[INFO] cloning repository https://github.com/gugu8intel-i9/Rust-Neural-Network
[INFO] running `Command { std: "git" "-c" "credential.helper=" "-c" "credential.helper=/workspace/cargo-home/bin/git-credential-null" "clone" "--bare" "https://github.com/gugu8intel-i9/Rust-Neural-Network" "/workspace/cache/git-repos/https%3A%2F%2Fgithub.com%2Fgugu8intel-i9%2FRust-Neural-Network", kill_on_drop: false }`
[INFO] [stderr] Cloning into bare repository '/workspace/cache/git-repos/https%3A%2F%2Fgithub.com%2Fgugu8intel-i9%2FRust-Neural-Network'...
[INFO] running `Command { std: "git" "rev-parse" "HEAD", kill_on_drop: false }`
[INFO] [stdout] c08dd0271a4c53fd45639b2bf88586426499b797
[INFO] testing gugu8intel-i9/Rust-Neural-Network against 1.95.0 for beta-1.96-2
[INFO] running `Command { std: "git" "clone" "/workspace/cache/git-repos/https%3A%2F%2Fgithub.com%2Fgugu8intel-i9%2FRust-Neural-Network" "/workspace/builds/worker-1-tc1/source", kill_on_drop: false }`
[INFO] [stderr] Cloning into '/workspace/builds/worker-1-tc1/source'...
[INFO] [stderr] done.
[INFO] started tweaking git repo https://github.com/gugu8intel-i9/Rust-Neural-Network
[INFO] finished tweaking git repo https://github.com/gugu8intel-i9/Rust-Neural-Network
[INFO] tweaked toml for git repo https://github.com/gugu8intel-i9/Rust-Neural-Network written to /workspace/builds/worker-1-tc1/source/Cargo.toml
[INFO] validating manifest of git repo https://github.com/gugu8intel-i9/Rust-Neural-Network on toolchain 1.95.0
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+1.95.0" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }`
[INFO] crate git repo https://github.com/gugu8intel-i9/Rust-Neural-Network 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" "+1.95.0" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] [stderr]     Updating crates.io index
[INFO] [stderr]  Downloading crates ...
[INFO] [stderr]   Downloaded ndarray-rand v0.14.0
[INFO] [stderr]   Downloaded matrixmultiply v0.3.10
[INFO] [stderr]   Downloaded rand_distr v0.4.3
[INFO] [stderr]   Downloaded zerocopy-derive v0.8.48
[INFO] [stderr]   Downloaded ndarray v0.15.6
[INFO] [stderr]   Downloaded libc v0.2.183
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-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:d429b63d4308055ea97f60fb1d3dfca48854a00942f1bd2ad806beaf015945ec" "/opt/rustwide/cargo-home/bin/cargo" "+1.95.0" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }`
[INFO] [stdout] 56b11f408a253378d29a74b82ca99af057874a28a96f095a108c772fc8c6947c
[INFO] running `Command { std: "docker" "start" "-a" "56b11f408a253378d29a74b82ca99af057874a28a96f095a108c772fc8c6947c", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "inspect" "56b11f408a253378d29a74b82ca99af057874a28a96f095a108c772fc8c6947c", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "56b11f408a253378d29a74b82ca99af057874a28a96f095a108c772fc8c6947c", kill_on_drop: false }`
[INFO] [stdout] 56b11f408a253378d29a74b82ca99af057874a28a96f095a108c772fc8c6947c
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-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=warn" "-e" "RUSTDOCFLAGS=--cap-lints=warn" "-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:d429b63d4308055ea97f60fb1d3dfca48854a00942f1bd2ad806beaf015945ec" "/opt/rustwide/cargo-home/bin/cargo" "+1.95.0" "build" "--frozen" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] a565781617a533793432cda79cdf46286ab8484966daac92deabc825173427cc
[INFO] running `Command { std: "docker" "start" "-a" "a565781617a533793432cda79cdf46286ab8484966daac92deabc825173427cc", kill_on_drop: false }`
[INFO] [stderr]    Compiling autocfg v1.5.0
[INFO] [stderr]    Compiling crossbeam-utils v0.8.21
[INFO] [stderr]    Compiling libm v0.2.16
[INFO] [stderr]    Compiling libc v0.2.183
[INFO] [stderr]    Compiling zerocopy v0.8.48
[INFO] [stderr]    Compiling cfg-if v1.0.4
[INFO] [stderr]    Compiling serde_core v1.0.228
[INFO] [stderr]    Compiling rayon-core v1.13.0
[INFO] [stderr]    Compiling serde v1.0.228
[INFO] [stderr]    Compiling either v1.15.0
[INFO] [stderr]    Compiling rawpointer v0.2.1
[INFO] [stderr]    Compiling num-traits v0.2.19
[INFO] [stderr]    Compiling matrixmultiply v0.3.10
[INFO] [stderr]    Compiling crossbeam-epoch v0.9.18
[INFO] [stderr]    Compiling crossbeam-deque v0.8.6
[INFO] [stderr]    Compiling getrandom v0.2.17
[INFO] [stderr]    Compiling rand_core v0.6.4
[INFO] [stderr]    Compiling rayon v1.11.0
[INFO] [stderr]    Compiling num-complex v0.4.6
[INFO] [stderr]    Compiling num-integer v0.1.46
[INFO] [stderr]    Compiling ndarray v0.15.6
[INFO] [stderr]    Compiling ppv-lite86 v0.2.21
[INFO] [stderr]    Compiling rand_chacha v0.3.1
[INFO] [stderr]    Compiling rand v0.8.5
[INFO] [stderr]    Compiling rand_distr v0.4.3
[INFO] [stderr]    Compiling ndarray-rand v0.14.0
[INFO] [stderr]    Compiling rust-nn v0.1.0 (/opt/rustwide/workdir)
[INFO] [stderr]     Finished `dev` profile [unoptimized + debuginfo] target(s) in 14.65s
[INFO] running `Command { std: "docker" "inspect" "a565781617a533793432cda79cdf46286ab8484966daac92deabc825173427cc", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "a565781617a533793432cda79cdf46286ab8484966daac92deabc825173427cc", kill_on_drop: false }`
[INFO] [stdout] a565781617a533793432cda79cdf46286ab8484966daac92deabc825173427cc
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-1-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=warn" "-e" "RUSTDOCFLAGS=--cap-lints=warn" "-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:d429b63d4308055ea97f60fb1d3dfca48854a00942f1bd2ad806beaf015945ec" "/opt/rustwide/cargo-home/bin/cargo" "+1.95.0" "test" "--frozen" "--no-run" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] 6d785dd049e04d939eec6969154009d15c9a392e6d83f1a564cbbc38386181a7
[INFO] running `Command { std: "docker" "start" "-a" "6d785dd049e04d939eec6969154009d15c9a392e6d83f1a564cbbc38386181a7", kill_on_drop: false }`
[INFO] [stderr]    Compiling approx v0.5.1
[INFO] [stderr]    Compiling rust-nn v0.1.0 (/opt/rustwide/workdir)
[INFO] [stdout] warning: unused import: `Optimizer`
[INFO] [stdout]  --> examples/xor.rs:3:22
[INFO] [stdout]   |
[INFO] [stdout] 3 | use rust_nn::optim::{Optimizer, Adam};
[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: `Loss`
[INFO] [stdout]  --> examples/xor.rs:4:30
[INFO] [stdout]   |
[INFO] [stdout] 4 | use rust_nn::loss::{MSELoss, Loss};
[INFO] [stdout]   |                              ^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `rust_nn::nn::Dropout`
[INFO] [stdout]  --> examples/classification.rs:7:53
[INFO] [stdout]   |
[INFO] [stdout] 7 | use rust_nn::nn::{Module, Sequential, Linear, ReLU, Dropout};
[INFO] [stdout]   |                                                     ^^^^^^^ no `Dropout` in `nn`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `rust_nn::train::TrainConfig`
[INFO] [stdout]   --> examples/classification.rs:10:49
[INFO] [stdout]    |
[INFO] [stdout] 10 | use rust_nn::train::{SimpleDataLoader, Trainer, TrainConfig};
[INFO] [stdout]    |                                                 ^^^^^^^^^^^ no `TrainConfig` in `train`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Module`
[INFO] [stdout]  --> examples/classification.rs:7:19
[INFO] [stdout]   |
[INFO] [stdout] 7 | use rust_nn::nn::{Module, Sequential, Linear, ReLU, Dropout};
[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: `Optimizer`
[INFO] [stdout]  --> examples/classification.rs:8:22
[INFO] [stdout]   |
[INFO] [stdout] 8 | use rust_nn::optim::{Optimizer, Adam};
[INFO] [stdout]   |                      ^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `rust_nn::nn::Sigmoid`
[INFO] [stdout]  --> examples/basic.rs:7:53
[INFO] [stdout]   |
[INFO] [stdout] 7 | use rust_nn::nn::{Module, Sequential, Linear, ReLU, Sigmoid};
[INFO] [stdout]   |                                                     ^^^^^^^ no `Sigmoid` in `nn`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0432]: unresolved import `rust_nn::activations::softmax`
[INFO] [stdout]  --> examples/basic.rs:8:43
[INFO] [stdout]   |
[INFO] [stdout] 8 | use rust_nn::activations::{relu, sigmoid, softmax};
[INFO] [stdout]   |                                           ^^^^^^^ no `softmax` in `activations`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:19:43
[INFO] [stdout]    |
[INFO] [stdout] 19 |     println!("Zeros tensor (2x3):\n{}\n", zeros);
[INFO] [stdout]    |                                    --     ^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                    |
[INFO] [stdout]    |                                    required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:22:42
[INFO] [stdout]    |
[INFO] [stdout] 22 |     println!("Ones tensor (2x3):\n{}\n", ones);
[INFO] [stdout]    |                                   --     ^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                   |
[INFO] [stdout]    |                                   required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:25:44
[INFO] [stdout]    |
[INFO] [stdout] 25 |     println!("Random tensor (2x3):\n{}\n", random);
[INFO] [stdout]    |                                     --     ^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                     |
[INFO] [stdout]    |                                     required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:31:33
[INFO] [stdout]    |
[INFO] [stdout] 31 |     println!("Tensor A:\n{}\n", a);
[INFO] [stdout]    |                          --     ^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                          |
[INFO] [stdout]    |                          required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:32:33
[INFO] [stdout]    |
[INFO] [stdout] 32 |     println!("Tensor B:\n{}\n", b);
[INFO] [stdout]    |                          --     ^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                          |
[INFO] [stdout]    |                          required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:36:30
[INFO] [stdout]    |
[INFO] [stdout] 36 |     println!("A + B:\n{}\n", sum);
[INFO] [stdout]    |                       --     ^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                       |
[INFO] [stdout]    |                       required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:39:45
[INFO] [stdout]    |
[INFO] [stdout] 39 |     println!("A * B (element-wise):\n{}\n", product);
[INFO] [stdout]    |                                      --     ^^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                      |
[INFO] [stdout]    |                                      required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:43:48
[INFO] [stdout]    |
[INFO] [stdout] 43 |     println!("A @ B (matrix multiply):\n{}\n", matmul);
[INFO] [stdout]    |                                         --     ^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                         |
[INFO] [stdout]    |                                         required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:48:53
[INFO] [stdout]    |
[INFO] [stdout] 48 |     println!("Reshaped from [2,3] to [3,2]:\n{}\n", reshaped);
[INFO] [stdout]    |                                              --     ^^^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                                              |
[INFO] [stdout]    |                                              required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:52:37
[INFO] [stdout]    |
[INFO] [stdout] 52 |     println!("A transposed:\n{}\n", transposed);
[INFO] [stdout]    |                              --     ^^^^^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                              |
[INFO] [stdout]    |                              required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]   --> examples/basic.rs:55:30
[INFO] [stdout]    |
[INFO] [stdout] 55 |     println!("A sum: {:.4}", a.sum());
[INFO] [stdout]    |                      -----   ^^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]    |                      |
[INFO] [stdout]    |                      required by this formatting parameter
[INFO] [stdout]    |
[INFO] [stdout]    = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]    = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `mean` found for struct `Tensor` in the current scope
[INFO] [stdout]   --> examples/basic.rs:56:33
[INFO] [stdout]    |
[INFO] [stdout] 56 |     println!("A mean: {:.4}", a.mean());
[INFO] [stdout]    |                                 ^^^^ method not found in `Tensor`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: the method `max` exists for struct `Tensor`, but its trait bounds were not satisfied
[INFO] [stdout]   --> examples/basic.rs:57:32
[INFO] [stdout]    |
[INFO] [stdout] 57 |     println!("A max: {:.4}", a.max());
[INFO] [stdout]    |                                ^^^ method cannot be called on `Tensor` due to unsatisfied trait bounds
[INFO] [stdout]    |
[INFO] [stdout]   ::: src/tensor.rs:36:1
[INFO] [stdout]    |
[INFO] [stdout] 36 | pub struct Tensor(pub Arc<RwLock<TensorData>>);
[INFO] [stdout]    | ----------------- doesn't satisfy `Tensor: Iterator` or `Tensor: Ord`
[INFO] [stdout]    |
[INFO] [stdout]    = note: the following trait bounds were not satisfied:
[INFO] [stdout]            `Tensor: Ord`
[INFO] [stdout]            which is required by `&Tensor: Ord`
[INFO] [stdout]            `Tensor: Ord`
[INFO] [stdout]            which is required by `&mut Tensor: Ord`
[INFO] [stdout]            `Tensor: Iterator`
[INFO] [stdout]            which is required by `&mut Tensor: Iterator`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/basic.rs:83:14
[INFO] [stdout]    |
[INFO] [stdout] 83 |         .add(Linear::new(10, 32))
[INFO] [stdout]    |              ^^^^^^^^^^^-------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 83 |         .add(Linear::new(10, 32, /* bool */))
[INFO] [stdout]    |                                ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/basic.rs:85:14
[INFO] [stdout]    |
[INFO] [stdout] 85 |         .add(Linear::new(32, 16))
[INFO] [stdout]    |              ^^^^^^^^^^^-------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 85 |         .add(Linear::new(32, 16, /* bool */))
[INFO] [stdout]    |                                ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/basic.rs:87:14
[INFO] [stdout]    |
[INFO] [stdout] 87 |         .add(Linear::new(16, 5));
[INFO] [stdout]    |              ^^^^^^^^^^^------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 87 |         .add(Linear::new(16, 5, /* bool */));
[INFO] [stdout]    |                               ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]   --> examples/classification.rs:36:35
[INFO] [stdout]    |
[INFO] [stdout] 32 |             inputs_data.push(mean + noise);
[INFO] [stdout]    |             -----------      ------------ this argument has type `f64`...
[INFO] [stdout]    |             |
[INFO] [stdout]    |             ... which causes `inputs_data` to have type `Vec<f64>`
[INFO] [stdout] ...
[INFO] [stdout] 36 |     let inputs = Tensor::from_vec(inputs_data, vec![n_samples, n_features]);
[INFO] [stdout]    |                  ---------------- ^^^^^^^^^^^ expected `Vec<f32>`, found `Vec<f64>`
[INFO] [stdout]    |                  |
[INFO] [stdout]    |                  arguments to this function are incorrect
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected struct `Vec<f32>`
[INFO] [stdout]               found struct `Vec<f64>`
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/tensor.rs:62:12
[INFO] [stdout]    |
[INFO] [stdout] 62 |     pub fn from_vec(data: Vec<f32>, shape: Vec<usize>) -> Self {
[INFO] [stdout]    |            ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `get` found for struct `Tensor` in the current scope
[INFO] [stdout]    --> examples/basic.rs:100:49
[INFO] [stdout]     |
[INFO] [stdout] 100 |         println!("  Class {}: {:.4}", i, output.get(&[0, i]));
[INFO] [stdout]     |                                                 ^^^ method not found in `Tensor`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]    --> examples/basic.rs:106:9
[INFO] [stdout]     |
[INFO] [stdout] 106 |     for (name, param) in &params {
[INFO] [stdout]     |         ^^^^^^^^^^^^^    ------- this is an iterator with items of type `&Tensor`
[INFO] [stdout]     |         |
[INFO] [stdout]     |         expected `Tensor`, found `(_, _)`
[INFO] [stdout]     |
[INFO] [stdout]     = note: expected struct `Tensor`
[INFO] [stdout]                 found tuple `(_, _)`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]   --> examples/classification.rs:37:36
[INFO] [stdout]    |
[INFO] [stdout] 26 |         targets_data.push(class as f64);
[INFO] [stdout]    |         ------------      ------------ this argument has type `f64`...
[INFO] [stdout]    |         |
[INFO] [stdout]    |         ... which causes `targets_data` to have type `Vec<f64>`
[INFO] [stdout] ...
[INFO] [stdout] 37 |     let targets = Tensor::from_vec(targets_data, vec![n_samples]);
[INFO] [stdout]    |                   ---------------- ^^^^^^^^^^^^ expected `Vec<f32>`, found `Vec<f64>`
[INFO] [stdout]    |                   |
[INFO] [stdout]    |                   arguments to this function are incorrect
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected struct `Vec<f32>`
[INFO] [stdout]               found struct `Vec<f64>`
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/tensor.rs:62:12
[INFO] [stdout]    |
[INFO] [stdout] 62 |     pub fn from_vec(data: Vec<f32>, shape: Vec<usize>) -> Self {
[INFO] [stdout]    |            ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]    --> examples/basic.rs:117:35
[INFO] [stdout]     |
[INFO] [stdout] 117 |     println!("Matrix (2x3):\n{}", matrix);
[INFO] [stdout]     |                              --   ^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]     |                              |
[INFO] [stdout]     |                              required by this formatting parameter
[INFO] [stdout]     |
[INFO] [stdout]     = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]     = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]    --> examples/basic.rs:118:32
[INFO] [stdout]     |
[INFO] [stdout] 118 |     println!("Bias (3,):\n{}", bias);
[INFO] [stdout]     |                           --   ^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]     |                           |
[INFO] [stdout]     |                           required by this formatting parameter
[INFO] [stdout]     |
[INFO] [stdout]     = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]     = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0277]: `Tensor` doesn't implement `std::fmt::Display`
[INFO] [stdout]    --> examples/basic.rs:119:50
[INFO] [stdout]     |
[INFO] [stdout] 119 |     println!("Matrix + Bias (broadcasted):\n{}", matrix.add(&bias));
[INFO] [stdout]     |                                             --   ^^^^^^^^^^^^^^^^^ `Tensor` cannot be formatted with the default formatter
[INFO] [stdout]     |                                             |
[INFO] [stdout]     |                                             required by this formatting parameter
[INFO] [stdout]     |
[INFO] [stdout]     = help: the trait `std::fmt::Display` is not implemented for `Tensor`
[INFO] [stdout]     = note: in format strings you may be able to use `{:?}` (or {:#?} for pretty-print) instead
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/classification.rs:46:14
[INFO] [stdout]    |
[INFO] [stdout] 46 |         .add(Linear::new(n_features, 64))
[INFO] [stdout]    |              ^^^^^^^^^^^---------------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 46 |         .add(Linear::new(n_features, 64, /* bool */))
[INFO] [stdout]    |                                        ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0061, E0277, E0308, E0432, E0599.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0061`.
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/classification.rs:49:14
[INFO] [stdout]    |
[INFO] [stdout] 49 |         .add(Linear::new(64, 32))
[INFO] [stdout]    |              ^^^^^^^^^^^-------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 49 |         .add(Linear::new(64, 32, /* bool */))
[INFO] [stdout]    |                                ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 3 arguments but 2 arguments were supplied
[INFO] [stdout]   --> examples/classification.rs:51:14
[INFO] [stdout]    |
[INFO] [stdout] 51 |         .add(Linear::new(32, n_classes));
[INFO] [stdout]    |              ^^^^^^^^^^^--------------- argument #3 of type `bool` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/nn.rs:19:12
[INFO] [stdout]    |
[INFO] [stdout] 19 |     pub fn new(in_features: usize, out_features: usize, bias: bool) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 51 |         .add(Linear::new(32, n_classes, /* bool */));
[INFO] [stdout]    |                                       ++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0061]: this function takes 2 arguments but 1 argument was supplied
[INFO] [stdout]   --> examples/classification.rs:59:21
[INFO] [stdout]    |
[INFO] [stdout] 59 |     let optimizer = Adam::new(0.01)
[INFO] [stdout]    |                     ^^^^^^^^^ ---- argument #1 of type `Vec<Tensor>` is missing
[INFO] [stdout]    |
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/optim.rs:68:12
[INFO] [stdout]    |
[INFO] [stdout] 68 |     pub fn new(params: Vec<Tensor>, lr: f32) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] help: provide the argument
[INFO] [stdout]    |
[INFO] [stdout] 59 |     let optimizer = Adam::new(/* Vec<Tensor> */, 0.01)
[INFO] [stdout]    |                               ++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `rust-nn` (example "basic") due to 23 previous errors
[INFO] [stderr] warning: build failed, waiting for other jobs to finish...
[INFO] [stdout] error[E0599]: no method named `with_weight_decay` found for struct `Adam` in the current scope
[INFO] [stdout]   --> examples/classification.rs:60:10
[INFO] [stdout]    |
[INFO] [stdout] 59 |       let optimizer = Adam::new(0.01)
[INFO] [stdout]    |  _____________________-
[INFO] [stdout] 60 | |         .with_weight_decay(1e-4);
[INFO] [stdout]    | |         -^^^^^^^^^^^^^^^^^ method not found in `Adam`
[INFO] [stdout]    | |_________|
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no function or associated item named `new` found for struct `CrossEntropyLoss` in the current scope
[INFO] [stdout]   --> examples/classification.rs:61:37
[INFO] [stdout]    |
[INFO] [stdout] 61 |     let loss_fn = CrossEntropyLoss::new();
[INFO] [stdout]    |                                     ^^^ function or associated item not found in `CrossEntropyLoss`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]   --> examples/classification.rs:72:36
[INFO] [stdout]    |
[INFO] [stdout] 72 |     let mut trainer = Trainer::new(model, optimizer, loss_fn)
[INFO] [stdout]    |                       ------------ ^^^^^ expected `Arc<dyn Module>`, found `Sequential`
[INFO] [stdout]    |                       |
[INFO] [stdout]    |                       arguments to this function are incorrect
[INFO] [stdout]    |
[INFO] [stdout]    = note: expected struct `Arc<(dyn Module + 'static)>`
[INFO] [stdout]               found struct `Sequential`
[INFO] [stdout] note: associated function defined here
[INFO] [stdout]   --> src/train.rs:80:12
[INFO] [stdout]    |
[INFO] [stdout] 80 |     pub fn new(model: Arc<dyn Module>, optimizer: O, loss_fn: L) -> Self {
[INFO] [stdout]    |            ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `set_shuffle` found for struct `SimpleDataLoader` in the current scope
[INFO] [stdout]   --> examples/classification.rs:81:18
[INFO] [stdout]    |
[INFO] [stdout] 81 |     train_loader.set_shuffle(true);
[INFO] [stdout]    |                  ^^^^^^^^^^^ method not found in `SimpleDataLoader`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0308]: mismatched types
[INFO] [stdout]   --> examples/classification.rs:97:40
[INFO] [stdout]    |
[INFO] [stdout] 97 |     let test_inputs = inputs.reshape(&[n_samples as isize, -1]);
[INFO] [stdout]    |                                        ^^^^^^^^^^^^^^^^^^ expected `usize`, found `isize`
[INFO] [stdout]    |
[INFO] [stdout] help: you can convert an `isize` to a `usize` and panic if the converted value doesn't fit
[INFO] [stdout]    |
[INFO] [stdout] 97 |     let test_inputs = inputs.reshape(&[(n_samples as isize).try_into().unwrap(), -1]);
[INFO] [stdout]    |                                        +                  +++++++++++++++++++++
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0600]: cannot apply unary operator `-` to type `usize`
[INFO] [stdout]   --> examples/classification.rs:97:60
[INFO] [stdout]    |
[INFO] [stdout] 97 |     let test_inputs = inputs.reshape(&[n_samples as isize, -1]);
[INFO] [stdout]    |                                                            ^^ cannot apply unary operator `-`
[INFO] [stdout]    |
[INFO] [stdout]    = note: unsigned values cannot be negated
[INFO] [stdout] help: you may have meant the maximum value of `usize`
[INFO] [stdout]    |
[INFO] [stdout] 97 -     let test_inputs = inputs.reshape(&[n_samples as isize, -1]);
[INFO] [stdout] 97 +     let test_inputs = inputs.reshape(&[n_samples as isize, usize::MAX]);
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0599]: no method named `row` found for struct `Tensor` in the current scope
[INFO] [stdout]   --> examples/classification.rs:98:52
[INFO] [stdout]    |
[INFO] [stdout] 98 |     let predictions = trainer.predict(&test_inputs.row(0).reshape(&[1, -1]));
[INFO] [stdout]    |                                                    ^^^
[INFO] [stdout]    |
[INFO] [stdout] help: there is a method `borrow` with a similar name, but with different arguments
[INFO] [stdout]   --> /rustc/59807616e1fa2540724bfbac14d7976d7e4a3860/library/core/src/borrow.rs:179:4
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] Some errors have detailed explanations: E0061, E0308, E0432, E0599, E0600.
[INFO] [stdout] 
[INFO] [stdout] For more information about an error, try `rustc --explain E0061`.
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `rust-nn` (example "classification") due to 15 previous errors; 2 warnings emitted
[INFO] running `Command { std: "docker" "inspect" "6d785dd049e04d939eec6969154009d15c9a392e6d83f1a564cbbc38386181a7", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "6d785dd049e04d939eec6969154009d15c9a392e6d83f1a564cbbc38386181a7", kill_on_drop: false }`
[INFO] [stdout] 6d785dd049e04d939eec6969154009d15c9a392e6d83f1a564cbbc38386181a7
