[INFO] updating cached repository https://github.com/SSebigo/iris-classification [INFO] running `"git" "-c" "credential.helper=" "-c" "credential.helper=/workspace/cargo-home/bin/git-credential-null" "-c" "remote.origin.fetch=refs/heads/*:refs/heads/*" "fetch" "origin" "--force" "--prune"` [INFO] running `"git" "rev-parse" "HEAD"` [INFO] [stdout] 49bdf25c8825328d541edd31a06875d882b6fd94 [INFO] checking SSebigo/iris-classification against master#45d050cde277b22a755847338f2acc2c7b834141 for pr-71393 [INFO] running `"git" "clone" "/workspace/cache/git-repos/https%3A%2F%2Fgithub.com%2FSSebigo%2Firis-classification" "/workspace/builds/worker-6/source"` [INFO] [stderr] Cloning into '/workspace/builds/worker-6/source'... [INFO] [stderr] done. [INFO] validating manifest of git repo https://github.com/SSebigo/iris-classification on toolchain 45d050cde277b22a755847338f2acc2c7b834141 [INFO] running `"/workspace/cargo-home/bin/cargo" "+45d050cde277b22a755847338f2acc2c7b834141" "read-manifest" "--manifest-path" "Cargo.toml"` [INFO] started tweaking git repo https://github.com/SSebigo/iris-classification [INFO] finished tweaking git repo https://github.com/SSebigo/iris-classification [INFO] tweaked toml for git repo https://github.com/SSebigo/iris-classification written to /workspace/builds/worker-6/source/Cargo.toml [INFO] crate git repo https://github.com/SSebigo/iris-classification already has a lockfile, it will not be regenerated [INFO] running `"/workspace/cargo-home/bin/cargo" "+45d050cde277b22a755847338f2acc2c7b834141" "fetch" "--locked" "--manifest-path" "Cargo.toml"` [INFO] running `"docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-6/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-6/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" "MAP_USER_ID=0" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--network" "none" "rustops/crates-build-env" "/opt/rustwide/cargo-home/bin/cargo" "+45d050cde277b22a755847338f2acc2c7b834141" "check" "--frozen" "--all" "--all-targets"` [INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap. [INFO] [stdout] ede198f440ba4f576ea86faaf90da73b80a36e630558e68e483345faeaec66ef [INFO] running `"docker" "start" "-a" "ede198f440ba4f576ea86faaf90da73b80a36e630558e68e483345faeaec66ef"` [INFO] [stderr] Checking rand_core v0.4.0 [INFO] [stderr] Compiling semver-parser v0.7.0 [INFO] [stderr] Compiling num-traits v0.2.6 [INFO] [stderr] Compiling libc v0.2.48 [INFO] [stderr] Compiling num-complex v0.2.1 [INFO] [stderr] Compiling ndarray v0.12.1 [INFO] [stderr] Checking itertools v0.7.11 [INFO] [stderr] Checking matrixmultiply v0.1.15 [INFO] [stderr] Compiling semver v0.9.0 [INFO] [stderr] Checking rand_core v0.3.1 [INFO] [stderr] Checking rand_jitter v0.1.1 [INFO] [stderr] Checking rand_chacha v0.1.1 [INFO] [stderr] Checking rand_xorshift v0.1.1 [INFO] [stderr] Checking rand_isaac v0.1.1 [INFO] [stderr] Checking rand_hc v0.1.0 [INFO] [stderr] Compiling rustc_version v0.2.3 [INFO] [stderr] Compiling rand_pcg v0.1.1 [INFO] [stderr] Checking rand_os v0.1.1 [INFO] [stderr] Checking rand v0.6.5 [INFO] [stderr] Checking ndarray-rand v0.9.0 [INFO] [stderr] Checking iris-classification v0.1.0 (/opt/rustwide/workdir) [INFO] [stderr] warning: unused import: `Array` [INFO] [stderr] --> src/model.rs:1:15 [INFO] [stderr] | [INFO] [stderr] 1 | use ndarray::{Array, Array2}; [INFO] [stderr] | ^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_imports)]` on by default [INFO] [stderr] [INFO] [stderr] warning: unused import: `Array` [INFO] [stderr] --> src/model.rs:1:15 [INFO] [stderr] | [INFO] [stderr] 1 | use ndarray::{Array, Array2}; [INFO] [stderr] | ^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_imports)]` on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `test_set` [INFO] [stderr] --> src/main.rs:26:21 [INFO] [stderr] | [INFO] [stderr] 26 | let (train_set, test_set) = (train_set.to_vec(), test_set.to_vec()); [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_set` [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_variables)]` on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `set_labels` [INFO] [stderr] --> src/model.rs:76:52 [INFO] [stderr] | [INFO] [stderr] 76 | pub fn fit(&mut self, training_set: Vec, set_labels: Vec<&str>, epochs: usize) { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_set_labels` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `test_set` [INFO] [stderr] --> src/model.rs:132:21 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_set` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `set_labels` [INFO] [stderr] --> src/model.rs:132:41 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_set_labels` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `prediction_set` [INFO] [stderr] --> src/model.rs:136:23 [INFO] [stderr] | [INFO] [stderr] 136 | pub fn predict(prediction_set: T) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prediction_set` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `learning_rate` [INFO] [stderr] --> src/model.rs:141:13 [INFO] [stderr] | [INFO] [stderr] 141 | let learning_rate = 0.001; [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_learning_rate` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `beta_1` [INFO] [stderr] --> src/model.rs:142:13 [INFO] [stderr] | [INFO] [stderr] 142 | let beta_1 = 0.9; [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_beta_1` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `beta_2` [INFO] [stderr] --> src/model.rs:143:13 [INFO] [stderr] | [INFO] [stderr] 143 | let beta_2 = 0.999; [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_beta_2` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `epsilon` [INFO] [stderr] --> src/model.rs:144:13 [INFO] [stderr] | [INFO] [stderr] 144 | let epsilon = 10_f64.powf(-8_f64); [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_epsilon` [INFO] [stderr] [INFO] [stderr] warning: cannot borrow `*self` as mutable because it is also borrowed as immutable [INFO] [stderr] --> src/model.rs:107:52 [INFO] [stderr] | [INFO] [stderr] 104 | match self.layers.last() { [INFO] [stderr] | ----------- immutable borrow occurs here [INFO] [stderr] ... [INFO] [stderr] 107 | prediction_error = self.loss(result.neurons.clone(), iris.class.clone()); [INFO] [stderr] | ^^^^ -------------- immutable borrow later used here [INFO] [stderr] | | [INFO] [stderr] | mutable borrow occurs here [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(mutable_borrow_reservation_conflict)]` on by default [INFO] [stderr] = warning: this borrowing pattern was not meant to be accepted, and may become a hard error in the future [INFO] [stderr] = note: for more information, see issue #59159 [INFO] [stderr] [INFO] [stderr] warning: method is never used: `sigmoid_prime` [INFO] [stderr] --> src/layer.rs:63:5 [INFO] [stderr] | [INFO] [stderr] 63 | fn sigmoid_prime(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(dead_code)]` on by default [INFO] [stderr] [INFO] [stderr] warning: method is never used: `evaluate` [INFO] [stderr] --> src/model.rs:132:5 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `predict` [INFO] [stderr] --> src/model.rs:136:5 [INFO] [stderr] | [INFO] [stderr] 136 | pub fn predict(prediction_set: T) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `adam_optimizer` [INFO] [stderr] --> src/model.rs:140:5 [INFO] [stderr] | [INFO] [stderr] 140 | fn adam_optimizer(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `gradient_descent` [INFO] [stderr] --> src/model.rs:147:5 [INFO] [stderr] | [INFO] [stderr] 147 | fn gradient_descent(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `mean_squared_error` [INFO] [stderr] --> src/model.rs:155:5 [INFO] [stderr] | [INFO] [stderr] 155 | fn mean_squared_error(&mut self, prediction: Array2, target: Array2) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: 17 warnings emitted [INFO] [stderr] [INFO] [stderr] warning: unused variable: `test_set` [INFO] [stderr] --> src/main.rs:26:21 [INFO] [stderr] | [INFO] [stderr] 26 | let (train_set, test_set) = (train_set.to_vec(), test_set.to_vec()); [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_set` [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_variables)]` on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `set_labels` [INFO] [stderr] --> src/model.rs:76:52 [INFO] [stderr] | [INFO] [stderr] 76 | pub fn fit(&mut self, training_set: Vec, set_labels: Vec<&str>, epochs: usize) { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_set_labels` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `test_set` [INFO] [stderr] --> src/model.rs:132:21 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_set` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `set_labels` [INFO] [stderr] --> src/model.rs:132:41 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_set_labels` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `prediction_set` [INFO] [stderr] --> src/model.rs:136:23 [INFO] [stderr] | [INFO] [stderr] 136 | pub fn predict(prediction_set: T) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prediction_set` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `learning_rate` [INFO] [stderr] --> src/model.rs:141:13 [INFO] [stderr] | [INFO] [stderr] 141 | let learning_rate = 0.001; [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_learning_rate` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `beta_1` [INFO] [stderr] --> src/model.rs:142:13 [INFO] [stderr] | [INFO] [stderr] 142 | let beta_1 = 0.9; [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_beta_1` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `beta_2` [INFO] [stderr] --> src/model.rs:143:13 [INFO] [stderr] | [INFO] [stderr] 143 | let beta_2 = 0.999; [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_beta_2` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `epsilon` [INFO] [stderr] --> src/model.rs:144:13 [INFO] [stderr] | [INFO] [stderr] 144 | let epsilon = 10_f64.powf(-8_f64); [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_epsilon` [INFO] [stderr] [INFO] [stderr] warning: cannot borrow `*self` as mutable because it is also borrowed as immutable [INFO] [stderr] --> src/model.rs:107:52 [INFO] [stderr] | [INFO] [stderr] 104 | match self.layers.last() { [INFO] [stderr] | ----------- immutable borrow occurs here [INFO] [stderr] ... [INFO] [stderr] 107 | prediction_error = self.loss(result.neurons.clone(), iris.class.clone()); [INFO] [stderr] | ^^^^ -------------- immutable borrow later used here [INFO] [stderr] | | [INFO] [stderr] | mutable borrow occurs here [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(mutable_borrow_reservation_conflict)]` on by default [INFO] [stderr] = warning: this borrowing pattern was not meant to be accepted, and may become a hard error in the future [INFO] [stderr] = note: for more information, see issue #59159 [INFO] [stderr] [INFO] [stderr] warning: method is never used: `sigmoid_prime` [INFO] [stderr] --> src/layer.rs:63:5 [INFO] [stderr] | [INFO] [stderr] 63 | fn sigmoid_prime(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(dead_code)]` on by default [INFO] [stderr] [INFO] [stderr] warning: method is never used: `evaluate` [INFO] [stderr] --> src/model.rs:132:5 [INFO] [stderr] | [INFO] [stderr] 132 | pub fn evaluate(test_set: Vec, set_labels: Vec<&str>) -> (usize, usize) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `predict` [INFO] [stderr] --> src/model.rs:136:5 [INFO] [stderr] | [INFO] [stderr] 136 | pub fn predict(prediction_set: T) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `adam_optimizer` [INFO] [stderr] --> src/model.rs:140:5 [INFO] [stderr] | [INFO] [stderr] 140 | fn adam_optimizer(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `gradient_descent` [INFO] [stderr] --> src/model.rs:147:5 [INFO] [stderr] | [INFO] [stderr] 147 | fn gradient_descent(&mut self) { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: method is never used: `mean_squared_error` [INFO] [stderr] --> src/model.rs:155:5 [INFO] [stderr] | [INFO] [stderr] 155 | fn mean_squared_error(&mut self, prediction: Array2, target: Array2) -> Array2 { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: 17 warnings emitted [INFO] [stderr] [INFO] [stderr] Finished dev [unoptimized + debuginfo] target(s) in 20.18s [INFO] running `"docker" "inspect" "ede198f440ba4f576ea86faaf90da73b80a36e630558e68e483345faeaec66ef"` [INFO] running `"docker" "rm" "-f" "ede198f440ba4f576ea86faaf90da73b80a36e630558e68e483345faeaec66ef"` [INFO] [stdout] ede198f440ba4f576ea86faaf90da73b80a36e630558e68e483345faeaec66ef