[INFO] fetching crate sklears-kernel-approximation 0.1.0-alpha.1... [INFO] testing sklears-kernel-approximation-0.1.0-alpha.1 against master#c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38 for pr-146098-8 [INFO] extracting crate sklears-kernel-approximation 0.1.0-alpha.1 into /workspace/builds/worker-5-tc1/source [INFO] started tweaking crates.io crate sklears-kernel-approximation 0.1.0-alpha.1 [INFO] finished tweaking crates.io crate sklears-kernel-approximation 0.1.0-alpha.1 [INFO] tweaked toml for crates.io crate sklears-kernel-approximation 0.1.0-alpha.1 written to /workspace/builds/worker-5-tc1/source/Cargo.toml [INFO] validating manifest of crates.io crate sklears-kernel-approximation 0.1.0-alpha.1 on toolchain c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38 [INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }` [INFO] crate crates.io crate sklears-kernel-approximation 0.1.0-alpha.1 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" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }` [INFO] [stderr] Updating crates.io index [INFO] [stderr] Downloading crates ... [INFO] [stderr] Downloaded simba v0.9.1 [INFO] [stderr] Downloaded lax v0.17.0 [INFO] [stderr] Downloaded mach v0.3.2 [INFO] [stderr] Downloaded ndarray-rand v0.15.0 [INFO] [stderr] Downloaded cauchy v0.4.0 [INFO] [stderr] Downloaded lambert_w v1.2.28 [INFO] [stderr] Downloaded ppmd-rust v1.2.1 [INFO] [stderr] Downloaded ndarray-linalg v0.17.0 [INFO] [stderr] Downloaded libbz2-rs-sys v0.2.2 [INFO] [stderr] Downloaded special v0.11.4 [INFO] [stderr] Downloaded statrs v0.18.0 [INFO] [stderr] Downloaded bzip2 v0.6.0 [INFO] [stderr] Downloaded katexit v0.1.5 [INFO] [stderr] Downloaded zip v5.1.1 [INFO] [stderr] Downloaded sklears-utils v0.1.0-alpha.1 [INFO] [stderr] Downloaded proptest v1.8.0 [INFO] [stderr] Downloaded lzma-rust2 v0.13.0 [INFO] [stderr] Downloaded nalgebra v0.33.2 [INFO] [stderr] Downloaded sklears-core v0.1.0-alpha.1 [INFO] [stderr] Downloaded numrs2 v0.1.0-beta.3 [INFO] [stderr] Downloaded scirs2-linalg v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-core v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-stats v0.1.0-rc.1 [INFO] [stderr] Downloaded lapack-sys v0.14.0 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-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@sha256:4848fb76d95f26979359cc7e45710b1dbc8f3acb7aeedee7c460d7702230f228" "/opt/rustwide/cargo-home/bin/cargo" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }` [INFO] [stdout] f93ffed11cdc1d7e3e8be4fa56102390c7af04129b695d74bbb7e62dfa9adde4 [INFO] running `Command { std: "docker" "start" "-a" "f93ffed11cdc1d7e3e8be4fa56102390c7af04129b695d74bbb7e62dfa9adde4", kill_on_drop: false }` [INFO] running `Command { std: "docker" "inspect" "f93ffed11cdc1d7e3e8be4fa56102390c7af04129b695d74bbb7e62dfa9adde4", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "f93ffed11cdc1d7e3e8be4fa56102390c7af04129b695d74bbb7e62dfa9adde4", kill_on_drop: false }` [INFO] [stdout] f93ffed11cdc1d7e3e8be4fa56102390c7af04129b695d74bbb7e62dfa9adde4 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-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@sha256:4848fb76d95f26979359cc7e45710b1dbc8f3acb7aeedee7c460d7702230f228" "/opt/rustwide/cargo-home/bin/cargo" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "build" "--frozen" "--message-format=json", kill_on_drop: false }` [INFO] [stdout] 6ee3cc0892a72da0c049fdedb25ecb8891129c38abb95b0ab049fad260cd56e2 [INFO] running `Command { std: "docker" "start" "-a" "6ee3cc0892a72da0c049fdedb25ecb8891129c38abb95b0ab049fad260cd56e2", kill_on_drop: false }` [INFO] [stderr] Compiling unicode-ident v1.0.19 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v1.18.1 [INFO] [stderr] Compiling bincode v2.0.1 [INFO] [stderr] Compiling half v2.6.0 [INFO] [stderr] Compiling serde-pickle v1.2.0 [INFO] [stderr] Compiling csv v1.3.1 [INFO] [stderr] Compiling ndarray v0.16.1 [INFO] [stderr] Compiling simba v0.9.1 [INFO] [stderr] Compiling cauchy v0.4.0 [INFO] [stderr] Compiling rustfft v6.4.1 [INFO] [stderr] Compiling special v0.11.4 [INFO] [stderr] Compiling lax v0.17.0 [INFO] [stderr] Compiling ndarray-rand v0.15.0 [INFO] [stderr] Compiling ndarray-linalg v0.17.0 [INFO] [stderr] Compiling nalgebra v0.33.2 [INFO] [stderr] Compiling statrs v0.18.0 [INFO] [stderr] Compiling scirs2-linalg v0.1.0-rc.1 [INFO] [stderr] Compiling scirs2-stats v0.1.0-rc.1 [INFO] [stderr] Compiling numrs2 v0.1.0-beta.3 [INFO] [stderr] Compiling sklears-core v0.1.0-alpha.1 [INFO] [stderr] Compiling sklears-utils v0.1.0-alpha.1 [INFO] [stderr] Compiling sklears-kernel-approximation v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/plugin_architecture.rs:329:9 [INFO] [stdout] | [INFO] [stdout] 329 | /// PluginMetadata [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 330 | / PluginMetadata { [INFO] [stdout] 331 | | name: "linear_kernel".to_string(), [INFO] [stdout] 332 | | version: "1.0.0".to_string(), [INFO] [stdout] 333 | | description: "Simple linear kernel approximation plugin".to_string(), [INFO] [stdout] ... | [INFO] [stdout] 337 | | optional_parameters: vec!["normalize".to_string()], [INFO] [stdout] 338 | | } [INFO] [stdout] | |_________- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/advanced_testing.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/anisotropic_rbf.rs:29:5 [INFO] [stdout] | [INFO] [stdout] 29 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/benchmarking.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/validation.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/chi2_samplers.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/computer_vision_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safety.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/fastfood.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safe_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/gpu_acceleration.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/gradient_kernel_learning.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/information_theoretic.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/time_series_kernels.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/time_series_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/memory_efficient.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/multi_scale_rbf.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/nlp_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/optimal_transport.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/out_of_core.rs:11:39 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/out_of_core.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Distribution` [INFO] [stdout] --> src/plugin_architecture.rs:415:35 [INFO] [stdout] | [INFO] [stdout] 415 | use scirs2_core::random::{Distribution, StandardNormal}; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/polynomial_count_sketch.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Fft` [INFO] [stdout] --> src/polynomial_count_sketch.rs:3:15 [INFO] [stdout] | [INFO] [stdout] 3 | use rustfft::{Fft, FftPlanner}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/mod.rs:26:39 [INFO] [stdout] | [INFO] [stdout] 26 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/rbf_sampler.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/robust_kernels.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/robust_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `sklears_core::traits::Fit` [INFO] [stdout] --> src/robust_kernels.rs:15:5 [INFO] [stdout] | [INFO] [stdout] 15 | use sklears_core::traits::Fit; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/approximations.rs:10:39 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/mod.rs:25:5 [INFO] [stdout] | [INFO] [stdout] 25 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/inference.rs:13:5 [INFO] [stdout] | [INFO] [stdout] 13 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/inference.rs:14:39 [INFO] [stdout] | [INFO] [stdout] 14 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gamma` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:490:47 [INFO] [stdout] | [INFO] [stdout] 490 | fn kernel_trace(&self, x: &Array2, gamma: Float) -> Result { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_gamma` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:630:14 [INFO] [stdout] | [INFO] [stdout] 630 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/adaptive_dimension.rs:235:9 [INFO] [stdout] | [INFO] [stdout] 235 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:237:9 [INFO] [stdout] | [INFO] [stdout] 237 | x_val_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fitted_sampler` [INFO] [stdout] --> src/adaptive_dimension.rs:238:9 [INFO] [stdout] | [INFO] [stdout] 238 | fitted_sampler: &crate::rbf_sampler::RBFSampler, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fitted_sampler` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/adaptive_dimension.rs:400:9 [INFO] [stdout] | [INFO] [stdout] 400 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:402:9 [INFO] [stdout] | [INFO] [stdout] 402 | x_train_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/anisotropic_rbf.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | for iter in 0..self.max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_inv_sqrt` [INFO] [stdout] --> src/anisotropic_rbf.rs:195:13 [INFO] [stdout] | [INFO] [stdout] 195 | let k_inv_sqrt = u.dot(&s_inv_diag).dot(&vt); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_inv_sqrt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `vt` [INFO] [stdout] --> src/anisotropic_rbf.rs:662:20 [INFO] [stdout] | [INFO] [stdout] 662 | let (u, s, vt) = precision.svd(true, true).map_err(|e| { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_vt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method_name` [INFO] [stdout] --> src/benchmarking.rs:391:13 [INFO] [stdout] | [INFO] [stdout] 391 | let method_name = method.method_name(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_method_name` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fit_start` [INFO] [stdout] --> src/benchmarking.rs:440:13 [INFO] [stdout] | [INFO] [stdout] 440 | let fit_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fit_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:193:13 [INFO] [stdout] | [INFO] [stdout] 193 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:214:17 [INFO] [stdout] | [INFO] [stdout] 214 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/budget_constrained.rs:240:21 [INFO] [stdout] | [INFO] [stdout] 240 | let x_train_transformed = fitted.transform(&x_train)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_quality` [INFO] [stdout] --> src/budget_constrained.rs:375:9 [INFO] [stdout] | [INFO] [stdout] 375 | current_quality: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_quality` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:493:13 [INFO] [stdout] | [INFO] [stdout] 493 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:504:17 [INFO] [stdout] | [INFO] [stdout] 504 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:120:18 [INFO] [stdout] | [INFO] [stdout] 120 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:420:18 [INFO] [stdout] | [INFO] [stdout] 420 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:648:21 [INFO] [stdout] | [INFO] [stdout] 648 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:649:21 [INFO] [stdout] | [INFO] [stdout] 649 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:749:21 [INFO] [stdout] | [INFO] [stdout] 749 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:750:21 [INFO] [stdout] | [INFO] [stdout] 750 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:945:18 [INFO] [stdout] | [INFO] [stdout] 945 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:685:27 [INFO] [stdout] | [INFO] [stdout] 685 | fn compute_mse(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:693:27 [INFO] [stdout] | [INFO] [stdout] 693 | fn compute_mae(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:700:32 [INFO] [stdout] | [INFO] [stdout] 700 | fn compute_r2_score(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/custom_kernel.rs:387:14 [INFO] [stdout] | [INFO] [stdout] 387 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/distributed_kernel.rs:448:14 [INFO] [stdout] | [INFO] [stdout] 448 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:160:9 [INFO] [stdout] | [INFO] [stdout] 160 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:409:9 [INFO] [stdout] | [INFO] [stdout] 409 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/error_bounded.rs:125:13 [INFO] [stdout] | [INFO] [stdout] 125 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/error_bounded.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | let x_test = x [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/error_bounded.rs:217:9 [INFO] [stdout] | [INFO] [stdout] 217 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:364:9 [INFO] [stdout] | [INFO] [stdout] 364 | n_components: usize, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/error_bounded.rs:517:13 [INFO] [stdout] | [INFO] [stdout] 517 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:585:57 [INFO] [stdout] | [INFO] [stdout] 585 | fn compute_error_bound(&self, trial_errors: &[f64], n_components: usize) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `block_end` [INFO] [stdout] --> src/fastfood.rs:274:17 [INFO] [stdout] | [INFO] [stdout] 274 | let block_end = block_start + padded_dim; [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_block_end` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ctx` [INFO] [stdout] --> src/gpu_acceleration.rs:1002:9 [INFO] [stdout] | [INFO] [stdout] 1002 | ctx: &GpuContext, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_ctx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gradient_kernel_learning.rs:215:13 [INFO] [stdout] | [INFO] [stdout] 215 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `param_idx` [INFO] [stdout] --> src/gradient_kernel_learning.rs:620:13 [INFO] [stdout] | [INFO] [stdout] 620 | for param_idx in 1..self.parameters.len() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:698:9 [INFO] [stdout] | [INFO] [stdout] 698 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:699:9 [INFO] [stdout] | [INFO] [stdout] 699 | y_train: &Array1, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:700:9 [INFO] [stdout] | [INFO] [stdout] 700 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:701:9 [INFO] [stdout] | [INFO] [stdout] 701 | y_val: &Array1, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_y_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:717:9 [INFO] [stdout] | [INFO] [stdout] 717 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:718:9 [INFO] [stdout] | [INFO] [stdout] 718 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:727:9 [INFO] [stdout] | [INFO] [stdout] 727 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:728:9 [INFO] [stdout] | [INFO] [stdout] 728 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:729:9 [INFO] [stdout] | [INFO] [stdout] 729 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:738:9 [INFO] [stdout] | [INFO] [stdout] 738 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:739:9 [INFO] [stdout] | [INFO] [stdout] 739 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:748:9 [INFO] [stdout] | [INFO] [stdout] 748 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:749:9 [INFO] [stdout] | [INFO] [stdout] 749 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:750:9 [INFO] [stdout] | [INFO] [stdout] 750 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:27 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:49 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:765:9 [INFO] [stdout] | [INFO] [stdout] 765 | x1: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:766:9 [INFO] [stdout] | [INFO] [stdout] 766 | x2: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:803:9 [INFO] [stdout] | [INFO] [stdout] 803 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `target_kernel` [INFO] [stdout] --> src/gradient_kernel_learning.rs:804:9 [INFO] [stdout] | [INFO] [stdout] 804 | target_kernel: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_target_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:805:9 [INFO] [stdout] | [INFO] [stdout] 805 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/gradient_kernel_learning.rs:860:9 [INFO] [stdout] | [INFO] [stdout] 860 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:861:9 [INFO] [stdout] | [INFO] [stdout] 861 | y: Option<&Array1>, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/incremental_nystroem.rs:129:25 [INFO] [stdout] | [INFO] [stdout] 129 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:280:9 [INFO] [stdout] | [INFO] [stdout] 280 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:655:9 [INFO] [stdout] | [INFO] [stdout] 655 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_components` [INFO] [stdout] --> src/incremental_nystroem.rs:898:13 [INFO] [stdout] | [INFO] [stdout] 898 | let current_components = self.components_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:899:13 [INFO] [stdout] | [INFO] [stdout] 899 | let current_normalization = self.normalization_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_components` [INFO] [stdout] --> src/incremental_nystroem.rs:915:14 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:915:30 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/incremental_nystroem.rs:1319:13 [INFO] [stdout] | [INFO] [stdout] 1319 | let components = self [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/information_theoretic.rs:77:14 [INFO] [stdout] | [INFO] [stdout] 77 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/information_theoretic.rs:490:13 [INFO] [stdout] | [INFO] [stdout] 490 | for iteration in 0..self.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cluster_centers` [INFO] [stdout] --> src/information_theoretic.rs:588:9 [INFO] [stdout] | [INFO] [stdout] 588 | cluster_centers: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cluster_centers` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `normal` [INFO] [stdout] --> src/information_theoretic.rs:756:9 [INFO] [stdout] | [INFO] [stdout] 756 | let normal = RandNormal::new(mean, std).unwrap(); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_normal` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:14 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:25 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:14 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:25 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:284:14 [INFO] [stdout] | [INFO] [stdout] 284 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:179:13 [INFO] [stdout] | [INFO] [stdout] 179 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:185:13 [INFO] [stdout] | [INFO] [stdout] 185 | let n_features = x_transformed.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/memory_efficient.rs:90:13 [INFO] [stdout] | [INFO] [stdout] 90 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:255:14 [INFO] [stdout] | [INFO] [stdout] 255 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/multi_kernel_learning.rs:317:14 [INFO] [stdout] | [INFO] [stdout] 317 | for (i, (base_kernel, &weight)) in self.base_kernels.iter().zip(weights.iter()).enumerate() [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/multi_kernel_learning.rs:686:17 [INFO] [stdout] | [INFO] [stdout] 686 | let n = kernel.nrows() as f64; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:726:14 [INFO] [stdout] | [INFO] [stdout] 726 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:757:14 [INFO] [stdout] | [INFO] [stdout] 757 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/multi_scale_rbf.rs:247:25 [INFO] [stdout] | [INFO] [stdout] 247 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gammas` [INFO] [stdout] --> src/multi_scale_rbf.rs:403:13 [INFO] [stdout] | [INFO] [stdout] 403 | let gammas = self [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_gammas` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_scale_rbf.rs:424:14 [INFO] [stdout] | [INFO] [stdout] 424 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/numerical_stability.rs:696:14 [INFO] [stdout] | [INFO] [stdout] 696 | let (n1, n_features) = data1.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/nystroem.rs:294:9 [INFO] [stdout] | [INFO] [stdout] 294 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_valid` [INFO] [stdout] --> src/nystroem.rs:558:13 [INFO] [stdout] | [INFO] [stdout] 558 | let n_valid = valid_indices.len(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_valid` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/optimal_transport.rs:526:13 [INFO] [stdout] | [INFO] [stdout] 526 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `local_idx` [INFO] [stdout] --> src/out_of_core.rs:419:18 [INFO] [stdout] | [INFO] [stdout] 419 | for (local_idx, row) in chunk.axis_iter(Axis(0)).enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_local_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `best_score` [INFO] [stdout] --> src/parameter_learning.rs:908:13 [INFO] [stdout] | [INFO] [stdout] 908 | let best_score = parameter_history [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_best_score` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:221:29 [INFO] [stdout] | [INFO] [stdout] 221 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/progressive.rs:366:9 [INFO] [stdout] | [INFO] [stdout] 366 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:675:29 [INFO] [stdout] | [INFO] [stdout] 675 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `improvement` [INFO] [stdout] --> src/progressive.rs:788:9 [INFO] [stdout] | [INFO] [stdout] 788 | improvement: f64, [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_improvement` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/progressive.rs:790:9 [INFO] [stdout] | [INFO] [stdout] 790 | components: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/quasi_random_features.rs:193:14 [INFO] [stdout] | [INFO] [stdout] 193 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:147:14 [INFO] [stdout] | [INFO] [stdout] 147 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:313:14 [INFO] [stdout] | [INFO] [stdout] 313 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:517:14 [INFO] [stdout] | [INFO] [stdout] 517 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:695:14 [INFO] [stdout] | [INFO] [stdout] 695 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean` [INFO] [stdout] --> src/robust_kernels.rs:231:18 [INFO] [stdout] | [INFO] [stdout] 231 | let (mean, cov) = self.compute_robust_statistics(&subset_data); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/robust_kernels.rs:364:17 [INFO] [stdout] | [INFO] [stdout] 364 | for iteration in 0..self.config.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `index` [INFO] [stdout] --> src/robust_kernels.rs:395:58 [INFO] [stdout] | [INFO] [stdout] 395 | fn compute_residual(&self, sample: &ArrayView1, index: usize) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_index` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:476:9 [INFO] [stdout] | [INFO] [stdout] 476 | cov: &Array2, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:492:53 [INFO] [stdout] | [INFO] [stdout] 492 | fn compute_huber_center(&self, x: &Array2, delta: f64) -> Array1 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:498:74 [INFO] [stdout] | [INFO] [stdout] 498 | fn compute_huber_scale(&self, x: &Array2, center: &Array1, delta: f64) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:516:9 [INFO] [stdout] | [INFO] [stdout] 516 | delta: f64, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:522:53 [INFO] [stdout] | [INFO] [stdout] 522 | fn compute_tukey_center(&self, x: &Array2, c: f64) -> Array1 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:528:74 [INFO] [stdout] | [INFO] [stdout] 528 | fn compute_tukey_scale(&self, x: &Array2, center: &Array1, c: f64) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:546:9 [INFO] [stdout] | [INFO] [stdout] 546 | c: f64, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `basis_idx` [INFO] [stdout] --> src/robust_kernels.rs:757:22 [INFO] [stdout] | [INFO] [stdout] 757 | for (j, &basis_idx) in indices.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_basis_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:916:20 [INFO] [stdout] | [INFO] [stdout] 916 | let (mean, cov) = self.compute_robust_statistics(x); [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/robust_kernels.rs:968:39 [INFO] [stdout] | [INFO] [stdout] 968 | fn compute_robust_estimate(&self, x: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:329:13 [INFO] [stdout] | [INFO] [stdout] 329 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/approximations.rs:354:13 [INFO] [stdout] | [INFO] [stdout] 354 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:355:13 [INFO] [stdout] | [INFO] [stdout] 355 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:405:13 [INFO] [stdout] | [INFO] [stdout] 405 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:414:13 [INFO] [stdout] | [INFO] [stdout] 414 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel` [INFO] [stdout] --> src/sparse_gp/approximations.rs:482:9 [INFO] [stdout] | [INFO] [stdout] 482 | kernel: &K, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/inference.rs:144:13 [INFO] [stdout] | [INFO] [stdout] 144 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/sparse_gp/ski.rs:99:13 [INFO] [stdout] | [INFO] [stdout] 99 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/sparse_gp/ski.rs:428:47 [INFO] [stdout] | [INFO] [stdout] 428 | pub fn fit_tensor(&self, x: &Array2, y: &Array1) -> Result> { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:30:13 [INFO] [stdout] | [INFO] [stdout] 30 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/variational.rs:48:13 [INFO] [stdout] | [INFO] [stdout] 48 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:136:13 [INFO] [stdout] | [INFO] [stdout] 136 | let n = y.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/variational.rs:137:13 [INFO] [stdout] | [INFO] [stdout] 137 | let m = variational_mean.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/variational.rs:311:9 [INFO] [stdout] | [INFO] [stdout] 311 | k_nm: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `noise_variance` [INFO] [stdout] --> src/sparse_gp/variational.rs:314:9 [INFO] [stdout] | [INFO] [stdout] 314 | noise_variance: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_noise_variance` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_cov` [INFO] [stdout] --> src/sparse_gp/variational.rs:425:13 [INFO] [stdout] | [INFO] [stdout] 425 | let variational_cov = variational_cov_factor.dot(&variational_cov_factor.t()); [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_mm_inv` [INFO] [stdout] --> src/sparse_gp/variational.rs:506:13 [INFO] [stdout] | [INFO] [stdout] 506 | let k_mm_inv = KernelOps::invert_using_cholesky(&k_mm)?; [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_mm_inv` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:411:24 [INFO] [stdout] | [INFO] [stdout] 411 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ar_coefficients` [INFO] [stdout] --> src/time_series_kernels.rs:434:13 [INFO] [stdout] | [INFO] [stdout] 434 | let ar_coefficients = self.ar_coefficients.as_ref().ok_or("Model not fitted")?; [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ar_coefficients` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:440:24 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:440:38 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:589:24 [INFO] [stdout] | [INFO] [stdout] 589 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:619:24 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:619:38 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `u2` [INFO] [stdout] --> src/type_safe_kernels.rs:368:29 [INFO] [stdout] | [INFO] [stdout] 368 | let u2: f64 = rng.gen(); [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_u2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/validation.rs:380:18 [INFO] [stdout] | [INFO] [stdout] 380 | for (i, ¶m_value) in param_values.iter().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/validation.rs:675:9 [INFO] [stdout] | [INFO] [stdout] 675 | method: &T, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `dev` profile [unoptimized + debuginfo] target(s) in 4m 08s [INFO] running `Command { std: "docker" "inspect" "6ee3cc0892a72da0c049fdedb25ecb8891129c38abb95b0ab049fad260cd56e2", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "6ee3cc0892a72da0c049fdedb25ecb8891129c38abb95b0ab049fad260cd56e2", kill_on_drop: false }` [INFO] [stdout] 6ee3cc0892a72da0c049fdedb25ecb8891129c38abb95b0ab049fad260cd56e2 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-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@sha256:4848fb76d95f26979359cc7e45710b1dbc8f3acb7aeedee7c460d7702230f228" "/opt/rustwide/cargo-home/bin/cargo" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "test" "--frozen" "--no-run" "--message-format=json", kill_on_drop: false }` [INFO] [stdout] b1336a1142ad2558d8d99122f4dbf7b8fbcae09a6802eaa318c41ecaf82274b5 [INFO] running `Command { std: "docker" "start" "-a" "b1336a1142ad2558d8d99122f4dbf7b8fbcae09a6802eaa318c41ecaf82274b5", kill_on_drop: false }` [INFO] [stderr] Compiling rustix v1.1.2 [INFO] [stderr] Compiling wait-timeout v0.2.1 [INFO] [stderr] Compiling rand_xorshift v0.4.0 [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/plugin_architecture.rs:329:9 [INFO] [stdout] | [INFO] [stdout] 329 | /// PluginMetadata [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 330 | / PluginMetadata { [INFO] [stdout] 331 | | name: "linear_kernel".to_string(), [INFO] [stdout] 332 | | version: "1.0.0".to_string(), [INFO] [stdout] 333 | | description: "Simple linear kernel approximation plugin".to_string(), [INFO] [stdout] ... | [INFO] [stdout] 337 | | optional_parameters: vec!["normalize".to_string()], [INFO] [stdout] 338 | | } [INFO] [stdout] | |_________- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/advanced_testing.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/anisotropic_rbf.rs:29:5 [INFO] [stdout] | [INFO] [stdout] 29 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/benchmarking.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/validation.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/chi2_samplers.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/computer_vision_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safety.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/fastfood.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safe_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/gpu_acceleration.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/gradient_kernel_learning.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/information_theoretic.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/time_series_kernels.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/time_series_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/memory_efficient.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/multi_scale_rbf.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/nlp_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/optimal_transport.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/out_of_core.rs:11:39 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/out_of_core.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Distribution` [INFO] [stdout] --> src/plugin_architecture.rs:415:35 [INFO] [stdout] | [INFO] [stdout] 415 | use scirs2_core::random::{Distribution, StandardNormal}; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/polynomial_count_sketch.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Fft` [INFO] [stdout] --> src/polynomial_count_sketch.rs:3:15 [INFO] [stdout] | [INFO] [stdout] 3 | use rustfft::{Fft, FftPlanner}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/mod.rs:26:39 [INFO] [stdout] | [INFO] [stdout] 26 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/rbf_sampler.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/robust_kernels.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/robust_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `sklears_core::traits::Fit` [INFO] [stdout] --> src/robust_kernels.rs:15:5 [INFO] [stdout] | [INFO] [stdout] 15 | use sklears_core::traits::Fit; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/approximations.rs:10:39 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/mod.rs:25:5 [INFO] [stdout] | [INFO] [stdout] 25 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/inference.rs:13:5 [INFO] [stdout] | [INFO] [stdout] 13 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/inference.rs:14:39 [INFO] [stdout] | [INFO] [stdout] 14 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gamma` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:490:47 [INFO] [stdout] | [INFO] [stdout] 490 | fn kernel_trace(&self, x: &Array2, gamma: Float) -> Result { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_gamma` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:630:14 [INFO] [stdout] | [INFO] [stdout] 630 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/adaptive_dimension.rs:235:9 [INFO] [stdout] | [INFO] [stdout] 235 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:237:9 [INFO] [stdout] | [INFO] [stdout] 237 | x_val_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fitted_sampler` [INFO] [stdout] --> src/adaptive_dimension.rs:238:9 [INFO] [stdout] | [INFO] [stdout] 238 | fitted_sampler: &crate::rbf_sampler::RBFSampler, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fitted_sampler` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/adaptive_dimension.rs:400:9 [INFO] [stdout] | [INFO] [stdout] 400 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:402:9 [INFO] [stdout] | [INFO] [stdout] 402 | x_train_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/anisotropic_rbf.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | for iter in 0..self.max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_inv_sqrt` [INFO] [stdout] --> src/anisotropic_rbf.rs:195:13 [INFO] [stdout] | [INFO] [stdout] 195 | let k_inv_sqrt = u.dot(&s_inv_diag).dot(&vt); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_inv_sqrt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `vt` [INFO] [stdout] --> src/anisotropic_rbf.rs:662:20 [INFO] [stdout] | [INFO] [stdout] 662 | let (u, s, vt) = precision.svd(true, true).map_err(|e| { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_vt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method_name` [INFO] [stdout] --> src/benchmarking.rs:391:13 [INFO] [stdout] | [INFO] [stdout] 391 | let method_name = method.method_name(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_method_name` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fit_start` [INFO] [stdout] --> src/benchmarking.rs:440:13 [INFO] [stdout] | [INFO] [stdout] 440 | let fit_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fit_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:193:13 [INFO] [stdout] | [INFO] [stdout] 193 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:214:17 [INFO] [stdout] | [INFO] [stdout] 214 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/budget_constrained.rs:240:21 [INFO] [stdout] | [INFO] [stdout] 240 | let x_train_transformed = fitted.transform(&x_train)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_quality` [INFO] [stdout] --> src/budget_constrained.rs:375:9 [INFO] [stdout] | [INFO] [stdout] 375 | current_quality: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_quality` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:493:13 [INFO] [stdout] | [INFO] [stdout] 493 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:504:17 [INFO] [stdout] | [INFO] [stdout] 504 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:120:18 [INFO] [stdout] | [INFO] [stdout] 120 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:420:18 [INFO] [stdout] | [INFO] [stdout] 420 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:648:21 [INFO] [stdout] | [INFO] [stdout] 648 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:649:21 [INFO] [stdout] | [INFO] [stdout] 649 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:749:21 [INFO] [stdout] | [INFO] [stdout] 749 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:750:21 [INFO] [stdout] | [INFO] [stdout] 750 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:945:18 [INFO] [stdout] | [INFO] [stdout] 945 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:685:27 [INFO] [stdout] | [INFO] [stdout] 685 | fn compute_mse(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:693:27 [INFO] [stdout] | [INFO] [stdout] 693 | fn compute_mae(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:700:32 [INFO] [stdout] | [INFO] [stdout] 700 | fn compute_r2_score(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/custom_kernel.rs:387:14 [INFO] [stdout] | [INFO] [stdout] 387 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/distributed_kernel.rs:448:14 [INFO] [stdout] | [INFO] [stdout] 448 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:160:9 [INFO] [stdout] | [INFO] [stdout] 160 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:409:9 [INFO] [stdout] | [INFO] [stdout] 409 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/error_bounded.rs:125:13 [INFO] [stdout] | [INFO] [stdout] 125 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/error_bounded.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | let x_test = x [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/error_bounded.rs:217:9 [INFO] [stdout] | [INFO] [stdout] 217 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:364:9 [INFO] [stdout] | [INFO] [stdout] 364 | n_components: usize, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/error_bounded.rs:517:13 [INFO] [stdout] | [INFO] [stdout] 517 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:585:57 [INFO] [stdout] | [INFO] [stdout] 585 | fn compute_error_bound(&self, trial_errors: &[f64], n_components: usize) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `block_end` [INFO] [stdout] --> src/fastfood.rs:274:17 [INFO] [stdout] | [INFO] [stdout] 274 | let block_end = block_start + padded_dim; [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_block_end` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ctx` [INFO] [stdout] --> src/gpu_acceleration.rs:1002:9 [INFO] [stdout] | [INFO] [stdout] 1002 | ctx: &GpuContext, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_ctx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gradient_kernel_learning.rs:215:13 [INFO] [stdout] | [INFO] [stdout] 215 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `param_idx` [INFO] [stdout] --> src/gradient_kernel_learning.rs:620:13 [INFO] [stdout] | [INFO] [stdout] 620 | for param_idx in 1..self.parameters.len() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:698:9 [INFO] [stdout] | [INFO] [stdout] 698 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:699:9 [INFO] [stdout] | [INFO] [stdout] 699 | y_train: &Array1, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:700:9 [INFO] [stdout] | [INFO] [stdout] 700 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:701:9 [INFO] [stdout] | [INFO] [stdout] 701 | y_val: &Array1, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_y_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:717:9 [INFO] [stdout] | [INFO] [stdout] 717 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:718:9 [INFO] [stdout] | [INFO] [stdout] 718 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:727:9 [INFO] [stdout] | [INFO] [stdout] 727 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:728:9 [INFO] [stdout] | [INFO] [stdout] 728 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:729:9 [INFO] [stdout] | [INFO] [stdout] 729 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:738:9 [INFO] [stdout] | [INFO] [stdout] 738 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:739:9 [INFO] [stdout] | [INFO] [stdout] 739 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:748:9 [INFO] [stdout] | [INFO] [stdout] 748 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:749:9 [INFO] [stdout] | [INFO] [stdout] 749 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:750:9 [INFO] [stdout] | [INFO] [stdout] 750 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:27 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:49 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:765:9 [INFO] [stdout] | [INFO] [stdout] 765 | x1: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:766:9 [INFO] [stdout] | [INFO] [stdout] 766 | x2: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:803:9 [INFO] [stdout] | [INFO] [stdout] 803 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `target_kernel` [INFO] [stdout] --> src/gradient_kernel_learning.rs:804:9 [INFO] [stdout] | [INFO] [stdout] 804 | target_kernel: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_target_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:805:9 [INFO] [stdout] | [INFO] [stdout] 805 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/gradient_kernel_learning.rs:860:9 [INFO] [stdout] | [INFO] [stdout] 860 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:861:9 [INFO] [stdout] | [INFO] [stdout] 861 | y: Option<&Array1>, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/incremental_nystroem.rs:129:25 [INFO] [stdout] | [INFO] [stdout] 129 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:280:9 [INFO] [stdout] | [INFO] [stdout] 280 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:655:9 [INFO] [stdout] | [INFO] [stdout] 655 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_components` [INFO] [stdout] --> src/incremental_nystroem.rs:898:13 [INFO] [stdout] | [INFO] [stdout] 898 | let current_components = self.components_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:899:13 [INFO] [stdout] | [INFO] [stdout] 899 | let current_normalization = self.normalization_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_components` [INFO] [stdout] --> src/incremental_nystroem.rs:915:14 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:915:30 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/incremental_nystroem.rs:1319:13 [INFO] [stdout] | [INFO] [stdout] 1319 | let components = self [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/information_theoretic.rs:77:14 [INFO] [stdout] | [INFO] [stdout] 77 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/information_theoretic.rs:490:13 [INFO] [stdout] | [INFO] [stdout] 490 | for iteration in 0..self.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cluster_centers` [INFO] [stdout] --> src/information_theoretic.rs:588:9 [INFO] [stdout] | [INFO] [stdout] 588 | cluster_centers: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cluster_centers` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `normal` [INFO] [stdout] --> src/information_theoretic.rs:756:9 [INFO] [stdout] | [INFO] [stdout] 756 | let normal = RandNormal::new(mean, std).unwrap(); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_normal` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:14 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:25 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:14 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:25 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:284:14 [INFO] [stdout] | [INFO] [stdout] 284 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:179:13 [INFO] [stdout] | [INFO] [stdout] 179 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:185:13 [INFO] [stdout] | [INFO] [stdout] 185 | let n_features = x_transformed.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/memory_efficient.rs:90:13 [INFO] [stdout] | [INFO] [stdout] 90 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:255:14 [INFO] [stdout] | [INFO] [stdout] 255 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/multi_kernel_learning.rs:317:14 [INFO] [stdout] | [INFO] [stdout] 317 | for (i, (base_kernel, &weight)) in self.base_kernels.iter().zip(weights.iter()).enumerate() [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/multi_kernel_learning.rs:686:17 [INFO] [stdout] | [INFO] [stdout] 686 | let n = kernel.nrows() as f64; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:726:14 [INFO] [stdout] | [INFO] [stdout] 726 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:757:14 [INFO] [stdout] | [INFO] [stdout] 757 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/multi_scale_rbf.rs:247:25 [INFO] [stdout] | [INFO] [stdout] 247 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gammas` [INFO] [stdout] --> src/multi_scale_rbf.rs:403:13 [INFO] [stdout] | [INFO] [stdout] 403 | let gammas = self [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_gammas` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_scale_rbf.rs:424:14 [INFO] [stdout] | [INFO] [stdout] 424 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/numerical_stability.rs:696:14 [INFO] [stdout] | [INFO] [stdout] 696 | let (n1, n_features) = data1.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/nystroem.rs:294:9 [INFO] [stdout] | [INFO] [stdout] 294 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_valid` [INFO] [stdout] --> src/nystroem.rs:558:13 [INFO] [stdout] | [INFO] [stdout] 558 | let n_valid = valid_indices.len(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_valid` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/optimal_transport.rs:526:13 [INFO] [stdout] | [INFO] [stdout] 526 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `local_idx` [INFO] [stdout] --> src/out_of_core.rs:419:18 [INFO] [stdout] | [INFO] [stdout] 419 | for (local_idx, row) in chunk.axis_iter(Axis(0)).enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_local_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `best_score` [INFO] [stdout] --> src/parameter_learning.rs:908:13 [INFO] [stdout] | [INFO] [stdout] 908 | let best_score = parameter_history [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_best_score` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:221:29 [INFO] [stdout] | [INFO] [stdout] 221 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/progressive.rs:366:9 [INFO] [stdout] | [INFO] [stdout] 366 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:675:29 [INFO] [stdout] | [INFO] [stdout] 675 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `improvement` [INFO] [stdout] --> src/progressive.rs:788:9 [INFO] [stdout] | [INFO] [stdout] 788 | improvement: f64, [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_improvement` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/progressive.rs:790:9 [INFO] [stdout] | [INFO] [stdout] 790 | components: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/quasi_random_features.rs:193:14 [INFO] [stdout] | [INFO] [stdout] 193 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:147:14 [INFO] [stdout] | [INFO] [stdout] 147 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:313:14 [INFO] [stdout] | [INFO] [stdout] 313 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:517:14 [INFO] [stdout] | [INFO] [stdout] 517 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:695:14 [INFO] [stdout] | [INFO] [stdout] 695 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean` [INFO] [stdout] --> src/robust_kernels.rs:231:18 [INFO] [stdout] | [INFO] [stdout] 231 | let (mean, cov) = self.compute_robust_statistics(&subset_data); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/robust_kernels.rs:364:17 [INFO] [stdout] | [INFO] [stdout] 364 | for iteration in 0..self.config.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `index` [INFO] [stdout] --> src/robust_kernels.rs:395:58 [INFO] [stdout] | [INFO] [stdout] 395 | fn compute_residual(&self, sample: &ArrayView1, index: usize) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_index` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:476:9 [INFO] [stdout] | [INFO] [stdout] 476 | cov: &Array2, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:492:53 [INFO] [stdout] | [INFO] [stdout] 492 | fn compute_huber_center(&self, x: &Array2, delta: f64) -> Array1 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:498:74 [INFO] [stdout] | [INFO] [stdout] 498 | fn compute_huber_scale(&self, x: &Array2, center: &Array1, delta: f64) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:516:9 [INFO] [stdout] | [INFO] [stdout] 516 | delta: f64, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:522:53 [INFO] [stdout] | [INFO] [stdout] 522 | fn compute_tukey_center(&self, x: &Array2, c: f64) -> Array1 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:528:74 [INFO] [stdout] | [INFO] [stdout] 528 | fn compute_tukey_scale(&self, x: &Array2, center: &Array1, c: f64) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:546:9 [INFO] [stdout] | [INFO] [stdout] 546 | c: f64, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `basis_idx` [INFO] [stdout] --> src/robust_kernels.rs:757:22 [INFO] [stdout] | [INFO] [stdout] 757 | for (j, &basis_idx) in indices.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_basis_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:916:20 [INFO] [stdout] | [INFO] [stdout] 916 | let (mean, cov) = self.compute_robust_statistics(x); [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/robust_kernels.rs:968:39 [INFO] [stdout] | [INFO] [stdout] 968 | fn compute_robust_estimate(&self, x: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:329:13 [INFO] [stdout] | [INFO] [stdout] 329 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/approximations.rs:354:13 [INFO] [stdout] | [INFO] [stdout] 354 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:355:13 [INFO] [stdout] | [INFO] [stdout] 355 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:405:13 [INFO] [stdout] | [INFO] [stdout] 405 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:414:13 [INFO] [stdout] | [INFO] [stdout] 414 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel` [INFO] [stdout] --> src/sparse_gp/approximations.rs:482:9 [INFO] [stdout] | [INFO] [stdout] 482 | kernel: &K, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/inference.rs:144:13 [INFO] [stdout] | [INFO] [stdout] 144 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/sparse_gp/ski.rs:99:13 [INFO] [stdout] | [INFO] [stdout] 99 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/sparse_gp/ski.rs:428:47 [INFO] [stdout] | [INFO] [stdout] 428 | pub fn fit_tensor(&self, x: &Array2, y: &Array1) -> Result> { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:30:13 [INFO] [stdout] | [INFO] [stdout] 30 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/variational.rs:48:13 [INFO] [stdout] | [INFO] [stdout] 48 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:136:13 [INFO] [stdout] | [INFO] [stdout] 136 | let n = y.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/variational.rs:137:13 [INFO] [stdout] | [INFO] [stdout] 137 | let m = variational_mean.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/variational.rs:311:9 [INFO] [stdout] | [INFO] [stdout] 311 | k_nm: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `noise_variance` [INFO] [stdout] --> src/sparse_gp/variational.rs:314:9 [INFO] [stdout] | [INFO] [stdout] 314 | noise_variance: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_noise_variance` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_cov` [INFO] [stdout] --> src/sparse_gp/variational.rs:425:13 [INFO] [stdout] | [INFO] [stdout] 425 | let variational_cov = variational_cov_factor.dot(&variational_cov_factor.t()); [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_mm_inv` [INFO] [stdout] --> src/sparse_gp/variational.rs:506:13 [INFO] [stdout] | [INFO] [stdout] 506 | let k_mm_inv = KernelOps::invert_using_cholesky(&k_mm)?; [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_mm_inv` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:411:24 [INFO] [stdout] | [INFO] [stdout] 411 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ar_coefficients` [INFO] [stdout] --> src/time_series_kernels.rs:434:13 [INFO] [stdout] | [INFO] [stdout] 434 | let ar_coefficients = self.ar_coefficients.as_ref().ok_or("Model not fitted")?; [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ar_coefficients` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:440:24 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:440:38 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:589:24 [INFO] [stdout] | [INFO] [stdout] 589 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:619:24 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:619:38 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `u2` [INFO] [stdout] --> src/type_safe_kernels.rs:368:29 [INFO] [stdout] | [INFO] [stdout] 368 | let u2: f64 = rng.gen(); [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_u2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/validation.rs:380:18 [INFO] [stdout] | [INFO] [stdout] 380 | for (i, ¶m_value) in param_values.iter().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/validation.rs:675:9 [INFO] [stdout] | [INFO] [stdout] 675 | method: &T, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Compiling tempfile v3.23.0 [INFO] [stderr] Compiling rusty-fork v0.3.0 [INFO] [stderr] Compiling proptest v1.8.0 [INFO] [stderr] Compiling sklears-kernel-approximation v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/plugin_architecture.rs:329:9 [INFO] [stdout] | [INFO] [stdout] 329 | /// PluginMetadata [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 330 | / PluginMetadata { [INFO] [stdout] 331 | | name: "linear_kernel".to_string(), [INFO] [stdout] 332 | | version: "1.0.0".to_string(), [INFO] [stdout] 333 | | description: "Simple linear kernel approximation plugin".to_string(), [INFO] [stdout] ... | [INFO] [stdout] 337 | | optional_parameters: vec!["normalize".to_string()], [INFO] [stdout] 338 | | } [INFO] [stdout] | |_________- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `sklears_core::traits::Fit` [INFO] [stdout] --> src/robust_kernels.rs:15:5 [INFO] [stdout] | [INFO] [stdout] 15 | use sklears_core::traits::Fit; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/validation.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/advanced_testing.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/anisotropic_rbf.rs:29:5 [INFO] [stdout] | [INFO] [stdout] 29 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safety.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/benchmarking.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/chi2_samplers.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/type_safe_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/computer_vision_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/optimal_transport.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/time_series_kernels.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/time_series_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/out_of_core.rs:11:39 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/out_of_core.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/fastfood.rs:11:5 [INFO] [stdout] | [INFO] [stdout] 11 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/gpu_acceleration.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/gradient_kernel_learning.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/mod.rs:25:5 [INFO] [stdout] | [INFO] [stdout] 25 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/robust_kernels.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/mod.rs:26:39 [INFO] [stdout] | [INFO] [stdout] 26 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/robust_kernels.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/information_theoretic.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Distribution` [INFO] [stdout] --> src/plugin_architecture.rs:415:35 [INFO] [stdout] | [INFO] [stdout] 415 | use scirs2_core::random::{Distribution, StandardNormal}; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/polynomial_count_sketch.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Fft` [INFO] [stdout] --> src/polynomial_count_sketch.rs:3:15 [INFO] [stdout] | [INFO] [stdout] 3 | use rustfft::{Fft, FftPlanner}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/memory_efficient.rs:12:5 [INFO] [stdout] | [INFO] [stdout] 12 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/multi_scale_rbf.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/inference.rs:14:39 [INFO] [stdout] | [INFO] [stdout] 14 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/sparse_gp/inference.rs:13:5 [INFO] [stdout] | [INFO] [stdout] 13 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/nlp_kernels.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/rbf_sampler.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/sparse_gp/approximations.rs:10:39 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gamma` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:490:47 [INFO] [stdout] | [INFO] [stdout] 490 | fn kernel_trace(&self, x: &Array2, gamma: Float) -> Result { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_gamma` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/adaptive_bandwidth_rbf.rs:630:14 [INFO] [stdout] | [INFO] [stdout] 630 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/adaptive_dimension.rs:235:9 [INFO] [stdout] | [INFO] [stdout] 235 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:237:9 [INFO] [stdout] | [INFO] [stdout] 237 | x_val_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fitted_sampler` [INFO] [stdout] --> src/adaptive_dimension.rs:238:9 [INFO] [stdout] | [INFO] [stdout] 238 | fitted_sampler: &crate::rbf_sampler::RBFSampler, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fitted_sampler` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/adaptive_dimension.rs:400:9 [INFO] [stdout] | [INFO] [stdout] 400 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/adaptive_dimension.rs:402:9 [INFO] [stdout] | [INFO] [stdout] 402 | x_train_transformed: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/anisotropic_rbf.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | for iter in 0..self.max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_inv_sqrt` [INFO] [stdout] --> src/anisotropic_rbf.rs:195:13 [INFO] [stdout] | [INFO] [stdout] 195 | let k_inv_sqrt = u.dot(&s_inv_diag).dot(&vt); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_inv_sqrt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `vt` [INFO] [stdout] --> src/anisotropic_rbf.rs:662:20 [INFO] [stdout] | [INFO] [stdout] 662 | let (u, s, vt) = precision.svd(true, true).map_err(|e| { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_vt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method_name` [INFO] [stdout] --> src/benchmarking.rs:391:13 [INFO] [stdout] | [INFO] [stdout] 391 | let method_name = method.method_name(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_method_name` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fit_start` [INFO] [stdout] --> src/benchmarking.rs:440:13 [INFO] [stdout] | [INFO] [stdout] 440 | let fit_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fit_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data` [INFO] [stdout] --> src/benchmarking.rs:901:13 [INFO] [stdout] | [INFO] [stdout] 901 | data: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:193:13 [INFO] [stdout] | [INFO] [stdout] 193 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:214:17 [INFO] [stdout] | [INFO] [stdout] 214 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train_transformed` [INFO] [stdout] --> src/budget_constrained.rs:240:21 [INFO] [stdout] | [INFO] [stdout] 240 | let x_train_transformed = fitted.transform(&x_train)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_quality` [INFO] [stdout] --> src/budget_constrained.rs:375:9 [INFO] [stdout] | [INFO] [stdout] 375 | current_quality: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_quality` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/budget_constrained.rs:493:13 [INFO] [stdout] | [INFO] [stdout] 493 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `config_start` [INFO] [stdout] --> src/budget_constrained.rs:504:17 [INFO] [stdout] | [INFO] [stdout] 504 | let config_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:120:18 [INFO] [stdout] | [INFO] [stdout] 120 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:420:18 [INFO] [stdout] | [INFO] [stdout] 420 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:648:21 [INFO] [stdout] | [INFO] [stdout] 648 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:649:21 [INFO] [stdout] | [INFO] [stdout] 649 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ix` [INFO] [stdout] --> src/computer_vision_kernels.rs:749:21 [INFO] [stdout] | [INFO] [stdout] 749 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iy` [INFO] [stdout] --> src/computer_vision_kernels.rs:750:21 [INFO] [stdout] | [INFO] [stdout] 750 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/computer_vision_kernels.rs:945:18 [INFO] [stdout] | [INFO] [stdout] 945 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:685:27 [INFO] [stdout] | [INFO] [stdout] 685 | fn compute_mse(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:693:27 [INFO] [stdout] | [INFO] [stdout] 693 | fn compute_mae(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_transformed` [INFO] [stdout] --> src/cross_validation.rs:700:32 [INFO] [stdout] | [INFO] [stdout] 700 | fn compute_r2_score(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/custom_kernel.rs:387:14 [INFO] [stdout] | [INFO] [stdout] 387 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/distributed_kernel.rs:448:14 [INFO] [stdout] | [INFO] [stdout] 448 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:160:9 [INFO] [stdout] | [INFO] [stdout] 160 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/ensemble_nystroem.rs:409:9 [INFO] [stdout] | [INFO] [stdout] 409 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/error_bounded.rs:125:13 [INFO] [stdout] | [INFO] [stdout] 125 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/error_bounded.rs:132:13 [INFO] [stdout] | [INFO] [stdout] 132 | let x_test = x [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/error_bounded.rs:217:9 [INFO] [stdout] | [INFO] [stdout] 217 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:364:9 [INFO] [stdout] | [INFO] [stdout] 364 | n_components: usize, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/error_bounded.rs:517:13 [INFO] [stdout] | [INFO] [stdout] 517 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/error_bounded.rs:585:57 [INFO] [stdout] | [INFO] [stdout] 585 | fn compute_error_bound(&self, trial_errors: &[f64], n_components: usize) -> Result { [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `block_end` [INFO] [stdout] --> src/fastfood.rs:274:17 [INFO] [stdout] | [INFO] [stdout] 274 | let block_end = block_start + padded_dim; [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_block_end` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ctx` [INFO] [stdout] --> src/gpu_acceleration.rs:1002:9 [INFO] [stdout] | [INFO] [stdout] 1002 | ctx: &GpuContext, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_ctx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gradient_kernel_learning.rs:215:13 [INFO] [stdout] | [INFO] [stdout] 215 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `param_idx` [INFO] [stdout] --> src/gradient_kernel_learning.rs:620:13 [INFO] [stdout] | [INFO] [stdout] 620 | for param_idx in 1..self.parameters.len() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:698:9 [INFO] [stdout] | [INFO] [stdout] 698 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/gradient_kernel_learning.rs:699:9 [INFO] [stdout] | [INFO] [stdout] 699 | y_train: &Array1, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:700:9 [INFO] [stdout] | [INFO] [stdout] 700 | x_val: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_val` [INFO] [stdout] --> src/gradient_kernel_learning.rs:701:9 [INFO] [stdout] | [INFO] [stdout] 701 | y_val: &Array1, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_y_val` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:717:9 [INFO] [stdout] | [INFO] [stdout] 717 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:718:9 [INFO] [stdout] | [INFO] [stdout] 718 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:727:9 [INFO] [stdout] | [INFO] [stdout] 727 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:728:9 [INFO] [stdout] | [INFO] [stdout] 728 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:729:9 [INFO] [stdout] | [INFO] [stdout] 729 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:738:9 [INFO] [stdout] | [INFO] [stdout] 738 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:739:9 [INFO] [stdout] | [INFO] [stdout] 739 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:748:9 [INFO] [stdout] | [INFO] [stdout] 748 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:749:9 [INFO] [stdout] | [INFO] [stdout] 749 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:750:9 [INFO] [stdout] | [INFO] [stdout] 750 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:27 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:757:49 [INFO] [stdout] | [INFO] [stdout] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x1` [INFO] [stdout] --> src/gradient_kernel_learning.rs:765:9 [INFO] [stdout] | [INFO] [stdout] 765 | x1: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x2` [INFO] [stdout] --> src/gradient_kernel_learning.rs:766:9 [INFO] [stdout] | [INFO] [stdout] 766 | x2: &ArrayView2, [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_matrix` [INFO] [stdout] --> src/gradient_kernel_learning.rs:803:9 [INFO] [stdout] | [INFO] [stdout] 803 | kernel_matrix: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `target_kernel` [INFO] [stdout] --> src/gradient_kernel_learning.rs:804:9 [INFO] [stdout] | [INFO] [stdout] 804 | target_kernel: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_target_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel_derivative` [INFO] [stdout] --> src/gradient_kernel_learning.rs:805:9 [INFO] [stdout] | [INFO] [stdout] 805 | kernel_derivative: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/gradient_kernel_learning.rs:860:9 [INFO] [stdout] | [INFO] [stdout] 860 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/gradient_kernel_learning.rs:861:9 [INFO] [stdout] | [INFO] [stdout] 861 | y: Option<&Array1>, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/incremental_nystroem.rs:129:25 [INFO] [stdout] | [INFO] [stdout] 129 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:280:9 [INFO] [stdout] | [INFO] [stdout] 280 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/incremental_nystroem.rs:655:9 [INFO] [stdout] | [INFO] [stdout] 655 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_components` [INFO] [stdout] --> src/incremental_nystroem.rs:898:13 [INFO] [stdout] | [INFO] [stdout] 898 | let current_components = self.components_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `current_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:899:13 [INFO] [stdout] | [INFO] [stdout] 899 | let current_normalization = self.normalization_.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_components` [INFO] [stdout] --> src/incremental_nystroem.rs:915:14 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_normalization` [INFO] [stdout] --> src/incremental_nystroem.rs:915:30 [INFO] [stdout] | [INFO] [stdout] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_normalization` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/incremental_nystroem.rs:1319:13 [INFO] [stdout] | [INFO] [stdout] 1319 | let components = self [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/information_theoretic.rs:77:14 [INFO] [stdout] | [INFO] [stdout] 77 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/information_theoretic.rs:490:13 [INFO] [stdout] | [INFO] [stdout] 490 | for iteration in 0..self.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cluster_centers` [INFO] [stdout] --> src/information_theoretic.rs:588:9 [INFO] [stdout] | [INFO] [stdout] 588 | cluster_centers: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cluster_centers` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `normal` [INFO] [stdout] --> src/information_theoretic.rs:756:9 [INFO] [stdout] | [INFO] [stdout] 756 | let normal = RandNormal::new(mean, std).unwrap(); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_normal` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:14 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:182:25 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:14 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:251:25 [INFO] [stdout] | [INFO] [stdout] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/basic_regression.rs:284:14 [INFO] [stdout] | [INFO] [stdout] 284 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:179:13 [INFO] [stdout] | [INFO] [stdout] 179 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/kernel_ridge_regression/multitask_regression.rs:185:13 [INFO] [stdout] | [INFO] [stdout] 185 | let n_features = x_transformed.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/memory_efficient.rs:90:13 [INFO] [stdout] | [INFO] [stdout] 90 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:255:14 [INFO] [stdout] | [INFO] [stdout] 255 | let (n_samples, _) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/multi_kernel_learning.rs:317:14 [INFO] [stdout] | [INFO] [stdout] 317 | for (i, (base_kernel, &weight)) in self.base_kernels.iter().zip(weights.iter()).enumerate() [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/multi_kernel_learning.rs:686:17 [INFO] [stdout] | [INFO] [stdout] 686 | let n = kernel.nrows() as f64; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:726:14 [INFO] [stdout] | [INFO] [stdout] 726 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_kernel_learning.rs:757:14 [INFO] [stdout] | [INFO] [stdout] 757 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/multi_scale_rbf.rs:247:25 [INFO] [stdout] | [INFO] [stdout] 247 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `gammas` [INFO] [stdout] --> src/multi_scale_rbf.rs:403:13 [INFO] [stdout] | [INFO] [stdout] 403 | let gammas = self [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_gammas` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_scale_rbf.rs:424:14 [INFO] [stdout] | [INFO] [stdout] 424 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/numerical_stability.rs:696:14 [INFO] [stdout] | [INFO] [stdout] 696 | let (n1, n_features) = data1.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/nystroem.rs:294:9 [INFO] [stdout] | [INFO] [stdout] 294 | rng: &mut RealStdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_valid` [INFO] [stdout] --> src/nystroem.rs:558:13 [INFO] [stdout] | [INFO] [stdout] 558 | let n_valid = valid_indices.len(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_valid` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/optimal_transport.rs:526:13 [INFO] [stdout] | [INFO] [stdout] 526 | let n_samples = x.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `local_idx` [INFO] [stdout] --> src/out_of_core.rs:419:18 [INFO] [stdout] | [INFO] [stdout] 419 | for (local_idx, row) in chunk.axis_iter(Axis(0)).enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_local_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `best_score` [INFO] [stdout] --> src/parameter_learning.rs:908:13 [INFO] [stdout] | [INFO] [stdout] 908 | let best_score = parameter_history [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_best_score` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:221:29 [INFO] [stdout] | [INFO] [stdout] 221 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/progressive.rs:366:9 [INFO] [stdout] | [INFO] [stdout] 366 | x: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `converged` is never read [INFO] [stdout] --> src/progressive.rs:675:29 [INFO] [stdout] | [INFO] [stdout] 675 | let mut converged = false; [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `improvement` [INFO] [stdout] --> src/progressive.rs:788:9 [INFO] [stdout] | [INFO] [stdout] 788 | improvement: f64, [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_improvement` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `components` [INFO] [stdout] --> src/progressive.rs:790:9 [INFO] [stdout] | [INFO] [stdout] 790 | components: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/quasi_random_features.rs:193:14 [INFO] [stdout] | [INFO] [stdout] 193 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:147:14 [INFO] [stdout] | [INFO] [stdout] 147 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:313:14 [INFO] [stdout] | [INFO] [stdout] 313 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:517:14 [INFO] [stdout] | [INFO] [stdout] 517 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/rbf_sampler.rs:695:14 [INFO] [stdout] | [INFO] [stdout] 695 | let (n_samples, n_features) = x.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean` [INFO] [stdout] --> src/robust_kernels.rs:231:18 [INFO] [stdout] | [INFO] [stdout] 231 | let (mean, cov) = self.compute_robust_statistics(&subset_data); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/robust_kernels.rs:364:17 [INFO] [stdout] | [INFO] [stdout] 364 | for iteration in 0..self.config.max_iterations { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `index` [INFO] [stdout] --> src/robust_kernels.rs:395:58 [INFO] [stdout] | [INFO] [stdout] 395 | fn compute_residual(&self, sample: &ArrayView1, index: usize) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_index` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:476:9 [INFO] [stdout] | [INFO] [stdout] 476 | cov: &Array2, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:492:53 [INFO] [stdout] | [INFO] [stdout] 492 | fn compute_huber_center(&self, x: &Array2, delta: f64) -> Array1 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:498:74 [INFO] [stdout] | [INFO] [stdout] 498 | fn compute_huber_scale(&self, x: &Array2, center: &Array1, delta: f64) -> f64 { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `delta` [INFO] [stdout] --> src/robust_kernels.rs:516:9 [INFO] [stdout] | [INFO] [stdout] 516 | delta: f64, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:522:53 [INFO] [stdout] | [INFO] [stdout] 522 | fn compute_tukey_center(&self, x: &Array2, c: f64) -> Array1 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:528:74 [INFO] [stdout] | [INFO] [stdout] 528 | fn compute_tukey_scale(&self, x: &Array2, center: &Array1, c: f64) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `c` [INFO] [stdout] --> src/robust_kernels.rs:546:9 [INFO] [stdout] | [INFO] [stdout] 546 | c: f64, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `basis_idx` [INFO] [stdout] --> src/robust_kernels.rs:757:22 [INFO] [stdout] | [INFO] [stdout] 757 | for (j, &basis_idx) in indices.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_basis_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/robust_kernels.rs:916:20 [INFO] [stdout] | [INFO] [stdout] 916 | let (mean, cov) = self.compute_robust_statistics(x); [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/robust_kernels.rs:968:39 [INFO] [stdout] | [INFO] [stdout] 968 | fn compute_robust_estimate(&self, x: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:329:13 [INFO] [stdout] | [INFO] [stdout] 329 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/approximations.rs:354:13 [INFO] [stdout] | [INFO] [stdout] 354 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:355:13 [INFO] [stdout] | [INFO] [stdout] 355 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/approximations.rs:405:13 [INFO] [stdout] | [INFO] [stdout] 405 | let m = inducing_points.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/approximations.rs:414:13 [INFO] [stdout] | [INFO] [stdout] 414 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `kernel` [INFO] [stdout] --> src/sparse_gp/approximations.rs:482:9 [INFO] [stdout] | [INFO] [stdout] 482 | kernel: &K, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/inference.rs:144:13 [INFO] [stdout] | [INFO] [stdout] 144 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/sparse_gp/ski.rs:99:13 [INFO] [stdout] | [INFO] [stdout] 99 | let n_features = x.ncols(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/sparse_gp/ski.rs:428:47 [INFO] [stdout] | [INFO] [stdout] 428 | pub fn fit_tensor(&self, x: &Array2, y: &Array1) -> Result> { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> src/sparse_gp/ski.rs:631:13 [INFO] [stdout] | [INFO] [stdout] 631 | let x = array![[0.0, 0.0], [1.0, 1.0]]; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:30:13 [INFO] [stdout] | [INFO] [stdout] 30 | let n = x.nrows(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/sparse_gp/variational.rs:48:13 [INFO] [stdout] | [INFO] [stdout] 48 | for iter in 0..max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/sparse_gp/variational.rs:136:13 [INFO] [stdout] | [INFO] [stdout] 136 | let n = y.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `m` [INFO] [stdout] --> src/sparse_gp/variational.rs:137:13 [INFO] [stdout] | [INFO] [stdout] 137 | let m = variational_mean.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_nm` [INFO] [stdout] --> src/sparse_gp/variational.rs:311:9 [INFO] [stdout] | [INFO] [stdout] 311 | k_nm: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `noise_variance` [INFO] [stdout] --> src/sparse_gp/variational.rs:314:9 [INFO] [stdout] | [INFO] [stdout] 314 | noise_variance: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_noise_variance` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_cov` [INFO] [stdout] --> src/sparse_gp/variational.rs:425:13 [INFO] [stdout] | [INFO] [stdout] 425 | let variational_cov = variational_cov_factor.dot(&variational_cov_factor.t()); [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k_mm_inv` [INFO] [stdout] --> src/sparse_gp/variational.rs:506:13 [INFO] [stdout] | [INFO] [stdout] 506 | let k_mm_inv = KernelOps::invert_using_cholesky(&k_mm)?; [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_mm_inv` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `drift_detected` [INFO] [stdout] --> src/streaming_kernel.rs:970:13 [INFO] [stdout] | [INFO] [stdout] 970 | let drift_detected = sampler.detect_drift(&x2).unwrap(); [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_drift_detected` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:411:24 [INFO] [stdout] | [INFO] [stdout] 411 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ar_coefficients` [INFO] [stdout] --> src/time_series_kernels.rs:434:13 [INFO] [stdout] | [INFO] [stdout] 434 | let ar_coefficients = self.ar_coefficients.as_ref().ok_or("Model not fitted")?; [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ar_coefficients` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:440:24 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:440:38 [INFO] [stdout] | [INFO] [stdout] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:589:24 [INFO] [stdout] | [INFO] [stdout] 589 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_timepoints` [INFO] [stdout] --> src/time_series_kernels.rs:619:24 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/time_series_kernels.rs:619:38 [INFO] [stdout] | [INFO] [stdout] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `u2` [INFO] [stdout] --> src/type_safe_kernels.rs:368:29 [INFO] [stdout] | [INFO] [stdout] 368 | let u2: f64 = rng.gen(); [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_u2` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fast_config` [INFO] [stdout] --> src/type_safety.rs:1737:13 [INFO] [stdout] | [INFO] [stdout] 1737 | let fast_config = KernelPresets::fast_rbf_128(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fast_config` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `balanced_config` [INFO] [stdout] --> src/type_safety.rs:1743:13 [INFO] [stdout] | [INFO] [stdout] 1743 | let balanced_config = KernelPresets::balanced_rbf_256(); [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_balanced_config` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `accurate_config` [INFO] [stdout] --> src/type_safety.rs:1749:13 [INFO] [stdout] | [INFO] [stdout] 1749 | let accurate_config = KernelPresets::accurate_rbf_512(); [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_accurate_config` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/validation.rs:380:18 [INFO] [stdout] | [INFO] [stdout] 380 | for (i, ¶m_value) in param_values.iter().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/validation.rs:675:9 [INFO] [stdout] | [INFO] [stdout] 675 | method: &T, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data` [INFO] [stdout] --> src/validation.rs:840:13 [INFO] [stdout] | [INFO] [stdout] 840 | data: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data` [INFO] [stdout] --> src/validation.rs:848:13 [INFO] [stdout] | [INFO] [stdout] 848 | data: &Array2, [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `test` profile [unoptimized + debuginfo] target(s) in 48.80s [INFO] running `Command { std: "docker" "inspect" "b1336a1142ad2558d8d99122f4dbf7b8fbcae09a6802eaa318c41ecaf82274b5", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "b1336a1142ad2558d8d99122f4dbf7b8fbcae09a6802eaa318c41ecaf82274b5", kill_on_drop: false }` [INFO] [stdout] b1336a1142ad2558d8d99122f4dbf7b8fbcae09a6802eaa318c41ecaf82274b5 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5-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@sha256:4848fb76d95f26979359cc7e45710b1dbc8f3acb7aeedee7c460d7702230f228" "/opt/rustwide/cargo-home/bin/cargo" "+c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38" "test" "--frozen", kill_on_drop: false }` [INFO] [stdout] fa4c79740e72cbec61fbbcc432b33f23874cda8a4af74df301ee1ddba3de77bb [INFO] running `Command { std: "docker" "start" "-a" "fa4c79740e72cbec61fbbcc432b33f23874cda8a4af74df301ee1ddba3de77bb", kill_on_drop: false }` [INFO] [stderr] warning: unused doc comment [INFO] [stderr] --> src/plugin_architecture.rs:329:9 [INFO] [stderr] | [INFO] [stderr] 329 | /// PluginMetadata [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^ [INFO] [stderr] 330 | / PluginMetadata { [INFO] [stderr] 331 | | name: "linear_kernel".to_string(), [INFO] [stderr] 332 | | version: "1.0.0".to_string(), [INFO] [stderr] 333 | | description: "Simple linear kernel approximation plugin".to_string(), [INFO] [stderr] ... | [INFO] [stderr] 337 | | optional_parameters: vec!["normalize".to_string()], [INFO] [stderr] 338 | | } [INFO] [stderr] | |_________- rustdoc does not generate documentation for expressions [INFO] [stderr] | [INFO] [stderr] = help: use `//` for a plain comment [INFO] [stderr] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/advanced_testing.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/anisotropic_rbf.rs:29:5 [INFO] [stderr] | [INFO] [stderr] 29 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/benchmarking.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/validation.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/chi2_samplers.rs:5:5 [INFO] [stderr] | [INFO] [stderr] 5 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/computer_vision_kernels.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/type_safety.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/fastfood.rs:11:5 [INFO] [stderr] | [INFO] [stderr] 11 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/type_safe_kernels.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/gpu_acceleration.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `rayon::prelude` [INFO] [stderr] --> src/gradient_kernel_learning.rs:7:5 [INFO] [stderr] | [INFO] [stderr] 7 | use rayon::prelude::*; [INFO] [stderr] | ^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/information_theoretic.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/time_series_kernels.rs:11:5 [INFO] [stderr] | [INFO] [stderr] 11 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `rayon::prelude` [INFO] [stderr] --> src/time_series_kernels.rs:7:5 [INFO] [stderr] | [INFO] [stderr] 7 | use rayon::prelude::*; [INFO] [stderr] | ^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/memory_efficient.rs:12:5 [INFO] [stderr] | [INFO] [stderr] 12 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/multi_scale_rbf.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/nlp_kernels.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/optimal_transport.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Rng` [INFO] [stderr] --> src/out_of_core.rs:11:39 [INFO] [stderr] | [INFO] [stderr] 11 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stderr] | ^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/out_of_core.rs:10:5 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Distribution` [INFO] [stderr] --> src/plugin_architecture.rs:415:35 [INFO] [stderr] | [INFO] [stderr] 415 | use scirs2_core::random::{Distribution, StandardNormal}; [INFO] [stderr] | ^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/polynomial_count_sketch.rs:7:5 [INFO] [stderr] | [INFO] [stderr] 7 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Fft` [INFO] [stderr] --> src/polynomial_count_sketch.rs:3:15 [INFO] [stderr] | [INFO] [stderr] 3 | use rustfft::{Fft, FftPlanner}; [INFO] [stderr] | ^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Rng` [INFO] [stderr] --> src/sparse_gp/mod.rs:26:39 [INFO] [stderr] | [INFO] [stderr] 26 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stderr] | ^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/rbf_sampler.rs:5:5 [INFO] [stderr] | [INFO] [stderr] 5 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/robust_kernels.rs:12:5 [INFO] [stderr] | [INFO] [stderr] 12 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `rayon::prelude` [INFO] [stderr] --> src/robust_kernels.rs:7:5 [INFO] [stderr] | [INFO] [stderr] 7 | use rayon::prelude::*; [INFO] [stderr] | ^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `sklears_core::traits::Fit` [INFO] [stderr] --> src/robust_kernels.rs:15:5 [INFO] [stderr] | [INFO] [stderr] 15 | use sklears_core::traits::Fit; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Rng` [INFO] [stderr] --> src/sparse_gp/approximations.rs:10:39 [INFO] [stderr] | [INFO] [stderr] 10 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stderr] | ^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/sparse_gp/mod.rs:25:5 [INFO] [stderr] | [INFO] [stderr] 25 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/sparse_gp/inference.rs:13:5 [INFO] [stderr] | [INFO] [stderr] 13 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused import: `Rng` [INFO] [stderr] --> src/sparse_gp/inference.rs:14:39 [INFO] [stderr] | [INFO] [stderr] 14 | use scirs2_core::random::{thread_rng, Rng}; [INFO] [stderr] | ^^^ [INFO] [stderr] [INFO] [stderr] warning: unused variable: `gamma` [INFO] [stderr] --> src/adaptive_bandwidth_rbf.rs:490:47 [INFO] [stderr] | [INFO] [stderr] 490 | fn kernel_trace(&self, x: &Array2, gamma: Float) -> Result { [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_gamma` [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/adaptive_bandwidth_rbf.rs:630:14 [INFO] [stderr] | [INFO] [stderr] 630 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_val` [INFO] [stderr] --> src/adaptive_dimension.rs:235:9 [INFO] [stderr] | [INFO] [stderr] 235 | x_val: &Array2, [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_val_transformed` [INFO] [stderr] --> src/adaptive_dimension.rs:237:9 [INFO] [stderr] | [INFO] [stderr] 237 | x_val_transformed: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `fitted_sampler` [INFO] [stderr] --> src/adaptive_dimension.rs:238:9 [INFO] [stderr] | [INFO] [stderr] 238 | fitted_sampler: &crate::rbf_sampler::RBFSampler, [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fitted_sampler` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_train` [INFO] [stderr] --> src/adaptive_dimension.rs:400:9 [INFO] [stderr] | [INFO] [stderr] 400 | x_train: &Array2, [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_train_transformed` [INFO] [stderr] --> src/adaptive_dimension.rs:402:9 [INFO] [stderr] | [INFO] [stderr] 402 | x_train_transformed: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iter` [INFO] [stderr] --> src/anisotropic_rbf.rs:132:13 [INFO] [stderr] | [INFO] [stderr] 132 | for iter in 0..self.max_iter { [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `k_inv_sqrt` [INFO] [stderr] --> src/anisotropic_rbf.rs:195:13 [INFO] [stderr] | [INFO] [stderr] 195 | let k_inv_sqrt = u.dot(&s_inv_diag).dot(&vt); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_inv_sqrt` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `vt` [INFO] [stderr] --> src/anisotropic_rbf.rs:662:20 [INFO] [stderr] | [INFO] [stderr] 662 | let (u, s, vt) = precision.svd(true, true).map_err(|e| { [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_vt` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `method_name` [INFO] [stderr] --> src/benchmarking.rs:391:13 [INFO] [stderr] | [INFO] [stderr] 391 | let method_name = method.method_name(); [INFO] [stderr] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_method_name` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `fit_start` [INFO] [stderr] --> src/benchmarking.rs:440:13 [INFO] [stderr] | [INFO] [stderr] 440 | let fit_start = Instant::now(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fit_start` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `start_time` [INFO] [stderr] --> src/budget_constrained.rs:193:13 [INFO] [stderr] | [INFO] [stderr] 193 | let start_time = Instant::now(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `config_start` [INFO] [stderr] --> src/budget_constrained.rs:214:17 [INFO] [stderr] | [INFO] [stderr] 214 | let config_start = Instant::now(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_train_transformed` [INFO] [stderr] --> src/budget_constrained.rs:240:21 [INFO] [stderr] | [INFO] [stderr] 240 | let x_train_transformed = fitted.transform(&x_train)?; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `current_quality` [INFO] [stderr] --> src/budget_constrained.rs:375:9 [INFO] [stderr] | [INFO] [stderr] 375 | current_quality: f64, [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_quality` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `start_time` [INFO] [stderr] --> src/budget_constrained.rs:493:13 [INFO] [stderr] | [INFO] [stderr] 493 | let start_time = Instant::now(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `config_start` [INFO] [stderr] --> src/budget_constrained.rs:504:17 [INFO] [stderr] | [INFO] [stderr] 504 | let config_start = Instant::now(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_config_start` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/computer_vision_kernels.rs:120:18 [INFO] [stderr] | [INFO] [stderr] 120 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/computer_vision_kernels.rs:420:18 [INFO] [stderr] | [INFO] [stderr] 420 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `ix` [INFO] [stderr] --> src/computer_vision_kernels.rs:648:21 [INFO] [stderr] | [INFO] [stderr] 648 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iy` [INFO] [stderr] --> src/computer_vision_kernels.rs:649:21 [INFO] [stderr] | [INFO] [stderr] 649 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `ix` [INFO] [stderr] --> src/computer_vision_kernels.rs:749:21 [INFO] [stderr] | [INFO] [stderr] 749 | let ix = (image[[i, j + 1]] - image[[i, j - 1]]) / 2.0; [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_ix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iy` [INFO] [stderr] --> src/computer_vision_kernels.rs:750:21 [INFO] [stderr] | [INFO] [stderr] 750 | let iy = (image[[i + 1, j]] - image[[i - 1, j]]) / 2.0; [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_iy` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/computer_vision_kernels.rs:945:18 [INFO] [stderr] | [INFO] [stderr] 945 | fn fit(self, x: &Array2, _y: &()) -> Result { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_transformed` [INFO] [stderr] --> src/cross_validation.rs:685:27 [INFO] [stderr] | [INFO] [stderr] 685 | fn compute_mse(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_transformed` [INFO] [stderr] --> src/cross_validation.rs:693:27 [INFO] [stderr] | [INFO] [stderr] 693 | fn compute_mae(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_transformed` [INFO] [stderr] --> src/cross_validation.rs:700:32 [INFO] [stderr] | [INFO] [stderr] 700 | fn compute_r2_score(&self, x_transformed: &Array2, y: &Array1) -> Result { [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_transformed` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/custom_kernel.rs:387:14 [INFO] [stderr] | [INFO] [stderr] 387 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/distributed_kernel.rs:448:14 [INFO] [stderr] | [INFO] [stderr] 448 | let (n_samples, _) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/ensemble_nystroem.rs:160:9 [INFO] [stderr] | [INFO] [stderr] 160 | x: &Array2, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/ensemble_nystroem.rs:409:9 [INFO] [stderr] | [INFO] [stderr] 409 | x: &Array2, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/error_bounded.rs:125:13 [INFO] [stderr] | [INFO] [stderr] 125 | let n_features = x.ncols(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_test` [INFO] [stderr] --> src/error_bounded.rs:132:13 [INFO] [stderr] | [INFO] [stderr] 132 | let x_test = x [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/error_bounded.rs:217:9 [INFO] [stderr] | [INFO] [stderr] 217 | x: &Array2, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_components` [INFO] [stderr] --> src/error_bounded.rs:364:9 [INFO] [stderr] | [INFO] [stderr] 364 | n_components: usize, [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/error_bounded.rs:517:13 [INFO] [stderr] | [INFO] [stderr] 517 | let n_samples = x.nrows(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_components` [INFO] [stderr] --> src/error_bounded.rs:585:57 [INFO] [stderr] | [INFO] [stderr] 585 | fn compute_error_bound(&self, trial_errors: &[f64], n_components: usize) -> Result { [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `block_end` [INFO] [stderr] --> src/fastfood.rs:274:17 [INFO] [stderr] | [INFO] [stderr] 274 | let block_end = block_start + padded_dim; [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_block_end` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `ctx` [INFO] [stderr] --> src/gpu_acceleration.rs:1002:9 [INFO] [stderr] | [INFO] [stderr] 1002 | ctx: &GpuContext, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_ctx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/gradient_kernel_learning.rs:215:13 [INFO] [stderr] | [INFO] [stderr] 215 | let n_samples = x.nrows(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `param_idx` [INFO] [stderr] --> src/gradient_kernel_learning.rs:620:13 [INFO] [stderr] | [INFO] [stderr] 620 | for param_idx in 1..self.parameters.len() { [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_train` [INFO] [stderr] --> src/gradient_kernel_learning.rs:698:9 [INFO] [stderr] | [INFO] [stderr] 698 | x_train: &Array2, [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y_train` [INFO] [stderr] --> src/gradient_kernel_learning.rs:699:9 [INFO] [stderr] | [INFO] [stderr] 699 | y_train: &Array1, [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x_val` [INFO] [stderr] --> src/gradient_kernel_learning.rs:700:9 [INFO] [stderr] | [INFO] [stderr] 700 | x_val: &Array2, [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_val` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y_val` [INFO] [stderr] --> src/gradient_kernel_learning.rs:701:9 [INFO] [stderr] | [INFO] [stderr] 701 | y_val: &Array1, [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_y_val` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_matrix` [INFO] [stderr] --> src/gradient_kernel_learning.rs:717:9 [INFO] [stderr] | [INFO] [stderr] 717 | kernel_matrix: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/gradient_kernel_learning.rs:718:9 [INFO] [stderr] | [INFO] [stderr] 718 | y: &Array1, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_matrix` [INFO] [stderr] --> src/gradient_kernel_learning.rs:727:9 [INFO] [stderr] | [INFO] [stderr] 727 | kernel_matrix: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/gradient_kernel_learning.rs:728:9 [INFO] [stderr] | [INFO] [stderr] 728 | y: &Array1, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_derivative` [INFO] [stderr] --> src/gradient_kernel_learning.rs:729:9 [INFO] [stderr] | [INFO] [stderr] 729 | kernel_derivative: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_matrix` [INFO] [stderr] --> src/gradient_kernel_learning.rs:738:9 [INFO] [stderr] | [INFO] [stderr] 738 | kernel_matrix: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/gradient_kernel_learning.rs:739:9 [INFO] [stderr] | [INFO] [stderr] 739 | y: &Array1, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_matrix` [INFO] [stderr] --> src/gradient_kernel_learning.rs:748:9 [INFO] [stderr] | [INFO] [stderr] 748 | kernel_matrix: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/gradient_kernel_learning.rs:749:9 [INFO] [stderr] | [INFO] [stderr] 749 | y: &Array1, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_derivative` [INFO] [stderr] --> src/gradient_kernel_learning.rs:750:9 [INFO] [stderr] | [INFO] [stderr] 750 | kernel_derivative: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x1` [INFO] [stderr] --> src/gradient_kernel_learning.rs:757:27 [INFO] [stderr] | [INFO] [stderr] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x2` [INFO] [stderr] --> src/gradient_kernel_learning.rs:757:49 [INFO] [stderr] | [INFO] [stderr] 757 | fn compute_mmd(&self, x1: &ArrayView2, x2: &ArrayView2) -> Result { [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x1` [INFO] [stderr] --> src/gradient_kernel_learning.rs:765:9 [INFO] [stderr] | [INFO] [stderr] 765 | x1: &ArrayView2, [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_x1` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x2` [INFO] [stderr] --> src/gradient_kernel_learning.rs:766:9 [INFO] [stderr] | [INFO] [stderr] 766 | x2: &ArrayView2, [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_x2` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_matrix` [INFO] [stderr] --> src/gradient_kernel_learning.rs:803:9 [INFO] [stderr] | [INFO] [stderr] 803 | kernel_matrix: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `target_kernel` [INFO] [stderr] --> src/gradient_kernel_learning.rs:804:9 [INFO] [stderr] | [INFO] [stderr] 804 | target_kernel: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_target_kernel` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel_derivative` [INFO] [stderr] --> src/gradient_kernel_learning.rs:805:9 [INFO] [stderr] | [INFO] [stderr] 805 | kernel_derivative: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel_derivative` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/gradient_kernel_learning.rs:860:9 [INFO] [stderr] | [INFO] [stderr] 860 | x: &Array2, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/gradient_kernel_learning.rs:861:9 [INFO] [stderr] | [INFO] [stderr] 861 | y: Option<&Array1>, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/incremental_nystroem.rs:129:25 [INFO] [stderr] | [INFO] [stderr] 129 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `rng` [INFO] [stderr] --> src/incremental_nystroem.rs:280:9 [INFO] [stderr] | [INFO] [stderr] 280 | rng: &mut RealStdRng, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `rng` [INFO] [stderr] --> src/incremental_nystroem.rs:655:9 [INFO] [stderr] | [INFO] [stderr] 655 | rng: &mut RealStdRng, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `current_components` [INFO] [stderr] --> src/incremental_nystroem.rs:898:13 [INFO] [stderr] | [INFO] [stderr] 898 | let current_components = self.components_.as_ref().unwrap(); [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `current_normalization` [INFO] [stderr] --> src/incremental_nystroem.rs:899:13 [INFO] [stderr] | [INFO] [stderr] 899 | let current_normalization = self.normalization_.as_ref().unwrap(); [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_current_normalization` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `new_components` [INFO] [stderr] --> src/incremental_nystroem.rs:915:14 [INFO] [stderr] | [INFO] [stderr] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `new_normalization` [INFO] [stderr] --> src/incremental_nystroem.rs:915:30 [INFO] [stderr] | [INFO] [stderr] 915 | let (new_components, new_normalization) = self.compute_decomposition(new_kernel_matrix)?; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_normalization` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `components` [INFO] [stderr] --> src/incremental_nystroem.rs:1319:13 [INFO] [stderr] | [INFO] [stderr] 1319 | let components = self [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/information_theoretic.rs:77:14 [INFO] [stderr] | [INFO] [stderr] 77 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iteration` [INFO] [stderr] --> src/information_theoretic.rs:490:13 [INFO] [stderr] | [INFO] [stderr] 490 | for iteration in 0..self.max_iterations { [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `cluster_centers` [INFO] [stderr] --> src/information_theoretic.rs:588:9 [INFO] [stderr] | [INFO] [stderr] 588 | cluster_centers: &Array2, [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cluster_centers` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `normal` [INFO] [stderr] --> src/information_theoretic.rs:756:9 [INFO] [stderr] | [INFO] [stderr] 756 | let normal = RandNormal::new(mean, std).unwrap(); [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_normal` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/kernel_ridge_regression/basic_regression.rs:182:14 [INFO] [stderr] | [INFO] [stderr] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/kernel_ridge_regression/basic_regression.rs:182:25 [INFO] [stderr] | [INFO] [stderr] 182 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/kernel_ridge_regression/basic_regression.rs:251:14 [INFO] [stderr] | [INFO] [stderr] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/kernel_ridge_regression/basic_regression.rs:251:25 [INFO] [stderr] | [INFO] [stderr] 251 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/kernel_ridge_regression/basic_regression.rs:284:14 [INFO] [stderr] | [INFO] [stderr] 284 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/kernel_ridge_regression/multitask_regression.rs:179:13 [INFO] [stderr] | [INFO] [stderr] 179 | let n_samples = x.nrows(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/kernel_ridge_regression/multitask_regression.rs:185:13 [INFO] [stderr] | [INFO] [stderr] 185 | let n_features = x_transformed.ncols(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/memory_efficient.rs:90:13 [INFO] [stderr] | [INFO] [stderr] 90 | let n_features = x.ncols(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/multi_kernel_learning.rs:255:14 [INFO] [stderr] | [INFO] [stderr] 255 | let (n_samples, _) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/multi_kernel_learning.rs:317:14 [INFO] [stderr] | [INFO] [stderr] 317 | for (i, (base_kernel, &weight)) in self.base_kernels.iter().zip(weights.iter()).enumerate() [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n` [INFO] [stderr] --> src/multi_kernel_learning.rs:686:17 [INFO] [stderr] | [INFO] [stderr] 686 | let n = kernel.nrows() as f64; [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/multi_kernel_learning.rs:726:14 [INFO] [stderr] | [INFO] [stderr] 726 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/multi_kernel_learning.rs:757:14 [INFO] [stderr] | [INFO] [stderr] 757 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/multi_scale_rbf.rs:247:25 [INFO] [stderr] | [INFO] [stderr] 247 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `gammas` [INFO] [stderr] --> src/multi_scale_rbf.rs:403:13 [INFO] [stderr] | [INFO] [stderr] 403 | let gammas = self [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_gammas` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/multi_scale_rbf.rs:424:14 [INFO] [stderr] | [INFO] [stderr] 424 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/numerical_stability.rs:696:14 [INFO] [stderr] | [INFO] [stderr] 696 | let (n1, n_features) = data1.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `rng` [INFO] [stderr] --> src/nystroem.rs:294:9 [INFO] [stderr] | [INFO] [stderr] 294 | rng: &mut RealStdRng, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_valid` [INFO] [stderr] --> src/nystroem.rs:558:13 [INFO] [stderr] | [INFO] [stderr] 558 | let n_valid = valid_indices.len(); [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_valid` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/optimal_transport.rs:526:13 [INFO] [stderr] | [INFO] [stderr] 526 | let n_samples = x.nrows(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `local_idx` [INFO] [stderr] --> src/out_of_core.rs:419:18 [INFO] [stderr] | [INFO] [stderr] 419 | for (local_idx, row) in chunk.axis_iter(Axis(0)).enumerate() { [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_local_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `best_score` [INFO] [stderr] --> src/parameter_learning.rs:908:13 [INFO] [stderr] | [INFO] [stderr] 908 | let best_score = parameter_history [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_best_score` [INFO] [stderr] [INFO] [stderr] warning: value assigned to `converged` is never read [INFO] [stderr] --> src/progressive.rs:221:29 [INFO] [stderr] | [INFO] [stderr] 221 | let mut converged = false; [INFO] [stderr] | ^^^^^ [INFO] [stderr] | [INFO] [stderr] = help: maybe it is overwritten before being read? [INFO] [stderr] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/progressive.rs:366:9 [INFO] [stderr] | [INFO] [stderr] 366 | x: &Array2, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: value assigned to `converged` is never read [INFO] [stderr] --> src/progressive.rs:675:29 [INFO] [stderr] | [INFO] [stderr] 675 | let mut converged = false; [INFO] [stderr] | ^^^^^ [INFO] [stderr] | [INFO] [stderr] = help: maybe it is overwritten before being read? [INFO] [stderr] [INFO] [stderr] warning: unused variable: `improvement` [INFO] [stderr] --> src/progressive.rs:788:9 [INFO] [stderr] | [INFO] [stderr] 788 | improvement: f64, [INFO] [stderr] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_improvement` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `components` [INFO] [stderr] --> src/progressive.rs:790:9 [INFO] [stderr] | [INFO] [stderr] 790 | components: usize, [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_components` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/quasi_random_features.rs:193:14 [INFO] [stderr] | [INFO] [stderr] 193 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/rbf_sampler.rs:147:14 [INFO] [stderr] | [INFO] [stderr] 147 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/rbf_sampler.rs:313:14 [INFO] [stderr] | [INFO] [stderr] 313 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/rbf_sampler.rs:517:14 [INFO] [stderr] | [INFO] [stderr] 517 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/rbf_sampler.rs:695:14 [INFO] [stderr] | [INFO] [stderr] 695 | let (n_samples, n_features) = x.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `mean` [INFO] [stderr] --> src/robust_kernels.rs:231:18 [INFO] [stderr] | [INFO] [stderr] 231 | let (mean, cov) = self.compute_robust_statistics(&subset_data); [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iteration` [INFO] [stderr] --> src/robust_kernels.rs:364:17 [INFO] [stderr] | [INFO] [stderr] 364 | for iteration in 0..self.config.max_iterations { [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `index` [INFO] [stderr] --> src/robust_kernels.rs:395:58 [INFO] [stderr] | [INFO] [stderr] 395 | fn compute_residual(&self, sample: &ArrayView1, index: usize) -> f64 { [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_index` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `cov` [INFO] [stderr] --> src/robust_kernels.rs:476:9 [INFO] [stderr] | [INFO] [stderr] 476 | cov: &Array2, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `delta` [INFO] [stderr] --> src/robust_kernels.rs:492:53 [INFO] [stderr] | [INFO] [stderr] 492 | fn compute_huber_center(&self, x: &Array2, delta: f64) -> Array1 { [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `delta` [INFO] [stderr] --> src/robust_kernels.rs:498:74 [INFO] [stderr] | [INFO] [stderr] 498 | fn compute_huber_scale(&self, x: &Array2, center: &Array1, delta: f64) -> f64 { [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `delta` [INFO] [stderr] --> src/robust_kernels.rs:516:9 [INFO] [stderr] | [INFO] [stderr] 516 | delta: f64, [INFO] [stderr] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_delta` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `c` [INFO] [stderr] --> src/robust_kernels.rs:522:53 [INFO] [stderr] | [INFO] [stderr] 522 | fn compute_tukey_center(&self, x: &Array2, c: f64) -> Array1 { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `c` [INFO] [stderr] --> src/robust_kernels.rs:528:74 [INFO] [stderr] | [INFO] [stderr] 528 | fn compute_tukey_scale(&self, x: &Array2, center: &Array1, c: f64) -> f64 { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `c` [INFO] [stderr] --> src/robust_kernels.rs:546:9 [INFO] [stderr] | [INFO] [stderr] 546 | c: f64, [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_c` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `basis_idx` [INFO] [stderr] --> src/robust_kernels.rs:757:22 [INFO] [stderr] | [INFO] [stderr] 757 | for (j, &basis_idx) in indices.iter().enumerate() { [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_basis_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `cov` [INFO] [stderr] --> src/robust_kernels.rs:916:20 [INFO] [stderr] | [INFO] [stderr] 916 | let (mean, cov) = self.compute_robust_statistics(x); [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/robust_kernels.rs:968:39 [INFO] [stderr] | [INFO] [stderr] 968 | fn compute_robust_estimate(&self, x: &Array2, y: &Array1) -> Result { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `k_nm` [INFO] [stderr] --> src/sparse_gp/approximations.rs:329:13 [INFO] [stderr] | [INFO] [stderr] 329 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n` [INFO] [stderr] --> src/sparse_gp/approximations.rs:354:13 [INFO] [stderr] | [INFO] [stderr] 354 | let n = x.nrows(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `m` [INFO] [stderr] --> src/sparse_gp/approximations.rs:355:13 [INFO] [stderr] | [INFO] [stderr] 355 | let m = inducing_points.nrows(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `m` [INFO] [stderr] --> src/sparse_gp/approximations.rs:405:13 [INFO] [stderr] | [INFO] [stderr] 405 | let m = inducing_points.nrows(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `k_nm` [INFO] [stderr] --> src/sparse_gp/approximations.rs:414:13 [INFO] [stderr] | [INFO] [stderr] 414 | let k_nm = kernel.kernel_matrix(x, inducing_points); [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `kernel` [INFO] [stderr] --> src/sparse_gp/approximations.rs:482:9 [INFO] [stderr] | [INFO] [stderr] 482 | kernel: &K, [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_kernel` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iter` [INFO] [stderr] --> src/sparse_gp/inference.rs:144:13 [INFO] [stderr] | [INFO] [stderr] 144 | for iter in 0..max_iter { [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/sparse_gp/ski.rs:99:13 [INFO] [stderr] | [INFO] [stderr] 99 | let n_features = x.ncols(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `y` [INFO] [stderr] --> src/sparse_gp/ski.rs:428:47 [INFO] [stderr] | [INFO] [stderr] 428 | pub fn fit_tensor(&self, x: &Array2, y: &Array1) -> Result> { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n` [INFO] [stderr] --> src/sparse_gp/variational.rs:30:13 [INFO] [stderr] | [INFO] [stderr] 30 | let n = x.nrows(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `iter` [INFO] [stderr] --> src/sparse_gp/variational.rs:48:13 [INFO] [stderr] | [INFO] [stderr] 48 | for iter in 0..max_iter { [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n` [INFO] [stderr] --> src/sparse_gp/variational.rs:136:13 [INFO] [stderr] | [INFO] [stderr] 136 | let n = y.len(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `m` [INFO] [stderr] --> src/sparse_gp/variational.rs:137:13 [INFO] [stderr] | [INFO] [stderr] 137 | let m = variational_mean.len(); [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_m` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `k_nm` [INFO] [stderr] --> src/sparse_gp/variational.rs:311:9 [INFO] [stderr] | [INFO] [stderr] 311 | k_nm: &Array2, [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_k_nm` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `noise_variance` [INFO] [stderr] --> src/sparse_gp/variational.rs:314:9 [INFO] [stderr] | [INFO] [stderr] 314 | noise_variance: f64, [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_noise_variance` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `variational_cov` [INFO] [stderr] --> src/sparse_gp/variational.rs:425:13 [INFO] [stderr] | [INFO] [stderr] 425 | let variational_cov = variational_cov_factor.dot(&variational_cov_factor.t()); [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_cov` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `k_mm_inv` [INFO] [stderr] --> src/sparse_gp/variational.rs:506:13 [INFO] [stderr] | [INFO] [stderr] 506 | let k_mm_inv = KernelOps::invert_using_cholesky(&k_mm)?; [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_k_mm_inv` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_timepoints` [INFO] [stderr] --> src/time_series_kernels.rs:411:24 [INFO] [stderr] | [INFO] [stderr] 411 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `ar_coefficients` [INFO] [stderr] --> src/time_series_kernels.rs:434:13 [INFO] [stderr] | [INFO] [stderr] 434 | let ar_coefficients = self.ar_coefficients.as_ref().ok_or("Model not fitted")?; [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ar_coefficients` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_timepoints` [INFO] [stderr] --> src/time_series_kernels.rs:440:24 [INFO] [stderr] | [INFO] [stderr] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/time_series_kernels.rs:440:38 [INFO] [stderr] | [INFO] [stderr] 440 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_timepoints` [INFO] [stderr] --> src/time_series_kernels.rs:589:24 [INFO] [stderr] | [INFO] [stderr] 589 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_timepoints` [INFO] [stderr] --> src/time_series_kernels.rs:619:24 [INFO] [stderr] | [INFO] [stderr] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_timepoints` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/time_series_kernels.rs:619:38 [INFO] [stderr] | [INFO] [stderr] 619 | let (n_series, n_timepoints, n_features) = time_series.dim(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `u2` [INFO] [stderr] --> src/type_safe_kernels.rs:368:29 [INFO] [stderr] | [INFO] [stderr] 368 | let u2: f64 = rng.gen(); [INFO] [stderr] | ^^ help: if this is intentional, prefix it with an underscore: `_u2` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/validation.rs:380:18 [INFO] [stderr] | [INFO] [stderr] 380 | for (i, ¶m_value) in param_values.iter().enumerate() { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `method` [INFO] [stderr] --> src/validation.rs:675:9 [INFO] [stderr] | [INFO] [stderr] 675 | method: &T, [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stderr] [INFO] [stderr] warning: unused import: `sklears_core::traits::Fit` [INFO] [stderr] --> src/robust_kernels.rs:15:5 [INFO] [stderr] | [INFO] [stderr] 15 | use sklears_core::traits::Fit; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stderr] --> src/advanced_testing.rs:9:5 [INFO] [stderr] | [INFO] [stderr] 9 | use scirs2_core::random::Distribution; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused variable: `data` [INFO] [stderr] --> src/benchmarking.rs:901:13 [INFO] [stderr] | [INFO] [stderr] 901 | data: &Array2, [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `x` [INFO] [stderr] --> src/sparse_gp/ski.rs:631:13 [INFO] [stderr] | [INFO] [stderr] 631 | let x = array![[0.0, 0.0], [1.0, 1.0]]; [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `drift_detected` [INFO] [stderr] --> src/streaming_kernel.rs:970:13 [INFO] [stderr] | [INFO] [stderr] 970 | let drift_detected = sampler.detect_drift(&x2).unwrap(); [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_drift_detected` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `fast_config` [INFO] [stderr] --> src/type_safety.rs:1737:13 [INFO] [stderr] | [INFO] [stderr] 1737 | let fast_config = KernelPresets::fast_rbf_128(); [INFO] [stderr] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fast_config` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `balanced_config` [INFO] [stderr] --> src/type_safety.rs:1743:13 [INFO] [stderr] | [INFO] [stderr] 1743 | let balanced_config = KernelPresets::balanced_rbf_256(); [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_balanced_config` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `accurate_config` [INFO] [stderr] --> src/type_safety.rs:1749:13 [INFO] [stderr] | [INFO] [stderr] 1749 | let accurate_config = KernelPresets::accurate_rbf_512(); [INFO] [stderr] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_accurate_config` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `data` [INFO] [stderr] --> src/validation.rs:840:13 [INFO] [stderr] | [INFO] [stderr] 840 | data: &Array2, [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `data` [INFO] [stderr] --> src/validation.rs:848:13 [INFO] [stderr] | [INFO] [stderr] 848 | data: &Array2, [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_data` [INFO] [stderr] [INFO] [stderr] warning: `sklears-kernel-approximation` (lib) generated 182 warnings (run `cargo fix --lib -p sklears-kernel-approximation` to apply 147 suggestions) [INFO] [stderr] warning: `sklears-kernel-approximation` (lib test) generated 190 warnings (180 duplicates) (run `cargo fix --lib -p sklears-kernel-approximation --tests` to apply 8 suggestions) [INFO] [stderr] Finished `test` profile [unoptimized + debuginfo] target(s) in 0.41s [INFO] [stderr] Running unittests src/lib.rs (/opt/rustwide/target/debug/deps/sklears_kernel_approximation-59e97b6f53cf1af9) [INFO] [stdout] [INFO] [stdout] running 429 tests [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_error_handling ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_cross_validation_strategy ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_different_objective_functions ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_adaptive_bandwidth_rbf_sampler_basic ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_gamma_range ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_median_heuristic ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_single_sample ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_reproducibility ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_scott_rule ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_different_bandwidth_strategies ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_basic ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_rank_based ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_error_tolerance ... ok [INFO] [stdout] test adaptive_dimension::tests::test_quality_metrics ... ok [INFO] [stdout] test advanced_testing::tests::test_quality_assessment ... ok [INFO] [stdout] test adaptive_dimension::tests::test_dimension_selection_quality_efficiency ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_invalid_parameters ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_silverman_rule ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_anisotropic_rbf_reproducibility ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_anisotropic_rbf_sampler ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_mahalanobis_rbf_sampler ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_robust_anisotropic_rbf_huber ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_approximation_rank ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_reproducibility ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_different_error_bounds ... ok [INFO] [stdout] test adaptive_nystroem::tests::test_adaptive_nystroem_eigenvalue_decay ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_length_scale_learning ... ok [INFO] [stdout] test benchmarking::tests::test_csv_export ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_robust_anisotropic_rbf_mcd ... ok [INFO] [stdout] test budget_constrained::tests::test_budget_usage_tracking ... ok [INFO] [stdout] test adaptive_dimension::tests::test_dimension_selection_error_tolerance ... ok [INFO] [stdout] test budget_constrained::tests::test_budget_constraint_types ... ok [INFO] [stdout] test budget_constrained::tests::test_budget_constrained_rbf_sampler ... ok [INFO] [stdout] test chi2_samplers::tests::test_additive_chi2_sampler_basic ... ok [INFO] [stdout] test chi2_samplers::tests::test_additive_chi2_sampler_negative_input ... ok [INFO] [stdout] test chi2_samplers::tests::test_skewed_chi2_sampler_basic ... ok [INFO] [stdout] test budget_constrained::tests::test_early_stopping ... ok [INFO] [stdout] test chi2_samplers::tests::test_skewed_chi2_sampler_input_validation ... ok [INFO] [stdout] test chi2_samplers::tests::test_skewed_chi2_sampler_invalid_skewedness ... ok [INFO] [stdout] test benchmarking::tests::test_benchmark_dataset_creation ... ok [INFO] [stdout] test computer_vision_kernels::tests::test_spatial_pyramid_features ... ok [INFO] [stdout] test computer_vision_kernels::tests::test_convolutional_kernel_features ... ok [INFO] [stdout] test computer_vision_kernels::tests::test_scale_invariant_features ... ok [INFO] [stdout] test cross_validation::tests::test_cross_validation_result_aggregation ... ok [INFO] [stdout] test budget_constrained::tests::test_optimization_strategies ... ok [INFO] [stdout] test adaptive_dimension::tests::test_dimension_selection_result ... ok [INFO] [stdout] test computer_vision_kernels::tests::test_texture_kernel_approximation ... ok [INFO] [stdout] test cross_validation::tests::test_cross_validation_with_targets ... ok [INFO] [stdout] test budget_constrained::tests::test_reproducibility ... ok [INFO] [stdout] test cross_validation::tests::test_cv_splitter_consistency ... ok [INFO] [stdout] test cross_validation::tests::test_kfold_splitter ... ok [INFO] [stdout] test cross_validation::tests::test_monte_carlo_splitter ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_kernel_feature_mismatch ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_kernel_sampler_basic ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_kernel_sampler_different_kernels ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_kernel_sampler_reproducibility ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_kernel_zero_components ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_laplacian_kernel ... ok [INFO] [stdout] test cross_validation::tests::test_time_series_splitter ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_polynomial_kernel ... ok [INFO] [stdout] test custom_kernel::tests::test_custom_rbf_kernel ... ok [INFO] [stdout] test custom_kernel::tests::test_exact_kernel_matrix_computation ... ok [INFO] [stdout] test distributed_kernel::tests::test_distributed_nystroem_basic ... ok [INFO] [stdout] test distributed_kernel::tests::test_distributed_config ... ok [INFO] [stdout] test advanced_testing::tests::test_error_bounds_validator ... ok [INFO] [stdout] test distributed_kernel::tests::test_partition_strategies ... ok [INFO] [stdout] test distributed_kernel::tests::test_distributed_rbf_sampler_basic ... ok [INFO] [stdout] test distributed_kernel::tests::test_worker_stats ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_average ... ok [INFO] [stdout] test anisotropic_rbf::tests::test_anisotropic_rbf_learned_scales ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_basic ... ok [INFO] [stdout] test distributed_kernel::tests::test_worker_initialization ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_concatenate ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_best_approximation ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_custom_strategies ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_invalid_parameters ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_quality_metrics ... ok [INFO] [stdout] test distributed_kernel::tests::test_reproducibility ... ok [INFO] [stdout] test distributed_kernel::tests::test_different_worker_counts ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_weighted_average ... ok [INFO] [stdout] test ensemble_nystroem::tests::test_ensemble_nystroem_reproducibility ... ok [INFO] [stdout] test cross_validation::tests::test_grid_search_cv ... ok [INFO] [stdout] test cross_validation::tests::test_cross_validator_rbf ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_different_gamma ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_edge_cases ... ok [INFO] [stdout] test error_bounded::tests::test_bound_satisfaction ... ok [INFO] [stdout] test advanced_testing::tests::test_convergence_analyzer ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_kernel_rbf ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_reproducibility ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_large_dimensions ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_single_sample ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_transform_power_of_2 ... ok [INFO] [stdout] test fastfood::tests::test_next_power_of_2 ... ok [INFO] [stdout] test gpu_acceleration::tests::test_gpu_context_initialization ... ok [INFO] [stdout] test adaptive_dimension::tests::test_adaptive_sampler_reproducibility ... ok [INFO] [stdout] test fastfood::tests::test_fastfood_transform_basic ... ok [INFO] [stdout] test gpu_acceleration::tests::test_gpu_profiler ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_gradient_config ... ok [INFO] [stdout] test gpu_acceleration::tests::test_gpu_rbf_sampler ... ok [INFO] [stdout] test adaptive_dimension::tests::test_dimension_selection_elbow_method ... ok [INFO] [stdout] test cross_validation::tests::test_cross_validator_nystroem ... ok [INFO] [stdout] test gpu_acceleration::tests::test_gpu_nystroem ... ok [INFO] [stdout] test adaptive_dimension::tests::test_adaptive_rbf_sampler_basic ... ok [INFO] [stdout] test graph_kernels::tests::test_graph_creation ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_parameter_bounds ... ok [INFO] [stdout] test graph_kernels::tests::test_graph_with_labels ... ok [INFO] [stdout] test graph_kernels::tests::test_shortest_path_computation ... ok [INFO] [stdout] test graph_kernels::tests::test_shortest_path_kernel ... ok [INFO] [stdout] test benchmarking::tests::test_benchmark_summary ... ok [INFO] [stdout] test error_bounded::tests::test_reproducibility ... ok [INFO] [stdout] test graph_kernels::tests::test_subgraph_connectivity ... ok [INFO] [stdout] test graph_kernels::tests::test_random_walk_kernel ... ok [INFO] [stdout] test graph_kernels::tests::test_weisfeiler_lehman_kernel ... ok [INFO] [stdout] test graph_kernels::tests::test_subgraph_kernel ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_count_terms ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_degree_1 ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_interaction_high_degree ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_degree_3 ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_feature_mismatch ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_interaction_only ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_l1_normalization ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_multinomial_coefficients ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_single_feature ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_standard_normalization ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_zero_degree ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_l2_normalization ... ok [INFO] [stdout] test benchmarking::tests::test_benchmark_execution ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_adaptive_learning_rate ... ok [INFO] [stdout] test homogeneous_polynomial::tests::test_homogeneous_polynomial_basic ... ok [INFO] [stdout] test incremental_nystroem::tests::test_sliding_window_update ... ok [INFO] [stdout] test incremental_nystroem::tests::test_different_kernels ... ok [INFO] [stdout] test incremental_nystroem::tests::test_incremental_transform ... ok [INFO] [stdout] test information_theoretic::tests::test_entropy_computation ... ok [INFO] [stdout] test information_theoretic::tests::test_entropy_feature_selector ... ok [INFO] [stdout] test incremental_nystroem::tests::test_min_update_size ... ok [INFO] [stdout] test information_theoretic::tests::test_information_bottleneck_extractor ... ok [INFO] [stdout] test information_theoretic::tests::test_mutual_information_computation ... ok [INFO] [stdout] test information_theoretic::tests::test_kl_divergence_kernel ... ok [INFO] [stdout] test information_theoretic::tests::test_mutual_information_kernel ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_kernel_ridge_regression_fastfood ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_kernel_ridge_regression_rff ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_online_kernel_ridge_regression ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_reproducibility ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_kernel_ridge_regression_nystroem ... ok [INFO] [stdout] test kernel_ridge_regression::core_types::tests::test_approximation_method_accessors ... ok [INFO] [stdout] test kernel_ridge_regression::core_types::tests::test_ridge_config_builder ... ok [INFO] [stdout] test incremental_nystroem::tests::test_reproducibility ... ok [INFO] [stdout] test kernel_ridge_regression::core_types::tests::test_validation_functions ... ok [INFO] [stdout] test kernel_ridge_regression::basic_regression::tests::test_different_solvers ... ok [INFO] [stdout] test kernel_ridge_regression::core_types::tests::test_solver_properties ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_multitask_different_solvers ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_multitask_kernel_ridge_regression ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_multitask_reproducibility ... ok [INFO] [stdout] test incremental_nystroem::tests::test_incremental_nystroem_basic ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_multitask_with_regularization ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_convergence ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_task_regularization_penalties ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_custom_robust_loss ... ok [INFO] [stdout] test kernel_ridge_regression::multitask_regression::tests::test_multitask_single_task ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_gradient_kernel_learner ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_loss_edge_cases ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_loss_functions ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_different_robust_losses ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_outlier_detection ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_reproducibility ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_config ... ok [INFO] [stdout] test kernel_ridge_regression::robust_regression::tests::test_robust_kernel_ridge_regression ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_efficient_rbf_chunked_parallel ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_combination_strategies ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_important_kernels ... ok [INFO] [stdout] test memory_efficient::tests::test_reproducibility ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_base_kernel_evaluation ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_monitor ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_kernel_names ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_kernel_statistics ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_mkl_config ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_transform_compatibility ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_supervised_vs_unsupervised ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_adaptive_bandwidth ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_efficient_rbf_sampler ... ok [INFO] [stdout] test multi_kernel_learning::tests::test_multiple_kernel_learning_basic ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_different_combination_strategies ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_different_bandwidth_strategies ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_error_handling ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_multi_scale_rbf_sampler_basic ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_reproducibility ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_manual_gammas ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_scale_weights ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_single_scale ... ok [INFO] [stdout] test multi_scale_rbf::tests::test_gamma_computation_strategies ... ok [INFO] [stdout] test numerical_stability::tests::test_condition_number_monitoring ... ok [INFO] [stdout] test numerical_stability::tests::test_stability_monitor_creation ... ok [INFO] [stdout] test numerical_stability::tests::test_stability_report ... ok [INFO] [stdout] test nlp_kernels::tests::test_text_kernel_approximation ... ok [INFO] [stdout] test nlp_kernels::tests::test_document_kernel_approximation ... ok [INFO] [stdout] test nlp_kernels::tests::test_syntactic_kernel_approximation ... ok [INFO] [stdout] test nlp_kernels::tests::test_semantic_kernel_approximation ... ok [INFO] [stdout] test error_bounded::tests::test_error_bounded_rbf_sampler ... ok [INFO] [stdout] test numerical_stability::tests::test_stable_cholesky ... ok [INFO] [stdout] test numerical_stability::tests::test_stable_kernel_matrix ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_linear_kernel ... ok [INFO] [stdout] test numerical_stability::tests::test_stable_eigendecomposition ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_polynomial_kernel ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_reproducibility ... ok [INFO] [stdout] test numerical_stability::tests::test_stable_matrix_inverse ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_rbf_kernel ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_feature_mismatch ... ok [INFO] [stdout] test optimal_transport::tests::test_emd_kernel_sampler ... ok [INFO] [stdout] test optimal_transport::tests::test_gromov_wasserstein_sampler ... ok [INFO] [stdout] test optimal_transport::tests::test_reproducibility ... ok [INFO] [stdout] test optimal_transport::tests::test_wasserstein_different_methods ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_sampling_strategies ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_rbf_with_different_sampling ... ok [INFO] [stdout] test out_of_core::tests::test_data_density_estimation ... ok [INFO] [stdout] test out_of_core::tests::test_out_of_core_config ... ok [INFO] [stdout] test optimal_transport::tests::test_wasserstein_kernel_sampler ... ok [INFO] [stdout] test nystroem::tests::test_nystroem_improved_eigendecomposition ... ok [INFO] [stdout] test optimal_transport::tests::test_different_ground_metrics ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_efficient_nystroem_incremental ... ok [INFO] [stdout] test out_of_core::tests::test_memory_estimation ... ok [INFO] [stdout] test out_of_core::tests::test_out_of_core_loader ... ok [INFO] [stdout] test out_of_core::tests::test_streaming_strategy ... ok [INFO] [stdout] test out_of_core::tests::test_parallel_strategy ... ok [INFO] [stdout] test out_of_core::tests::test_adaptive_strategy ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_grid_creation ... ok [INFO] [stdout] test out_of_core::tests::test_out_of_core_rbf_sampler ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_objective_functions ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_learner_bayesian_optimization ... ok [INFO] [stdout] test out_of_core::tests::test_out_of_core_nystroem ... ok [INFO] [stdout] test parameter_learning::tests::test_optimization_result ... ok [INFO] [stdout] test plugin_architecture::tests::test_global_plugin_registry ... ok [INFO] [stdout] test error_bounded::tests::test_error_bound_methods ... ok [INFO] [stdout] test plugin_architecture::tests::test_plugin_instance_creation ... ok [INFO] [stdout] test plugin_architecture::tests::test_plugin_registration ... ok [INFO] [stdout] test plugin_architecture::tests::test_plugin_wrapper_fit_transform ... ok [INFO] [stdout] test polynomial_count_sketch::tests::test_polynomial_count_sketch_basic ... ok [INFO] [stdout] test polynomial_count_sketch::tests::test_polynomial_count_sketch_invalid_degree ... ok [INFO] [stdout] test polynomial_count_sketch::tests::test_polynomial_count_sketch_reproducibility ... ok [INFO] [stdout] test polynomial_count_sketch::tests::test_polynomial_count_sketch_with_coef0 ... ok [INFO] [stdout] test polynomial_count_sketch::tests::test_polynomial_count_sketch_zero_components ... ok [INFO] [stdout] test plugin_architecture::tests::test_invalid_configuration ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_degree_3 ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_basic ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_feature_mismatch ... ok [INFO] [stdout] test memory_efficient::tests::test_memory_efficient_nystroem ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_no_bias ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_single_feature ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_zero_degree ... ok [INFO] [stdout] test polynomial_features::tests::test_polynomial_features_interaction_only ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_learner_random_search ... ok [INFO] [stdout] test progressive::tests::test_progressive_reproducibility ... ok [INFO] [stdout] test parameter_learning::tests::test_cross_validation_objective ... ok [INFO] [stdout] test progressive::tests::test_progressive_strategies ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_learner_grid_search ... ok [INFO] [stdout] test quasi_random_features::tests::test_box_muller_transform ... ok [INFO] [stdout] test quasi_random_features::tests::test_different_sequence_types ... ok [INFO] [stdout] test quasi_random_features::tests::test_error_handling ... ok [INFO] [stdout] test quasi_random_features::tests::test_gamma_parameter ... ok [INFO] [stdout] test quasi_random_features::tests::test_get_first_primes ... ok [INFO] [stdout] test quasi_random_features::tests::test_halton_sequence ... ok [INFO] [stdout] test quasi_random_features::tests::test_quasi_random_rbf_sampler_basic ... ok [INFO] [stdout] test quasi_random_features::tests::test_reproducibility ... ok [INFO] [stdout] test quasi_random_features::tests::test_sobol_point_properties ... ok [INFO] [stdout] test quasi_random_features::tests::test_van_der_corput_sequence ... ok [INFO] [stdout] test progressive::tests::test_progressive_rbf_sampler ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_basic ... ok [INFO] [stdout] test progressive::tests::test_progressive_improvement ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_different_degrees ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_reproducibility ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_invalid_degree ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_feature_mismatch ... ok [INFO] [stdout] test rbf_sampler::tests::test_arc_cosine_sampler_zero_components ... ok [INFO] [stdout] test rbf_sampler::tests::test_laplacian_sampler_basic ... ok [INFO] [stdout] test rbf_sampler::tests::test_laplacian_sampler_feature_mismatch ... ok [INFO] [stdout] test progressive::tests::test_quality_metrics ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_basic ... ok [INFO] [stdout] test rbf_sampler::tests::test_laplacian_sampler_invalid_gamma ... ok [INFO] [stdout] test rbf_sampler::tests::test_laplacian_sampler_reproducibility ... ok [INFO] [stdout] test rbf_sampler::tests::test_laplacian_sampler_zero_components ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_feature_mismatch ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_reproducibility ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_zero_components ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_invalid_gamma ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_zero_degree ... ok [INFO] [stdout] test rbf_sampler::tests::test_rbf_sampler_basic ... ok [INFO] [stdout] test rbf_sampler::tests::test_rbf_sampler_invalid_gamma ... ok [INFO] [stdout] test rbf_sampler::tests::test_rbf_sampler_reproducibility ... ok [INFO] [stdout] test rbf_sampler::tests::test_rbf_sampler_zero_components ... ok [INFO] [stdout] test rbf_sampler::tests::test_rbf_sampler_feature_mismatch ... ok [INFO] [stdout] test robust_kernels::tests::test_contamination_resistance ... ok [INFO] [stdout] test rbf_sampler::tests::test_polynomial_sampler_different_degrees ... ok [INFO] [stdout] test robust_kernels::tests::test_influence_function_diagnostics ... ok [INFO] [stdout] test robust_kernels::tests::test_robust_nystroem ... ok [INFO] [stdout] test robust_kernels::tests::test_breakdown_point_analysis ... ok [INFO] [stdout] test progressive::tests::test_stopping_criteria ... ok [INFO] [stdout] test sparse_gp::approximations::tests::test_fic_approximation ... ok [INFO] [stdout] test sparse_gp::approximations::tests::test_kmeans_inducing_selection ... ok [INFO] [stdout] test sparse_gp::approximations::tests::test_sor_approximation ... ok [INFO] [stdout] test sparse_gp::approximations::tests::test_uniform_grid_selection ... ok [INFO] [stdout] test robust_kernels::tests::test_robust_rbf_sampler ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_block_diagonal_solver ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_diagonal_preconditioner ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_direct_prediction ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_iterative_refinement ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_lanczos_eigendecomposition ... ok [INFO] [stdout] test sparse_gp::inference::tests::test_pcg_solver ... ok [INFO] [stdout] test sparse_gp::kernels::tests::test_cholesky_decomposition ... ok [INFO] [stdout] test robust_kernels::tests::test_robust_loss_functions ... ok [INFO] [stdout] test sparse_gp::kernels::tests::test_rbf_kernel ... ok [INFO] [stdout] test sparse_gp::kernels::tests::test_triangular_solve ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_chunked_kernel_computation ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_simd_distance_matrix ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_batch_operations ... ok [INFO] [stdout] test sparse_gp::kernels::tests::test_kernel_parameters ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_simd_eigenvalues_2x2 ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_simd_posterior_mean ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_simd_posterior_variance ... ok [INFO] [stdout] test sparse_gp::approximations::tests::test_random_inducing_selection ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_cubic_interpolation ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_grid_generation ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_grid_size_inference ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_ski_fit ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_linear_interpolation_weights ... ok [INFO] [stdout] test sparse_gp::simd_operations::tests::test_simd_rbf_kernel_matrix ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_ski_prediction ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_ski_with_variance ... ok [INFO] [stdout] test sparse_gp::ski::tests::test_tensor_ski_creation ... ok [INFO] [stdout] test sparse_gp::variational::tests::test_kl_divergence_whitened ... ok [INFO] [stdout] test sparse_gp::variational::tests::test_expected_log_likelihood ... ok [INFO] [stdout] test sparse_gp::variational::tests::test_predictive_moments ... ok [INFO] [stdout] test sparse_gp::variational::tests::test_stochastic_batch_sampling ... ok [INFO] [stdout] test sparse_gp::variational::tests::test_vfe_initialization ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_matrix_basic ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_matrix_csr_conversion ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_matrix_sparsity_thresholding ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_basic ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_different_formats ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_interaction_only ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_feature_mismatch ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_matrix_to_dense ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_memory_efficiency ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_no_bias ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_single_feature ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_sparsity_strategies ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_transform_sparse ... ok [INFO] [stdout] test sparse_polynomial::tests::test_sparse_polynomial_zero_degree ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_gradient_optimizers ... ok [INFO] [stdout] test streaming_kernel::tests::test_buffer_strategies ... ok [INFO] [stdout] test streaming_kernel::tests::test_drift_detection ... ok [INFO] [stdout] test streaming_kernel::tests::test_feature_statistics ... ok [INFO] [stdout] test streaming_kernel::tests::test_streaming_config ... ok [INFO] [stdout] test streaming_kernel::tests::test_streaming_nystroem_basic ... ok [INFO] [stdout] test streaming_kernel::tests::test_streaming_rbf_sampler_basic ... ok [INFO] [stdout] test streaming_kernel::tests::test_streaming_sample ... ok [INFO] [stdout] test string_kernels::tests::test_mismatch_kernel ... ok [INFO] [stdout] test streaming_kernel::tests::test_online_updates ... ok [INFO] [stdout] test streaming_kernel::tests::test_transform_sample ... ok [INFO] [stdout] test string_kernels::tests::test_edit_distance_computation ... ok [INFO] [stdout] test string_kernels::tests::test_edit_distance_kernel ... ok [INFO] [stdout] test string_kernels::tests::test_ngram_binary_mode ... ok [INFO] [stdout] test string_kernels::tests::test_ngram_kernel_character ... ok [INFO] [stdout] test string_kernels::tests::test_ngram_kernel_word ... ok [INFO] [stdout] test string_kernels::tests::test_spectrum_kernel ... ok [INFO] [stdout] test string_kernels::tests::test_subsequence_kernel ... ok [INFO] [stdout] test structured_random_features::tests::test_different_gamma_values ... ok [INFO] [stdout] test structured_random_features::tests::test_fast_walsh_hadamard_transform ... ok [INFO] [stdout] test structured_random_features::tests::test_fwht_invalid_size ... ok [INFO] [stdout] test structured_random_features::tests::test_reproducibility ... ok [INFO] [stdout] test structured_random_features::tests::test_structured_random_features_basic ... ok [INFO] [stdout] test structured_random_features::tests::test_structured_rff_hadamard ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_contraction_map ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_contraction_methods ... ok [INFO] [stdout] test structured_random_features::tests::test_structured_matrices ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_different_orderings ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_interaction_only ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_no_bias ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_different_dimensions ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_single_feature ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_basic ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_feature_mismatch ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_zero_degree ... ok [INFO] [stdout] test tensor_polynomial::tests::test_tensor_polynomial_zero_dimensions ... ok [INFO] [stdout] test time_series_kernels::tests::test_autoregressive_kernel_approximation ... ok [INFO] [stdout] test time_series_kernels::tests::test_dtw_distance_computation ... ok [INFO] [stdout] test time_series_kernels::tests::test_dtw_window_constraints ... ok [INFO] [stdout] test time_series_kernels::tests::test_frequency_features ... ok [INFO] [stdout] test tests::test_kernel_approximation_integration ... ok [INFO] [stdout] test time_series_kernels::tests::test_ar_model_fitting ... ok [INFO] [stdout] test time_series_kernels::tests::test_global_alignment_kernel ... ok [INFO] [stdout] test time_series_kernels::tests::test_spectral_kernel_approximation ... ok [INFO] [stdout] test time_series_kernels::tests::test_time_series_kernel_config ... ok [INFO] [stdout] test time_series_kernels::tests::test_dtw_kernel_approximation ... ok [INFO] [stdout] test type_safe_kernels::tests::test_compile_time_compatibility ... ok [INFO] [stdout] test type_safe_kernels::tests::test_fastfood_power_of_two_requirement ... ok [INFO] [stdout] test type_safe_kernels::tests::test_quality_metrics ... ok [INFO] [stdout] test type_safety::advanced_composition_tests::test_approximation_bounds ... ok [INFO] [stdout] test type_safety::advanced_composition_tests::test_kernel_composition ... ok [INFO] [stdout] test type_safety::advanced_composition_tests::test_type_safe_configs ... ok [INFO] [stdout] test type_safety::advanced_composition_tests::test_validated_features ... ok [INFO] [stdout] test type_safety::advanced_type_safety_tests::test_bounded_quality_metrics ... ok [INFO] [stdout] test type_safety::advanced_type_safety_tests::test_kernel_method_compatibility ... ok [INFO] [stdout] test type_safety::advanced_type_safety_tests::test_macro_creation ... ok [INFO] [stdout] test type_safety::advanced_type_safety_tests::test_validated_components ... ok [INFO] [stdout] test type_safety::preset_tests::test_kernel_presets ... ok [INFO] [stdout] test type_safety::preset_tests::test_profile_guided_config ... ok [INFO] [stdout] test time_series_kernels::tests::test_reproducibility_with_random_state ... ok [INFO] [stdout] test type_safety::tests::test_compile_time_constants ... ok [INFO] [stdout] test type_safety::tests::test_polynomial_kernel ... ok [INFO] [stdout] test type_safety::tests::test_type_safe_nystrom ... ok [INFO] [stdout] test type_safety::tests::test_type_safe_rbf_rff ... ok [INFO] [stdout] test type_safe_kernels::tests::test_type_safe_laplacian_rff ... ok [INFO] [stdout] test type_safety::preset_tests::test_serializable_config ... ok [INFO] [stdout] test validation::tests::test_theoretical_bounds ... ok [INFO] [stdout] test validation::tests::test_validator_creation ... ok [INFO] [stdout] test type_safe_kernels::tests::test_type_safe_nystrom ... ok [INFO] [stdout] test type_safe_kernels::tests::test_type_safe_rbf_rff ... ok [INFO] [stdout] test parameter_learning::tests::test_effective_rank_objective ... ok [INFO] [stdout] test robust_kernels::tests::test_robust_estimators ... ok [INFO] [stdout] test out_of_core::tests::test_out_of_core_pipeline ... ok [INFO] [stdout] test validation::tests::test_method_validation ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_learner_nystroem ... ok [INFO] [stdout] test gradient_kernel_learning::tests::test_multi_kernel_learner ... ok [INFO] [stdout] test validation::tests::test_cross_validation ... ok [INFO] [stdout] test progressive::tests::test_progressive_nystroem ... ok [INFO] [stdout] test budget_constrained::tests::test_budget_constrained_nystroem ... ok [INFO] [stdout] test error_bounded::tests::test_error_bounded_nystroem ... ok [INFO] [stdout] test adaptive_bandwidth_rbf::tests::test_large_dataset_efficiency ... ok [INFO] [stdout] test parameter_learning::tests::test_parameter_learner_coordinate_descent ... ok [INFO] [stdout] test error_bounded::tests::test_min_components_search ... ok [INFO] [stdout] [INFO] [stdout] test result: ok. 429 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 11.02s [INFO] [stdout] [INFO] [stderr] Running unittests src/bin/test_manual.rs (/opt/rustwide/target/debug/deps/test_manual-4e62a7664e67976e) [INFO] [stdout] [INFO] [stdout] running 0 tests [INFO] [stdout] [INFO] [stdout] test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s [INFO] [stdout] [INFO] [stderr] Doc-tests sklears_kernel_approximation [INFO] [stdout] [INFO] [stdout] running 27 tests [INFO] [stdout] test src/adaptive_bandwidth_rbf.rs - adaptive_bandwidth_rbf::AdaptiveBandwidthRBFSampler (line 71) ... ignored [INFO] [stdout] test src/adaptive_nystroem.rs - adaptive_nystroem::AdaptiveNystroem (line 60) ... ignored [INFO] [stdout] test src/chi2_samplers.rs - chi2_samplers::AdditiveChi2Sampler (line 26) ... ignored [INFO] [stdout] test src/chi2_samplers.rs - chi2_samplers::SkewedChi2Sampler (line 138) ... ignored [INFO] [stdout] test src/custom_kernel.rs - custom_kernel::CustomKernelSampler (line 269) ... ignored [INFO] [stdout] test src/ensemble_nystroem.rs - ensemble_nystroem::EnsembleNystroem (line 56) ... ignored [INFO] [stdout] test src/fastfood.rs - fastfood::FastfoodTransform (line 45) ... ignored [INFO] [stdout] test src/homogeneous_polynomial.rs - homogeneous_polynomial::HomogeneousPolynomialFeatures (line 58) ... ignored [INFO] [stdout] test src/incremental_nystroem.rs - incremental_nystroem::IncrementalNystroem (line 48) ... ignored [INFO] [stdout] test src/kernel_ridge_regression/mod.rs - kernel_ridge_regression (line 38) ... ignored [INFO] [stdout] test src/kernel_ridge_regression/mod.rs - kernel_ridge_regression (line 67) ... ignored [INFO] [stdout] test src/kernel_ridge_regression/mod.rs - kernel_ridge_regression (line 93) ... ignored [INFO] [stdout] test src/kernel_ridge_regression/multitask_regression.rs - kernel_ridge_regression::multitask_regression::MultiTaskKernelRidgeRegression (line 37) ... ignored [INFO] [stdout] test src/kernel_ridge_regression/robust_regression.rs - kernel_ridge_regression::robust_regression::RobustKernelRidgeRegression (line 36) ... ignored [INFO] [stdout] test src/multi_scale_rbf.rs - multi_scale_rbf::MultiScaleRBFSampler (line 68) ... ignored [INFO] [stdout] test src/nystroem.rs - nystroem::Nystroem (line 99) ... ignored [INFO] [stdout] test src/polynomial_count_sketch.rs - polynomial_count_sketch::PolynomialCountSketch (line 31) ... ignored [INFO] [stdout] test src/polynomial_features.rs - polynomial_features::PolynomialFeatures (line 25) ... ignored [INFO] [stdout] test src/quasi_random_features.rs - quasi_random_features::QuasiRandomRBFSampler (line 49) ... ignored [INFO] [stdout] test src/rbf_sampler.rs - rbf_sampler::ArcCosineSampler (line 586) ... ignored [INFO] [stdout] test src/rbf_sampler.rs - rbf_sampler::LaplacianSampler (line 195) ... ignored [INFO] [stdout] test src/rbf_sampler.rs - rbf_sampler::PolynomialSampler (line 363) ... ignored [INFO] [stdout] test src/rbf_sampler.rs - rbf_sampler::RBFSampler (line 29) ... ignored [INFO] [stdout] test src/sparse_polynomial.rs - sparse_polynomial::SparsePolynomialFeatures (line 323) ... ignored [INFO] [stdout] test src/structured_random_features.rs - structured_random_features::StructuredRandomFeatures (line 205) ... ignored [INFO] [stdout] test src/tensor_polynomial.rs - tensor_polynomial::TensorPolynomialFeatures (line 55) ... ignored [INFO] [stdout] test src/optimal_transport.rs - optimal_transport::WassersteinKernelSampler::new (line 85) ... ok [INFO] [stdout] [INFO] [stdout] test result: ok. 1 passed; 0 failed; 26 ignored; 0 measured; 0 filtered out; finished in 1.76s [INFO] [stdout] [INFO] running `Command { std: "docker" "inspect" "fa4c79740e72cbec61fbbcc432b33f23874cda8a4af74df301ee1ddba3de77bb", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "fa4c79740e72cbec61fbbcc432b33f23874cda8a4af74df301ee1ddba3de77bb", kill_on_drop: false }` [INFO] [stdout] fa4c79740e72cbec61fbbcc432b33f23874cda8a4af74df301ee1ddba3de77bb