDataFrame<T>> {
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^^^^^^^^ expected `TimeSeriesDataset<T>`, found `neuro_divergent::TimeSeriesDataFrame<T>`
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected signature `fn(&basic_tests::MockMLP<_>, &neuro_divergent_core::TimeSeriesDataset<T>) -> Result<ForecastResult<T>, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]                found signature `fn(&basic_tests::MockMLP<_>, &neuro_divergent::TimeSeriesDataFrame<T>) -> Result<neuro_divergent::ForecastDataFrame<T>, neuro_divergent::NeuroDivergentError>`
[INFO] [stdout] help: change the parameter type to match the trait
[INFO] [stdout]     |
[INFO] [stdout] 148 -     fn predict(&self, data: &TimeSeriesDataFrame<T>) -> NeuroDivergentResult<ForecastDataFrame<T>> {
[INFO] [stdout] 148 +     fn predict(&self, data: &neuro_divergent_core::TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastDataFrame<T>> {
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0053]: method `reset` has an incompatible type for trait
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:194:28
[INFO] [stdout]     |
[INFO] [stdout] 194 |     fn reset(&mut self) -> NeuroDivergentResult<()> {
[INFO] [stdout]     |                            ^^^^^^^^^^^^^^^^^^^^^^^^ expected `NeuroDivergentError`, found `neuro_divergent::NeuroDivergentError`
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected signature `fn(&mut basic_tests::MockMLP<_>) -> Result<_, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]                found signature `fn(&mut basic_tests::MockMLP<_>) -> Result<_, neuro_divergent::NeuroDivergentError>`
[INFO] [stdout] help: change the output type to match the trait
[INFO] [stdout]     |
[INFO] [stdout] 194 -     fn reset(&mut self) -> NeuroDivergentResult<()> {
[INFO] [stdout] 194 +     fn reset(&mut self) -> Result<(), neuro_divergent_core::NeuroDivergentError> {
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0046]: not all trait items implemented, missing: `State`, `cross_validation`, `state`, `restore_state`, `metadata`, `validate_data`, `is_trained`, `parameter_count`, `training_stats`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:118:1
[INFO] [stdout]     |
[INFO] [stdout] 118 | impl<T: Float + Send + Sync> BaseModel<T> for MockMLP<T> {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ missing `State`, `cross_validation`, `state`, `restore_state`, `metadata`, `validate_data`, `is_trained`, `parameter_count`, `training_stats` in implementation
[INFO] [stdout]     |
[INFO] [stdout]     = help: implement the missing item: `type State = /* Type */;`
[INFO] [stdout]     = help: implement the missing item: `fn cross_validation(&mut self, _: &neuro_divergent_core::TimeSeriesDataset<T>, _: neuro_divergent_core::CrossValidationConfig) -> Result<CrossValidationResult<T>, neuro_divergent_core::NeuroDivergentError> { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn state(&self) -> &<Self as neuro_divergent_core::BaseModel<T>>::State { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn restore_state(&mut self, _: <Self as neuro_divergent_core::BaseModel<T>>::State) -> Result<(), neuro_divergent_core::NeuroDivergentError> { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn metadata(&self) -> ModelMetadata { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn validate_data(&self, _: &neuro_divergent_core::TimeSeriesDataset<T>) -> Result<(), neuro_divergent_core::NeuroDivergentError> { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn is_trained(&self) -> bool { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn parameter_count(&self) -> usize { todo!() }`
[INFO] [stdout]     = help: implement the missing item: `fn training_stats(&self) -> std::option::Option<TrainingStatistics<T>> { todo!() }`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0310]: the parameter type `T` may not live long enough
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:118:30
[INFO] [stdout]     |
[INFO] [stdout] 118 | impl<T: Float + Send + Sync> BaseModel<T> for MockMLP<T> {
[INFO] [stdout]     |                              ^^^^^^^^^^^^
[INFO] [stdout]     |                              |
[INFO] [stdout]     |                              the parameter type `T` must be valid for the static lifetime...
[INFO] [stdout]     |                              ...so that the type `T` will meet its required lifetime bounds...
[INFO] [stdout]     |
[INFO] [stdout] note: ...that is required by this bound
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:44:46
[INFO] [stdout]     |
[INFO] [stdout] 44  | pub trait BaseModel<T: Float + Send + Sync + 'static>: Send + Sync {
[INFO] [stdout]     |                                              ^^^^^^^
[INFO] [stdout] help: consider adding an explicit lifetime bound
[INFO] [stdout]     |
[INFO] [stdout] 118 | impl<T: Float + Send + Sync + 'static> BaseModel<T> for MockMLP<T> {
[INFO] [stdout]     |                             +++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be shared between threads safely
[INFO] [stdout]    --> tests/unit/registry_tests.rs:260:37
[INFO] [stdout]     |
[INFO] [stdout] 260 | impl<T: Float> TestableModel<T> for MockMLPModel<T> {
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^ `T` cannot be shared between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required because it appears within the type `PhantomData<T>`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/marker.rs:823:12
[INFO] [stdout] note: required because it appears within the type `MockMLPModel<T>`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:242:8
[INFO] [stdout]     |
[INFO] [stdout] 242 | struct MockMLPModel<T: Float> {
[INFO] [stdout]     |        ^^^^^^^^^^^^
[INFO] [stdout] note: required by a bound in `unit::registry_tests::TestableModel`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:39
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     |                                       ^^^^ required by this bound in `TestableModel`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Sync`
[INFO] [stdout]     |
[INFO] [stdout] 260 | impl<T: Float + std::marker::Sync> TestableModel<T> for MockMLPModel<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be sent between threads safely
[INFO] [stdout]    --> tests/unit/registry_tests.rs:260:37
[INFO] [stdout]     |
[INFO] [stdout] 260 | impl<T: Float> TestableModel<T> for MockMLPModel<T> {
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^ `T` cannot be sent between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required because it appears within the type `PhantomData<T>`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/marker.rs:823:12
[INFO] [stdout] note: required because it appears within the type `MockMLPModel<T>`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:242:8
[INFO] [stdout]     |
[INFO] [stdout] 242 | struct MockMLPModel<T: Float> {
[INFO] [stdout]     |        ^^^^^^^^^^^^
[INFO] [stdout] note: required by a bound in `unit::registry_tests::TestableModel`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:32
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     |                                ^^^^ required by this bound in `TestableModel`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Send`
[INFO] [stdout]     |
[INFO] [stdout] 260 | impl<T: Float + std::marker::Send> TestableModel<T> for MockMLPModel<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be shared between threads safely
[INFO] [stdout]    --> tests/unit/registry_tests.rs:323:37
[INFO] [stdout]     |
[INFO] [stdout] 323 | impl<T: Float> TestableModel<T> for MockLSTMModel<T> {
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^^ `T` cannot be shared between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required because it appears within the type `PhantomData<T>`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/marker.rs:823:12
[INFO] [stdout] note: required because it appears within the type `MockLSTMModel<T>`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:305:8
[INFO] [stdout]     |
[INFO] [stdout] 305 | struct MockLSTMModel<T: Float> {
[INFO] [stdout]     |        ^^^^^^^^^^^^^
[INFO] [stdout] note: required by a bound in `unit::registry_tests::TestableModel`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:39
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     |                                       ^^^^ required by this bound in `TestableModel`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Sync`
[INFO] [stdout]     |
[INFO] [stdout] 323 | impl<T: Float + std::marker::Sync> TestableModel<T> for MockLSTMModel<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` cannot be sent between threads safely
[INFO] [stdout]    --> tests/unit/registry_tests.rs:323:37
[INFO] [stdout]     |
[INFO] [stdout] 323 | impl<T: Float> TestableModel<T> for MockLSTMModel<T> {
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^^ `T` cannot be sent between threads safely
[INFO] [stdout]     |
[INFO] [stdout] note: required because it appears within the type `PhantomData<T>`
[INFO] [stdout]    --> /rustc/82310651b93a594a3fd69015e1562186a080d94c/library/core/src/marker.rs:823:12
[INFO] [stdout] note: required because it appears within the type `MockLSTMModel<T>`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:305:8
[INFO] [stdout]     |
[INFO] [stdout] 305 | struct MockLSTMModel<T: Float> {
[INFO] [stdout]     |        ^^^^^^^^^^^^^
[INFO] [stdout] note: required by a bound in `unit::registry_tests::TestableModel`
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:32
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     |                                ^^^^ required by this bound in `TestableModel`
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Send`
[INFO] [stdout]     |
[INFO] [stdout] 323 | impl<T: Float + std::marker::Send> TestableModel<T> for MockLSTMModel<T> {
[INFO] [stdout]     |               +++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `context` found for enum `Result` in the current scope
[INFO] [stdout]    --> tests/unit/core_tests.rs:150:39
[INFO] [stdout]     |
[INFO] [stdout] 150 |         let with_context = base_error.context("additional context");
[INFO] [stdout]     |                                       ^^^^^^^ method not found in `Result<(), neuro_divergent::NeuroDivergentError>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: the following traits which provide `context` are implemented but not in scope; perhaps you want to import one of them
[INFO] [stdout]     |
[INFO] [stdout] 126 +     use anyhow::Context;
[INFO] [stdout]     |
[INFO] [stdout] 126 +     use neuro_divergent::errors::ErrorContext;
[INFO] [stdout]     |
[INFO] [stdout] 126 +     use quick_error::ResultExt;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `shape` found for struct `neuro_divergent::CrossValidationDataFrame` in the current scope
[INFO] [stdout]    --> tests/unit/core_tests.rs:367:26
[INFO] [stdout]     |
[INFO] [stdout] 367 |         assert_eq!(cv_df.shape(), (4, 7));
[INFO] [stdout]     |                          ^^^^^ method not found in `neuro_divergent::CrossValidationDataFrame<f64>`
[INFO] [stdout]     |
[INFO] [stdout] help: one of the expressions' fields has a method of the same name
[INFO] [stdout]     |
[INFO] [stdout] 367 |         assert_eq!(cv_df.data.shape(), (4, 7));
[INFO] [stdout]     |                          +++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` doesn't implement `Debug`
[INFO] [stdout]   --> tests/unit/models/basic_tests.rs:97:68
[INFO] [stdout]    |
[INFO] [stdout] 97 |         params.insert("learning_rate".to_string(), format!("{:?}", self.learning_rate));
[INFO] [stdout]    |                                                             ----   ^^^^^^^^^^^^^^^^^^ `T` cannot be formatted using `{:?}` because it doesn't implement `Debug`
[INFO] [stdout]    |                                                             |
[INFO] [stdout]    |                                                             required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = note: this error originates in the macro `$crate::__export::format_args` which comes from the expansion of the macro `format` (in Nightly builds, run with -Z macro-backtrace for more info)
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Debug`
[INFO] [stdout]    |
[INFO] [stdout] 62 | impl<T: Float + std::fmt::Debug> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]    |               +++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `T` doesn't implement `Debug`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:100:66
[INFO] [stdout]     |
[INFO] [stdout] 100 |             params.insert("dropout".to_string(), format!("{:?}", dropout));
[INFO] [stdout]     |                                                           ----   ^^^^^^^ `T` cannot be formatted using `{:?}` because it doesn't implement `Debug`
[INFO] [stdout]     |                                                           |
[INFO] [stdout]     |                                                           required by this formatting parameter
[INFO] [stdout]     |
[INFO] [stdout]     = note: this error originates in the macro `$crate::__export::format_args` which comes from the expansion of the macro `format` (in Nightly builds, run with -Z macro-backtrace for more info)
[INFO] [stdout] help: consider further restricting type parameter `T` with trait `Debug`
[INFO] [stdout]     |
[INFO] [stdout] 62  | impl<T: Float + std::fmt::Debug> ModelConfig<T> for MockMLPConfig<T> {
[INFO] [stdout]     |               +++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `?` couldn't convert the error to `neuro_divergent::NeuroDivergentError`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:122:26
[INFO] [stdout]     |
[INFO] [stdout] 122 |         config.validate()?;
[INFO] [stdout]     |                ----------^ the trait `From<neuro_divergent_core::NeuroDivergentError>` is not implemented for `neuro_divergent::NeuroDivergentError`
[INFO] [stdout]     |                |
[INFO] [stdout]     |                this can't be annotated with `?` because it has type `Result<_, neuro_divergent_core::NeuroDivergentError>`
[INFO] [stdout]     |
[INFO] [stdout]     = note: the question mark operation (`?`) implicitly performs a conversion on the error value using the `From` trait
[INFO] [stdout]     = help: the following other types implement trait `From<T>`:
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<ParseError>`
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<ShapeError>`
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<neuro_divergent_core::PolarsError>`
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<ruv_fann::errors::RuvFannError>`
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<serde_json::error::Error>`
[INFO] [stdout]               `neuro_divergent::NeuroDivergentError` implements `From<std::io::Error>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: the trait bound `neuro_divergent_core::Series: neuro_divergent_core::NamedFrom<Vec<usize>, _>` is not satisfied
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:171:18
[INFO] [stdout]     |
[INFO] [stdout] 171 |           let df = df! {
[INFO] [stdout]     |  __________________^
[INFO] [stdout] 172 | |             "unique_id" => forecast_data.iter().map(|(id, _, _)| id.clone()).collect::<Vec<_>>(),
[INFO] [stdout] 173 | |             "ds" => forecast_data.iter().map(|(_, step, _)| *step).collect::<Vec<_>>(),
[INFO] [stdout] 174 | |             "MockMLP" => forecast_data.iter().map(|(_, _, val)| T::to_f64(val).unwrap()).collect::<Vec<_>>(),
[INFO] [stdout] 175 | |         }.map_err(|e| NeuroDivergentError::prediction(format!("Failed to create forecast DataFrame: {}", e)))?;
[INFO] [stdout]     | |_________^ the trait `neuro_divergent_core::NamedFrom<Vec<usize>, _>` is not implemented for `neuro_divergent_core::Series`
[INFO] [stdout]     |
[INFO] [stdout]     = help: the following other types implement trait `neuro_divergent_core::NamedFrom<T, Phantom>`:
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<&neuro_divergent_core::Series, str>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, ListType>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, T>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, [&[u8]]>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, [&str]>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, [AnyValue<'_>]>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, [Cow<'_, [u8]>]>`
[INFO] [stdout]               `neuro_divergent_core::Series` implements `neuro_divergent_core::NamedFrom<T, [Cow<'_, str>]>`
[INFO] [stdout]             and 35 others
[INFO] [stdout]     = note: this error originates in the macro `df` (in Nightly builds, run with -Z macro-backtrace for more info)
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0283]: type annotations needed for `basic_tests::MockMLPConfig<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:225:13
[INFO] [stdout]     |
[INFO] [stdout] 225 |         let config = MockMLPConfig::new(10, 5);
[INFO] [stdout]     |             ^^^^^^   ------------- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout]     = note: cannot satisfy `_: num_traits::Float`
[INFO] [stdout]     = help: the following types implement trait `num_traits::Float`:
[INFO] [stdout]               f32
[INFO] [stdout]               f64
[INFO] [stdout] note: required by a bound in `basic_tests::MockMLPConfig`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:23:25
[INFO] [stdout]     |
[INFO] [stdout] 23  | struct MockMLPConfig<T: Float> {
[INFO] [stdout]     |                         ^^^^^ required by this bound in `MockMLPConfig`
[INFO] [stdout] help: consider giving `config` an explicit type, where the type for type parameter `T` is specified
[INFO] [stdout]     |
[INFO] [stdout] 225 |         let config: basic_tests::MockMLPConfig<T> = MockMLPConfig::new(10, 5);
[INFO] [stdout]     |                   +++++++++++++++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0283]: type annotations needed for `basic_tests::MockMLPConfig<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:232:13
[INFO] [stdout]     |
[INFO] [stdout] 232 |         let config = MockMLPConfig::new(10, 0);
[INFO] [stdout]     |             ^^^^^^   ------------- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout]     = note: cannot satisfy `_: num_traits::Float`
[INFO] [stdout]     = help: the following types implement trait `num_traits::Float`:
[INFO] [stdout]               f32
[INFO] [stdout]               f64
[INFO] [stdout] note: required by a bound in `basic_tests::MockMLPConfig`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:23:25
[INFO] [stdout]     |
[INFO] [stdout] 23  | struct MockMLPConfig<T: Float> {
[INFO] [stdout]     |                         ^^^^^ required by this bound in `MockMLPConfig`
[INFO] [stdout] help: consider giving `config` an explicit type, where the type for type parameter `T` is specified
[INFO] [stdout]     |
[INFO] [stdout] 232 |         let config: basic_tests::MockMLPConfig<T> = MockMLPConfig::new(10, 0);
[INFO] [stdout]     |                   +++++++++++++++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `parameters` found for struct `basic_tests::MockMLPConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:258:29
[INFO] [stdout]     |
[INFO] [stdout] 23  | struct MockMLPConfig<T: Float> {
[INFO] [stdout]     | ------------------------------ method `parameters` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 258 |         let params = config.parameters();
[INFO] [stdout]     |                             ^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following trait defines an item `parameters`, perhaps you need to implement it:
[INFO] [stdout]             candidate #1: `neuro_divergent::neuro_divergent_registry::BaseModel`
[INFO] [stdout] help: there is a method `to_parameters` with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 258 |         let params = config.to_parameters();
[INFO] [stdout]     |                             +++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:298:24
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 298 |         assert!(!model.is_fitted());
[INFO] [stdout]     |                        ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0283]: type annotations needed for `basic_tests::MockMLPConfig<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:305:13
[INFO] [stdout]     |
[INFO] [stdout] 305 |         let config = MockMLPConfig::new(0, 12); // Invalid input size
[INFO] [stdout]     |             ^^^^^^   ------------- type must be known at this point
[INFO] [stdout]     |
[INFO] [stdout]     = note: cannot satisfy `_: num_traits::Float`
[INFO] [stdout]     = help: the following types implement trait `num_traits::Float`:
[INFO] [stdout]               f32
[INFO] [stdout]               f64
[INFO] [stdout] note: required by a bound in `basic_tests::MockMLPConfig`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:23:25
[INFO] [stdout]     |
[INFO] [stdout] 23  | struct MockMLPConfig<T: Float> {
[INFO] [stdout]     |                         ^^^^^ required by this bound in `MockMLPConfig`
[INFO] [stdout] help: consider giving `config` an explicit type, where the type for type parameter `T` is specified
[INFO] [stdout]     |
[INFO] [stdout] 305 |         let config: basic_tests::MockMLPConfig<T> = MockMLPConfig::new(0, 12); // Invalid input size
[INFO] [stdout]     |                   +++++++++++++++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:316:24
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 316 |         assert!(!model.is_fitted());
[INFO] [stdout]     |                        ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:318:32
[INFO] [stdout]     |
[INFO] [stdout] 318 |         let result = model.fit(&data);
[INFO] [stdout]     |                            --- ^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<f64>`
[INFO] [stdout]     |                            |
[INFO] [stdout]     |                            arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<f64>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:320:23
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 320 |         assert!(model.is_fitted());
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:337:32
[INFO] [stdout]     |
[INFO] [stdout] 337 |         let result = model.fit(&ts_data);
[INFO] [stdout]     |                            --- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                            |
[INFO] [stdout]     |                            arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:347:36
[INFO] [stdout]     |
[INFO] [stdout] 347 |         let result = model.predict(&data);
[INFO] [stdout]     |                            ------- ^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<f64>`
[INFO] [stdout]     |                            |
[INFO] [stdout]     |                            arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<f64>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_prediction_error` found for enum `neuro_divergent_core::NeuroDivergentError` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:351:23
[INFO] [stdout]     |
[INFO] [stdout] 351 |         assert!(error.is_prediction_error());
[INFO] [stdout]     |                       ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout] help: there is a variant with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 351 -         assert!(error.is_prediction_error());
[INFO] [stdout] 351 +         assert!(error.PredictionError());
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `as_dyn_error` with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 351 -         assert!(error.is_prediction_error());
[INFO] [stdout] 351 +         assert!(error.as_dyn_error());
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:360:19
[INFO] [stdout]     |
[INFO] [stdout] 360 |         model.fit(&data).unwrap();
[INFO] [stdout]     |               --- ^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<f64>`
[INFO] [stdout]     |               |
[INFO] [stdout]     |               arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<f64>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:361:38
[INFO] [stdout]     |
[INFO] [stdout] 361 |         let forecast = model.predict(&data);
[INFO] [stdout]     |                              ------- ^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<f64>`
[INFO] [stdout]     |                              |
[INFO] [stdout]     |                              arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<f64>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `forecast_horizon` on type `ForecastResult<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:365:29
[INFO] [stdout]     |
[INFO] [stdout] 365 |         assert_eq!(forecast.forecast_horizon, config.horizon);
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `models` on type `ForecastResult<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:366:29
[INFO] [stdout]     |
[INFO] [stdout] 366 |         assert_eq!(forecast.models, vec!["MockMLP".to_string()]);
[INFO] [stdout]     |                             ^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `shape` found for struct `ForecastResult` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:369:39
[INFO] [stdout]     |
[INFO] [stdout] 369 |         let forecast_shape = forecast.shape();
[INFO] [stdout]     |                                       ^^^^^ method not found in `ForecastResult<_>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:380:19
[INFO] [stdout]     |
[INFO] [stdout] 380 |         model.fit(&data).unwrap();
[INFO] [stdout]     |               --- ^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<f64>`
[INFO] [stdout]     |               |
[INFO] [stdout]     |               arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<f64>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:381:23
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 381 |         assert!(model.is_fitted());
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:386:24
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 386 |         assert!(!model.is_fitted());
[INFO] [stdout]     |                        ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `validate_input` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:397:28
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `validate_input` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 397 |         let result = model.validate_input(&data);
[INFO] [stdout]     |                            ^^^^^^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `summary` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:406:29
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `summary` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 406 |         let summary = model.summary();
[INFO] [stdout]     |                             ^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:453:28
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 453 |             assert!(!model.is_fitted());
[INFO] [stdout]     |                            ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:464:40
[INFO] [stdout]     |
[INFO] [stdout] 464 |             let fit_result = model.fit(&ts_data);
[INFO] [stdout]     |                                    --- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                    |
[INFO] [stdout]     |                                    arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:466:27
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 466 |             assert!(model.is_fitted());
[INFO] [stdout]     |                           ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:469:48
[INFO] [stdout]     |
[INFO] [stdout] 469 |             let predict_result = model.predict(&ts_data);
[INFO] [stdout]     |                                        ------- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                        |
[INFO] [stdout]     |                                        arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `forecast_horizon` on type `ForecastResult<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:473:33
[INFO] [stdout]     |
[INFO] [stdout] 473 |             assert_eq!(forecast.forecast_horizon, horizon);
[INFO] [stdout]     |                                 ^^^^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:478:28
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 478 |             assert!(!model.is_fitted());
[INFO] [stdout]     |                            ^^^^^^^^^ method not found in `basic_tests::MockMLP<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:512:36
[INFO] [stdout]     |
[INFO] [stdout] 512 |         let fit_result = model.fit(&ts_train);
[INFO] [stdout]     |                                --- ^^^^^^^^^ expected `&TimeSeriesDataset<{float}>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                |
[INFO] [stdout]     |                                arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<{float}>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `basic_tests::MockMLP` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:514:23
[INFO] [stdout]     |
[INFO] [stdout] 112 | struct MockMLP<T: Float> {
[INFO] [stdout]     | ------------------------ method `is_fitted` not found for this struct
[INFO] [stdout] ...
[INFO] [stdout] 514 |         assert!(model.is_fitted());
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `basic_tests::MockMLP<{float}>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout]     = note: the following traits define an item `is_fitted`, perhaps you need to implement one of them:
[INFO] [stdout]             candidate #1: `unit::registry_tests::TestableModel`
[INFO] [stdout]             candidate #2: `neuro_divergent::neural_forecast::BaseModel`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:526:45
[INFO] [stdout]     |
[INFO] [stdout] 526 |         let forecast_result = model.predict(&ts_pred);
[INFO] [stdout]     |                                     ------- ^^^^^^^^ expected `&TimeSeriesDataset<{float}>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                     |
[INFO] [stdout]     |                                     arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<{float}>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `forecast_horizon` on type `ForecastResult<{float}>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:530:29
[INFO] [stdout]     |
[INFO] [stdout] 530 |         assert_eq!(forecast.forecast_horizon, 5);
[INFO] [stdout]     |                             ^^^^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `models` on type `ForecastResult<{float}>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:531:29
[INFO] [stdout]     |
[INFO] [stdout] 531 |         assert_eq!(forecast.models, vec!["MockMLP".to_string()]);
[INFO] [stdout]     |                             ^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `get_model_forecasts` found for struct `ForecastResult` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:534:40
[INFO] [stdout]     |
[INFO] [stdout] 534 |         let model_forecasts = forecast.get_model_forecasts("MockMLP").unwrap();
[INFO] [stdout]     |                                        ^^^^^^^^^^^^^^^^^^^ method not found in `ForecastResult<{float}>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:564:20
[INFO] [stdout]     |
[INFO] [stdout] 564 |         model1.fit(&ts_data).unwrap();
[INFO] [stdout]     |                --- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                |
[INFO] [stdout]     |                arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:565:20
[INFO] [stdout]     |
[INFO] [stdout] 565 |         model2.fit(&ts_data).unwrap();
[INFO] [stdout]     |                --- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                |
[INFO] [stdout]     |                arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:73:8
[INFO] [stdout]     |
[INFO] [stdout] 73  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<()>;
[INFO] [stdout]     |        ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:568:40
[INFO] [stdout]     |
[INFO] [stdout] 568 |         let forecast1 = model1.predict(&ts_data).unwrap();
[INFO] [stdout]     |                                ------- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                |
[INFO] [stdout]     |                                arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:569:40
[INFO] [stdout]     |
[INFO] [stdout] 569 |         let forecast2 = model2.predict(&ts_data).unwrap();
[INFO] [stdout]     |                                ------- ^^^^^^^^ expected `&TimeSeriesDataset<_>`, found `&TimeSeriesDataFrame<_>`
[INFO] [stdout]     |                                |
[INFO] [stdout]     |                                arguments to this method are incorrect
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected reference `&neuro_divergent_core::TimeSeriesDataset<_>`
[INFO] [stdout]                found reference `&neuro_divergent::TimeSeriesDataFrame<_>`
[INFO] [stdout] note: method defined here
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-core-0.1.0/src/traits.rs:84:8
[INFO] [stdout]     |
[INFO] [stdout] 84  |     fn predict(&self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<ForecastResult<T>>;
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `forecast_horizon` on type `ForecastResult<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:572:30
[INFO] [stdout]     |
[INFO] [stdout] 572 |         assert_eq!(forecast1.forecast_horizon, forecast2.forecast_horizon);
[INFO] [stdout]     |                              ^^^^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0609]: no field `forecast_horizon` on type `ForecastResult<_>`
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:572:58
[INFO] [stdout]     |
[INFO] [stdout] 572 |         assert_eq!(forecast1.forecast_horizon, forecast2.forecast_horizon);
[INFO] [stdout]     |                                                          ^^^^^^^^^^^^^^^^ unknown field
[INFO] [stdout]     |
[INFO] [stdout]     = note: available fields are: `forecasts`, `timestamps`, `series_id`, `model_name`, `generated_at`, `metadata`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `shape` found for struct `ForecastResult` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:575:30
[INFO] [stdout]     |
[INFO] [stdout] 575 |         assert_eq!(forecast1.shape().0, forecast2.shape().0);
[INFO] [stdout]     |                              ^^^^^ method not found in `ForecastResult<_>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `shape` found for struct `ForecastResult` in the current scope
[INFO] [stdout]    --> tests/unit/models/basic_tests.rs:575:51
[INFO] [stdout]     |
[INFO] [stdout] 575 |         assert_eq!(forecast1.shape().0, forecast2.shape().0);
[INFO] [stdout]     |                                                   ^^^^^ method not found in `ForecastResult<_>`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:212:33
[INFO] [stdout]     |
[INFO] [stdout] 212 |         let config = RNNConfig::new(24, 12)
[INFO] [stdout]     |                                 ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:235:39
[INFO] [stdout]     |
[INFO] [stdout] 235 |         let valid_config = RNNConfig::new(24, 12);
[INFO] [stdout]     |                                       ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:239:41
[INFO] [stdout]     |
[INFO] [stdout] 239 |         let invalid_hidden = RNNConfig::new(24, 12).with_hidden_size(0);
[INFO] [stdout]     |                                         ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:243:41
[INFO] [stdout]     |
[INFO] [stdout] 243 |         let invalid_layers = RNNConfig::new(24, 12).with_num_layers(0);
[INFO] [stdout]     |                                         ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:247:42
[INFO] [stdout]     |
[INFO] [stdout] 247 |         let invalid_dropout = RNNConfig::new(24, 12).with_dropout(1.5);
[INFO] [stdout]     |                                          ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:256:37
[INFO] [stdout]     |
[INFO] [stdout] 256 |             let config = RNNConfig::new(10, 5)
[INFO] [stdout]     |                                     ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:275:33
[INFO] [stdout]     |
[INFO] [stdout] 275 |         let config = RNNConfig::new(20, 10)
[INFO] [stdout]     |                                 ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:284:24
[INFO] [stdout]     |
[INFO] [stdout] 284 |         assert!(!model.is_fitted());
[INFO] [stdout]     |                        ^^^^^^^^^ method not found in `neuro_divergent_models::models::RNN<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout] note: `unit::registry_tests::TestableModel` defines an item `is_fitted`, perhaps you need to implement it
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:1
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `fit` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:285:23
[INFO] [stdout]     |
[INFO] [stdout] 285 |         assert!(model.fit(&ts_data).is_ok());
[INFO] [stdout]     |                       ^^^ method not found in `neuro_divergent_models::models::RNN<_>`
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:25:8
[INFO] [stdout]     |
[INFO] [stdout] 25  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<TrainingMetrics<T>>;
[INFO] [stdout]     |        --- the method is available for `neuro_divergent_models::models::RNN<_>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `fit` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `is_fitted` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:286:23
[INFO] [stdout]     |
[INFO] [stdout] 286 |         assert!(model.is_fitted());
[INFO] [stdout]     |                       ^^^^^^^^^ method not found in `neuro_divergent_models::models::RNN<_>`
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is implemented and in scope
[INFO] [stdout] note: `unit::registry_tests::TestableModel` defines an item `is_fitted`, perhaps you need to implement it
[INFO] [stdout]    --> tests/unit/registry_tests.rs:149:1
[INFO] [stdout]     |
[INFO] [stdout] 149 | trait TestableModel<T: Float>: Send + Sync {
[INFO] [stdout]     | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `predict` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:289:30
[INFO] [stdout]     |
[INFO] [stdout] 289 |         let forecast = model.predict(&ts_data).unwrap();
[INFO] [stdout]     |                              ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:28:8
[INFO] [stdout]     |
[INFO] [stdout] 28  |     fn predict(&self, input: &TimeSeriesInput<T>) -> NeuroDivergentResult<ForecastOutput<T>>;
[INFO] [stdout]     |        ------- the method is available for `neuro_divergent_models::models::RNN<_>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `predict` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] help: there is a method `predict_batch` with a similar name
[INFO] [stdout]     |
[INFO] [stdout] 289 |         let forecast = model.predict_batch(&ts_data).unwrap();
[INFO] [stdout]     |                                     ++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:298:37
[INFO] [stdout]     |
[INFO] [stdout] 298 |         let uni_config = RNNConfig::new(20, 10)
[INFO] [stdout]     |                                     ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `fit` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:304:27
[INFO] [stdout]     |
[INFO] [stdout] 304 |         assert!(uni_model.fit(&data).is_ok());
[INFO] [stdout]     |                           ^^^ method not found in `neuro_divergent_models::models::RNN<f64>`
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:25:8
[INFO] [stdout]     |
[INFO] [stdout] 25  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<TrainingMetrics<T>>;
[INFO] [stdout]     |        --- the method is available for `neuro_divergent_models::models::RNN<f64>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `fit` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:307:36
[INFO] [stdout]     |
[INFO] [stdout] 307 |         let bi_config = RNNConfig::new(20, 10)
[INFO] [stdout]     |                                    ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `fit` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:313:26
[INFO] [stdout]     |
[INFO] [stdout] 313 |         assert!(bi_model.fit(&data).is_ok());
[INFO] [stdout]     |                          ^^^ method not found in `neuro_divergent_models::models::RNN<f64>`
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:25:8
[INFO] [stdout]     |
[INFO] [stdout] 25  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<TrainingMetrics<T>>;
[INFO] [stdout]     |        --- the method is available for `neuro_divergent_models::models::RNN<f64>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `fit` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `neuro_divergent_models::RNNConfig` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:352:33
[INFO] [stdout]     |
[INFO] [stdout] 352 |         let config = RNNConfig::new(5, 3)
[INFO] [stdout]     |                                 ^^^ function or associated item not found in `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]     |
[INFO] [stdout] note: if you're trying to build a new `neuro_divergent_models::RNNConfig<_>`, consider using `neuro_divergent_models::RNNConfig::<T>::default_with_horizon` which returns `neuro_divergent_models::RNNConfig<_>`
[INFO] [stdout]    --> /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/config.rs:38:5
[INFO] [stdout]     |
[INFO] [stdout] 38  |     pub fn default_with_horizon(horizon: usize) -> Self {
[INFO] [stdout]     |     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `fit` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:358:23
[INFO] [stdout]     |
[INFO] [stdout] 358 |         assert!(model.fit(&ts_data).is_ok());
[INFO] [stdout]     |                       ^^^ method not found in `neuro_divergent_models::models::RNN<_>`
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:25:8
[INFO] [stdout]     |
[INFO] [stdout] 25  |     fn fit(&mut self, data: &TimeSeriesDataset<T>) -> NeuroDivergentResult<TrainingMetrics<T>>;
[INFO] [stdout]     |        --- the method is available for `neuro_divergent_models::models::RNN<_>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `fit` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `predict` found for struct `neuro_divergent_models::models::RNN` in the current scope
[INFO] [stdout]    --> tests/unit/models/recurrent_tests.rs:360:30
[INFO] [stdout]     |
[INFO] [stdout] 360 |         let forecast = model.predict(&ts_data).unwrap();
[INFO] [stdout]     |                              ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]    ::: /opt/rustwide/cargo-home/registry/src/index.crates.io-1949cf8c6b5b557f/neuro-divergent-models-0.1.0/src/foundation.rs:28:8
[INFO] [stdout]     |
[INFO] [stdout] 28  |     fn predict(&self, input: &TimeSeriesInput<T>) -> NeuroDivergentResult<ForecastOutput<T>>;
[INFO] [stdout]     |        ------- the method is available for `neuro_divergent_models::models::RNN<_>` here
[INFO] [stdout]     |
[INFO] [stdout]     = help: items from traits can only be used if the trait is in scope
[INFO] [stdout] help: trait `BaseModel` which provides `predict` is implemented but not in scope; perhaps you want to import it
[INFO] [stdout]     |
[INFO] [stdout] 208 +     use neuro_divergent_models::BaseModel;
[INFO] [stdout]     |
[WARN] too many lines in the log, truncating it
