[INFO] fetching crate sklears-multiclass 0.1.0-alpha.1... [INFO] testing sklears-multiclass-0.1.0-alpha.1 against master#c90bcb9571b7aab0d8beaa2ce8a998ffaf079d38 for pr-146098-8 [INFO] extracting crate sklears-multiclass 0.1.0-alpha.1 into /workspace/builds/worker-4-tc1/source [INFO] started tweaking crates.io crate sklears-multiclass 0.1.0-alpha.1 [INFO] finished tweaking crates.io crate sklears-multiclass 0.1.0-alpha.1 [INFO] tweaked toml for crates.io crate sklears-multiclass 0.1.0-alpha.1 written to /workspace/builds/worker-4-tc1/source/Cargo.toml [INFO] validating manifest of crates.io crate sklears-multiclass 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-multiclass 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 ... 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"/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] 0c2ee60ecc390a79a0530cb1c5531075d6385d44bd86a4b15bb77e191e2db3fe [INFO] running `Command { std: "docker" "start" "-a" "0c2ee60ecc390a79a0530cb1c5531075d6385d44bd86a4b15bb77e191e2db3fe", kill_on_drop: false }` [INFO] running `Command { std: "docker" "inspect" "0c2ee60ecc390a79a0530cb1c5531075d6385d44bd86a4b15bb77e191e2db3fe", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "0c2ee60ecc390a79a0530cb1c5531075d6385d44bd86a4b15bb77e191e2db3fe", kill_on_drop: false }` [INFO] [stdout] 0c2ee60ecc390a79a0530cb1c5531075d6385d44bd86a4b15bb77e191e2db3fe [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-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] dfbee99bc61464ccd190f81b50ad22ff8574f323a1ea48adccc68a3f753ebb2e [INFO] running `Command { std: "docker" "start" "-a" "dfbee99bc61464ccd190f81b50ad22ff8574f323a1ea48adccc68a3f753ebb2e", kill_on_drop: false }` [INFO] [stderr] Compiling libc v0.2.176 [INFO] [stderr] Compiling cfg-if v1.0.3 [INFO] [stderr] Compiling proc-macro2 v1.0.101 [INFO] [stderr] Compiling unicode-ident v1.0.19 [INFO] [stderr] Compiling libm v0.2.15 [INFO] [stderr] Compiling serde_core v1.0.228 [INFO] [stderr] Compiling quote v1.0.41 [INFO] [stderr] Compiling num-traits v0.2.19 [INFO] [stderr] Compiling zerocopy v0.8.27 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[stderr] Compiling serde_spanned v1.0.2 [INFO] [stderr] Compiling num-iter v0.1.45 [INFO] [stderr] Compiling toml_writer v1.0.3 [INFO] [stderr] Compiling num v0.4.3 [INFO] [stderr] Compiling smallvec v1.15.1 [INFO] [stderr] Compiling array-init v2.1.0 [INFO] [stderr] Compiling toml v0.9.7 [INFO] [stderr] Compiling zstd v0.13.3 [INFO] [stderr] Compiling zip v5.1.1 [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-autograd 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-multiclass v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [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: `rayon::prelude` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fold_idx` [INFO] [stdout] --> src/advanced/stacking.rs:603:14 [INFO] [stdout] | [INFO] [stdout] 603 | for (fold_idx, (train_indices, val_indices)) in folds.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fold_idx` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `increasing` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:221:16 [INFO] [stdout] | [INFO] [stdout] 221 | pub fn new(increasing: bool) -> Self { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_increasing` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `calibrator` [INFO] [stdout] --> src/calibration/mod.rs:637:33 [INFO] [stdout] | [INFO] [stdout] 637 | if let Some(calibrator) = fold_calibrators.first() { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_calibrator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1061:17 [INFO] [stdout] | [INFO] [stdout] 1061 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1064:17 [INFO] [stdout] | [INFO] [stdout] 1064 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/core/ecoc.rs:1188:13 [INFO] [stdout] | [INFO] [stdout] 1188 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/ecoc.rs:1397:14 [INFO] [stdout] | [INFO] [stdout] 1397 | 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: `result` [INFO] [stdout] --> src/core/ecoc.rs:1595:13 [INFO] [stdout] | [INFO] [stdout] 1595 | let result = Array1::::zeros(n_samples); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_result` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_one.rs:183:14 [INFO] [stdout] | [INFO] [stdout] 183 | 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_classes` [INFO] [stdout] --> src/core/one_vs_one.rs:775:13 [INFO] [stdout] | [INFO] [stdout] 775 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/core/one_vs_one.rs:832:9 [INFO] [stdout] | [INFO] [stdout] 832 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_rest.rs:184:14 [INFO] [stdout] | [INFO] [stdout] 184 | 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/ensemble/dynamic_ensemble.rs:365:25 [INFO] [stdout] | [INFO] [stdout] 365 | 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: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:560:22 [INFO] [stdout] | [INFO] [stdout] 560 | for (idx, &classifier_idx) in [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:669:22 [INFO] [stdout] | [INFO] [stdout] 669 | for &idx in neighbor_indices { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:506:25 [INFO] [stdout] | [INFO] [stdout] 506 | 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: value assigned to `stopped_early` is never read [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:570:37 [INFO] [stdout] | [INFO] [stdout] 570 | let mut stopped_early = 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: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:319:14 [INFO] [stdout] | [INFO] [stdout] 319 | 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: `estimator_idx` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:330:13 [INFO] [stdout] | [INFO] [stdout] 330 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:439:9 [INFO] [stdout] | [INFO] [stdout] 439 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov_matrix` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:458:17 [INFO] [stdout] | [INFO] [stdout] 458 | let cov_matrix = centered.t().dot(¢ered) / (X_subset.nrows() as f64 - 1.0); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cov_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:668:14 [INFO] [stdout] | [INFO] [stdout] 668 | 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/incremental/drift_detection.rs:203:13 [INFO] [stdout] | [INFO] [stdout] 203 | let mean = self.total_sum / n as f64; [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:149:25 [INFO] [stdout] | [INFO] [stdout] 149 | let (n_samples, n_classes) = test_scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:188:25 [INFO] [stdout] | [INFO] [stdout] 188 | let (n_samples, n_classes) = scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: variable `position` is assigned to, but never used [INFO] [stdout] --> src/uncertainty/conformal.rs:284:13 [INFO] [stdout] | [INFO] [stdout] 284 | let mut position = 0; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: consider using `_position` instead [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `position` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:290:17 [INFO] [stdout] | [INFO] [stdout] 290 | position = i + 1; [INFO] [stdout] | ^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `conformity_score` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:378:36 [INFO] [stdout] | [INFO] [stdout] 378 | let mut conformity_score = 0.0; [INFO] [stdout] | ^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:14 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:25 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/mod.rs:126:14 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:126:25 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:162:25 [INFO] [stdout] | [INFO] [stdout] 162 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/boosting.rs:266:14 [INFO] [stdout] | [INFO] [stdout] 266 | 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/dynamic_ensemble.rs:362:25 [INFO] [stdout] | [INFO] [stdout] 362 | 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: `validation_labels` [INFO] [stdout] --> src/dynamic_ensemble.rs:531:13 [INFO] [stdout] | [INFO] [stdout] 531 | let validation_labels = &self.base_estimator.validation_y; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_validation_labels` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:300:17 [INFO] [stdout] | [INFO] [stdout] 300 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:303:17 [INFO] [stdout] | [INFO] [stdout] 303 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/ecoc.rs:427:13 [INFO] [stdout] | [INFO] [stdout] 427 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ecoc.rs:565:14 [INFO] [stdout] | [INFO] [stdout] 565 | 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/one_vs_one.rs:185:14 [INFO] [stdout] | [INFO] [stdout] 185 | 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_classes` [INFO] [stdout] --> src/one_vs_one.rs:658:13 [INFO] [stdout] | [INFO] [stdout] 658 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/one_vs_one.rs:715:9 [INFO] [stdout] | [INFO] [stdout] 715 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/one_vs_rest.rs:186:14 [INFO] [stdout] | [INFO] [stdout] 186 | 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/rotation_forest.rs:301:14 [INFO] [stdout] | [INFO] [stdout] 301 | 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: `estimator_idx` [INFO] [stdout] --> src/rotation_forest.rs:312:13 [INFO] [stdout] | [INFO] [stdout] 312 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/rotation_forest.rs:421:9 [INFO] [stdout] | [INFO] [stdout] 421 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: type `IsotonicPoint` is more private than the item `IsotonicRegression::points` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:26:5 [INFO] [stdout] | [INFO] [stdout] 26 | pub points: Vec, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ field `IsotonicRegression::points` is reachable at visibility `pub` [INFO] [stdout] | [INFO] [stdout] note: but type `IsotonicPoint` is only usable at visibility `pub(self)` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:13:1 [INFO] [stdout] | [INFO] [stdout] 13 | struct IsotonicPoint { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] = note: `#[warn(private_interfaces)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `dev` profile [unoptimized + debuginfo] target(s) in 3m 56s [INFO] running `Command { std: "docker" "inspect" "dfbee99bc61464ccd190f81b50ad22ff8574f323a1ea48adccc68a3f753ebb2e", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "dfbee99bc61464ccd190f81b50ad22ff8574f323a1ea48adccc68a3f753ebb2e", kill_on_drop: false }` [INFO] [stdout] dfbee99bc61464ccd190f81b50ad22ff8574f323a1ea48adccc68a3f753ebb2e [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-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] 2c02fb9d5a8acdab2ec9a3133cfa18d44e0e154be23b42431f040cdf7d39a560 [INFO] running `Command { std: "docker" "start" "-a" "2c02fb9d5a8acdab2ec9a3133cfa18d44e0e154be23b42431f040cdf7d39a560", kill_on_drop: false }` [INFO] [stderr] Compiling rustix v1.1.2 [INFO] [stderr] Compiling linux-raw-sys v0.11.0 [INFO] [stderr] Compiling bitflags v2.9.4 [INFO] [stderr] Compiling fastrand v2.3.0 [INFO] [stderr] Compiling wait-timeout v0.2.1 [INFO] [stderr] Compiling quick-error v1.2.3 [INFO] [stderr] Compiling bit-vec v0.8.0 [INFO] [stderr] Compiling rand_xorshift v0.4.0 [INFO] [stderr] Compiling unarray v0.1.4 [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [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: `rayon::prelude` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fold_idx` [INFO] [stdout] --> src/advanced/stacking.rs:603:14 [INFO] [stdout] | [INFO] [stdout] 603 | for (fold_idx, (train_indices, val_indices)) in folds.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fold_idx` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `increasing` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:221:16 [INFO] [stdout] | [INFO] [stdout] 221 | pub fn new(increasing: bool) -> Self { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_increasing` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `calibrator` [INFO] [stdout] --> src/calibration/mod.rs:637:33 [INFO] [stdout] | [INFO] [stdout] 637 | if let Some(calibrator) = fold_calibrators.first() { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_calibrator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1061:17 [INFO] [stdout] | [INFO] [stdout] 1061 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1064:17 [INFO] [stdout] | [INFO] [stdout] 1064 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/core/ecoc.rs:1188:13 [INFO] [stdout] | [INFO] [stdout] 1188 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/ecoc.rs:1397:14 [INFO] [stdout] | [INFO] [stdout] 1397 | 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: `result` [INFO] [stdout] --> src/core/ecoc.rs:1595:13 [INFO] [stdout] | [INFO] [stdout] 1595 | let result = Array1::::zeros(n_samples); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_result` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_one.rs:183:14 [INFO] [stdout] | [INFO] [stdout] 183 | 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_classes` [INFO] [stdout] --> src/core/one_vs_one.rs:775:13 [INFO] [stdout] | [INFO] [stdout] 775 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/core/one_vs_one.rs:832:9 [INFO] [stdout] | [INFO] [stdout] 832 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_rest.rs:184:14 [INFO] [stdout] | [INFO] [stdout] 184 | 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/ensemble/dynamic_ensemble.rs:365:25 [INFO] [stdout] | [INFO] [stdout] 365 | 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: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:560:22 [INFO] [stdout] | [INFO] [stdout] 560 | for (idx, &classifier_idx) in [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:669:22 [INFO] [stdout] | [INFO] [stdout] 669 | for &idx in neighbor_indices { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:506:25 [INFO] [stdout] | [INFO] [stdout] 506 | 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: value assigned to `stopped_early` is never read [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:570:37 [INFO] [stdout] | [INFO] [stdout] 570 | let mut stopped_early = 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: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:319:14 [INFO] [stdout] | [INFO] [stdout] 319 | 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: `estimator_idx` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:330:13 [INFO] [stdout] | [INFO] [stdout] 330 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:439:9 [INFO] [stdout] | [INFO] [stdout] 439 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov_matrix` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:458:17 [INFO] [stdout] | [INFO] [stdout] 458 | let cov_matrix = centered.t().dot(¢ered) / (X_subset.nrows() as f64 - 1.0); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cov_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:668:14 [INFO] [stdout] | [INFO] [stdout] 668 | 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/incremental/drift_detection.rs:203:13 [INFO] [stdout] | [INFO] [stdout] 203 | let mean = self.total_sum / n as f64; [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:149:25 [INFO] [stdout] | [INFO] [stdout] 149 | let (n_samples, n_classes) = test_scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:188:25 [INFO] [stdout] | [INFO] [stdout] 188 | let (n_samples, n_classes) = scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: variable `position` is assigned to, but never used [INFO] [stdout] --> src/uncertainty/conformal.rs:284:13 [INFO] [stdout] | [INFO] [stdout] 284 | let mut position = 0; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: consider using `_position` instead [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `position` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:290:17 [INFO] [stdout] | [INFO] [stdout] 290 | position = i + 1; [INFO] [stdout] | ^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `conformity_score` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:378:36 [INFO] [stdout] | [INFO] [stdout] 378 | let mut conformity_score = 0.0; [INFO] [stdout] | ^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:14 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:25 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/mod.rs:126:14 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:126:25 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:162:25 [INFO] [stdout] | [INFO] [stdout] 162 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/boosting.rs:266:14 [INFO] [stdout] | [INFO] [stdout] 266 | 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/dynamic_ensemble.rs:362:25 [INFO] [stdout] | [INFO] [stdout] 362 | 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: `validation_labels` [INFO] [stdout] --> src/dynamic_ensemble.rs:531:13 [INFO] [stdout] | [INFO] [stdout] 531 | let validation_labels = &self.base_estimator.validation_y; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_validation_labels` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:300:17 [INFO] [stdout] | [INFO] [stdout] 300 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:303:17 [INFO] [stdout] | [INFO] [stdout] 303 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/ecoc.rs:427:13 [INFO] [stdout] | [INFO] [stdout] 427 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ecoc.rs:565:14 [INFO] [stdout] | [INFO] [stdout] 565 | 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/one_vs_one.rs:185:14 [INFO] [stdout] | [INFO] [stdout] 185 | 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_classes` [INFO] [stdout] --> src/one_vs_one.rs:658:13 [INFO] [stdout] | [INFO] [stdout] 658 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/one_vs_one.rs:715:9 [INFO] [stdout] | [INFO] [stdout] 715 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/one_vs_rest.rs:186:14 [INFO] [stdout] | [INFO] [stdout] 186 | 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/rotation_forest.rs:301:14 [INFO] [stdout] | [INFO] [stdout] 301 | 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: `estimator_idx` [INFO] [stdout] --> src/rotation_forest.rs:312:13 [INFO] [stdout] | [INFO] [stdout] 312 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/rotation_forest.rs:421:9 [INFO] [stdout] | [INFO] [stdout] 421 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: type `IsotonicPoint` is more private than the item `IsotonicRegression::points` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:26:5 [INFO] [stdout] | [INFO] [stdout] 26 | pub points: Vec, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ field `IsotonicRegression::points` is reachable at visibility `pub` [INFO] [stdout] | [INFO] [stdout] note: but type `IsotonicPoint` is only usable at visibility `pub(self)` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:13:1 [INFO] [stdout] | [INFO] [stdout] 13 | struct IsotonicPoint { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] = note: `#[warn(private_interfaces)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Compiling bit-set v0.8.0 [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-multiclass v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused import: `rayon::prelude` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [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: `rayon::prelude` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use rayon::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `fold_idx` [INFO] [stdout] --> src/advanced/stacking.rs:603:14 [INFO] [stdout] | [INFO] [stdout] 603 | for (fold_idx, (train_indices, val_indices)) in folds.iter().enumerate() { [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fold_idx` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights_low_norm` [INFO] [stdout] --> src/calibration/dirichlet_calibration.rs:554:13 [INFO] [stdout] | [INFO] [stdout] 554 | let weights_low_norm: f64 = calibrator_low_reg.weights.iter().map(|&x| x.abs()).sum(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights_low_norm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights_high_norm` [INFO] [stdout] --> src/calibration/dirichlet_calibration.rs:555:13 [INFO] [stdout] | [INFO] [stdout] 555 | let weights_high_norm: f64 = calibrator_high_reg.weights.iter().map(|&x| x.abs()).sum(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights_high_norm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `increasing` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:221:16 [INFO] [stdout] | [INFO] [stdout] 221 | pub fn new(increasing: bool) -> Self { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_increasing` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `initial_temp` [INFO] [stdout] --> src/calibration/temperature_scaling.rs:553:13 [INFO] [stdout] | [INFO] [stdout] 553 | let initial_temp = scaler.temperature; [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_initial_temp` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `calibrator` [INFO] [stdout] --> src/calibration/mod.rs:637:33 [INFO] [stdout] | [INFO] [stdout] 637 | if let Some(calibrator) = fold_calibrators.first() { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_calibrator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1061:17 [INFO] [stdout] | [INFO] [stdout] 1061 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/core/ecoc.rs:1064:17 [INFO] [stdout] | [INFO] [stdout] 1064 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/core/ecoc.rs:1188:13 [INFO] [stdout] | [INFO] [stdout] 1188 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/ecoc.rs:1397:14 [INFO] [stdout] | [INFO] [stdout] 1397 | 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: `result` [INFO] [stdout] --> src/core/ecoc.rs:1595:13 [INFO] [stdout] | [INFO] [stdout] 1595 | let result = Array1::::zeros(n_samples); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_result` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_one.rs:183:14 [INFO] [stdout] | [INFO] [stdout] 183 | 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_classes` [INFO] [stdout] --> src/core/one_vs_one.rs:775:13 [INFO] [stdout] | [INFO] [stdout] 775 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/core/one_vs_one.rs:832:9 [INFO] [stdout] | [INFO] [stdout] 832 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/core/one_vs_rest.rs:184:14 [INFO] [stdout] | [INFO] [stdout] 184 | 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/ensemble/dynamic_ensemble.rs:365:25 [INFO] [stdout] | [INFO] [stdout] 365 | 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: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:560:22 [INFO] [stdout] | [INFO] [stdout] 560 | for (idx, &classifier_idx) in [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `idx` [INFO] [stdout] --> src/ensemble/dynamic_ensemble.rs:669:22 [INFO] [stdout] | [INFO] [stdout] 669 | for &idx in neighbor_indices { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:506:25 [INFO] [stdout] | [INFO] [stdout] 506 | 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: value assigned to `stopped_early` is never read [INFO] [stdout] --> src/ensemble/gradient_boosting.rs:570:37 [INFO] [stdout] | [INFO] [stdout] 570 | let mut stopped_early = 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: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:319:14 [INFO] [stdout] | [INFO] [stdout] 319 | 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: `estimator_idx` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:330:13 [INFO] [stdout] | [INFO] [stdout] 330 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:439:9 [INFO] [stdout] | [INFO] [stdout] 439 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov_matrix` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:458:17 [INFO] [stdout] | [INFO] [stdout] 458 | let cov_matrix = centered.t().dot(¢ered) / (X_subset.nrows() as f64 - 1.0); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cov_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ensemble/rotation_forest.rs:668:14 [INFO] [stdout] | [INFO] [stdout] 668 | 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/incremental/drift_detection.rs:203:13 [INFO] [stdout] | [INFO] [stdout] 203 | let mean = self.total_sum / n as f64; [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/incremental/drift_detection.rs:359:13 [INFO] [stdout] | [INFO] [stdout] 359 | for i in 0..50 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/incremental/drift_detection.rs:370:13 [INFO] [stdout] | [INFO] [stdout] 370 | for i in 0..50 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:149:25 [INFO] [stdout] | [INFO] [stdout] 149 | let (n_samples, n_classes) = test_scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/conformal.rs:188:25 [INFO] [stdout] | [INFO] [stdout] 188 | let (n_samples, n_classes) = scores.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: variable `position` is assigned to, but never used [INFO] [stdout] --> src/uncertainty/conformal.rs:284:13 [INFO] [stdout] | [INFO] [stdout] 284 | let mut position = 0; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: consider using `_position` instead [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `position` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:290:17 [INFO] [stdout] | [INFO] [stdout] 290 | position = i + 1; [INFO] [stdout] | ^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `conformity_score` is never read [INFO] [stdout] --> src/uncertainty/conformal.rs:378:36 [INFO] [stdout] | [INFO] [stdout] 378 | let mut conformity_score = 0.0; [INFO] [stdout] | ^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:14 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/intervals.rs:99:25 [INFO] [stdout] | [INFO] [stdout] 99 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/uncertainty/mod.rs:126:14 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.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_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:126:25 [INFO] [stdout] | [INFO] [stdout] 126 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_classes` [INFO] [stdout] --> src/uncertainty/mod.rs:162:25 [INFO] [stdout] | [INFO] [stdout] 162 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `predictions` [INFO] [stdout] --> src/uncertainty/mod.rs:304:13 [INFO] [stdout] | [INFO] [stdout] 304 | let predictions = array![0, 1, 2]; [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_predictions` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `probabilities` [INFO] [stdout] --> src/uncertainty/mod.rs:305:13 [INFO] [stdout] | [INFO] [stdout] 305 | let probabilities = array![[0.8, 0.1, 0.1], [0.1, 0.8, 0.1], [0.1, 0.1, 0.8]]; [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_probabilities` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `quantifier` [INFO] [stdout] --> src/uncertainty/mod.rs:307:13 [INFO] [stdout] | [INFO] [stdout] 307 | let quantifier = UncertaintyQuantifier::new(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_quantifier` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/boosting.rs:266:14 [INFO] [stdout] | [INFO] [stdout] 266 | 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/dynamic_ensemble.rs:362:25 [INFO] [stdout] | [INFO] [stdout] 362 | 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: `validation_labels` [INFO] [stdout] --> src/dynamic_ensemble.rs:531:13 [INFO] [stdout] | [INFO] [stdout] 531 | let validation_labels = &self.base_estimator.validation_y; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_validation_labels` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:300:17 [INFO] [stdout] | [INFO] [stdout] 300 | for i in 0..(n_classes / 2) { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/ecoc.rs:303:17 [INFO] [stdout] | [INFO] [stdout] 303 | for i in (n_classes / 2)..n_classes { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `attempt` [INFO] [stdout] --> src/ecoc.rs:427:13 [INFO] [stdout] | [INFO] [stdout] 427 | for attempt in 0..max_attempts { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/ecoc.rs:565:14 [INFO] [stdout] | [INFO] [stdout] 565 | 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/one_vs_one.rs:185:14 [INFO] [stdout] | [INFO] [stdout] 185 | 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_classes` [INFO] [stdout] --> src/one_vs_one.rs:658:13 [INFO] [stdout] | [INFO] [stdout] 658 | let n_classes = self.base_estimator.classes.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `method` [INFO] [stdout] --> src/one_vs_one.rs:715:9 [INFO] [stdout] | [INFO] [stdout] 715 | method: &ConsensusMethod, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/one_vs_rest.rs:186:14 [INFO] [stdout] | [INFO] [stdout] 186 | 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/rotation_forest.rs:301:14 [INFO] [stdout] | [INFO] [stdout] 301 | 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: `estimator_idx` [INFO] [stdout] --> src/rotation_forest.rs:312:13 [INFO] [stdout] | [INFO] [stdout] 312 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/rotation_forest.rs:421:9 [INFO] [stdout] | [INFO] [stdout] 421 | rng: &mut Random, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: type `isotonic_regression::IsotonicPoint` is more private than the item `isotonic_regression::IsotonicRegression::points` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:26:5 [INFO] [stdout] | [INFO] [stdout] 26 | pub points: Vec, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ field `isotonic_regression::IsotonicRegression::points` is reachable at visibility `pub` [INFO] [stdout] | [INFO] [stdout] note: but type `isotonic_regression::IsotonicPoint` is only usable at visibility `pub(self)` [INFO] [stdout] --> src/calibration/isotonic_regression.rs:13:1 [INFO] [stdout] | [INFO] [stdout] 13 | struct IsotonicPoint { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] = note: `#[warn(private_interfaces)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `test` profile [unoptimized + debuginfo] target(s) in 17.89s [INFO] running `Command { std: "docker" "inspect" "2c02fb9d5a8acdab2ec9a3133cfa18d44e0e154be23b42431f040cdf7d39a560", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "2c02fb9d5a8acdab2ec9a3133cfa18d44e0e154be23b42431f040cdf7d39a560", kill_on_drop: false }` [INFO] [stdout] 2c02fb9d5a8acdab2ec9a3133cfa18d44e0e154be23b42431f040cdf7d39a560 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-4-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] b3e0fa5ecac26607adb59745d061aecebe83acaf28ff40c9f83c5ccd83e5fad8 [INFO] running `Command { std: "docker" "start" "-a" "b3e0fa5ecac26607adb59745d061aecebe83acaf28ff40c9f83c5ccd83e5fad8", kill_on_drop: false }` [INFO] [stderr] warning: unused import: `rayon::prelude` [INFO] [stdout] [INFO] [stderr] --> src/ensemble/dynamic_ensemble.rs:7:5 [INFO] [stdout] running 223 tests [INFO] [stderr] | [INFO] [stderr] 7 | use rayon::prelude::*; [INFO] [stderr] | ^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused import: `rayon::prelude` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:7:5 [INFO] [stderr] | [INFO] [stderr] 7 | use rayon::prelude::*; [INFO] [stderr] | ^^^^^^^^^^^^^^ [INFO] [stderr] [INFO] [stderr] warning: unused variable: `fold_idx` [INFO] [stderr] --> src/advanced/stacking.rs:603:14 [INFO] [stderr] | [INFO] [stderr] 603 | for (fold_idx, (train_indices, val_indices)) in folds.iter().enumerate() { [INFO] [stderr] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_fold_idx` [INFO] [stderr] | [INFO] [stderr] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stderr] [INFO] [stderr] warning: unused variable: `increasing` [INFO] [stderr] --> src/calibration/isotonic_regression.rs:221:16 [INFO] [stderr] | [INFO] [stderr] 221 | pub fn new(increasing: bool) -> Self { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_increasing` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `calibrator` [INFO] [stderr] --> src/calibration/mod.rs:637:33 [INFO] [stderr] | [INFO] [stderr] 637 | if let Some(calibrator) = fold_calibrators.first() { [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_calibrator` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/core/ecoc.rs:1061:17 [INFO] [stderr] | [INFO] [stderr] 1061 | for i in 0..(n_classes / 2) { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/core/ecoc.rs:1064:17 [INFO] [stderr] | [INFO] [stderr] 1064 | for i in (n_classes / 2)..n_classes { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `attempt` [INFO] [stderr] --> src/core/ecoc.rs:1188:13 [INFO] [stderr] | [INFO] [stderr] 1188 | for attempt in 0..max_attempts { [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/core/ecoc.rs:1397:14 [INFO] [stderr] | [INFO] [stderr] 1397 | 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: `result` [INFO] [stderr] --> src/core/ecoc.rs:1595:13 [INFO] [stderr] | [INFO] [stderr] 1595 | let result = Array1::::zeros(n_samples); [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_result` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/core/one_vs_one.rs:183:14 [INFO] [stderr] | [INFO] [stderr] 183 | 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_classes` [INFO] [stderr] --> src/core/one_vs_one.rs:775:13 [INFO] [stderr] | [INFO] [stderr] 775 | let n_classes = self.base_estimator.classes.len(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `method` [INFO] [stderr] --> src/core/one_vs_one.rs:832:9 [INFO] [stderr] | [INFO] [stderr] 832 | method: &ConsensusMethod, [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/core/one_vs_rest.rs:184:14 [INFO] [stderr] | [INFO] [stderr] 184 | 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/ensemble/dynamic_ensemble.rs:365:25 [INFO] [stderr] | [INFO] [stderr] 365 | 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: `idx` [INFO] [stderr] --> src/ensemble/dynamic_ensemble.rs:560:22 [INFO] [stderr] | [INFO] [stderr] 560 | for (idx, &classifier_idx) in [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `idx` [INFO] [stderr] --> src/ensemble/dynamic_ensemble.rs:669:22 [INFO] [stderr] | [INFO] [stderr] 669 | for &idx in neighbor_indices { [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_features` [INFO] [stderr] --> src/ensemble/gradient_boosting.rs:506:25 [INFO] [stderr] | [INFO] [stderr] 506 | 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: value assigned to `stopped_early` is never read [INFO] [stderr] --> src/ensemble/gradient_boosting.rs:570:37 [INFO] [stderr] | [INFO] [stderr] 570 | let mut stopped_early = 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: `n_samples` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:319:14 [INFO] [stderr] | [INFO] [stderr] 319 | 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: `estimator_idx` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:330:13 [INFO] [stderr] | [INFO] [stderr] 330 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `rng` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:439:9 [INFO] [stderr] | [INFO] [stderr] 439 | rng: &mut Random, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `cov_matrix` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:458:17 [INFO] [stderr] | [INFO] [stderr] 458 | let cov_matrix = centered.t().dot(¢ered) / (X_subset.nrows() as f64 - 1.0); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cov_matrix` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/ensemble/rotation_forest.rs:668:14 [INFO] [stderr] | [INFO] [stderr] 668 | 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/incremental/drift_detection.rs:203:13 [INFO] [stderr] | [INFO] [stderr] 203 | let mean = self.total_sum / n as f64; [INFO] [stderr] | ^^^^ help: if this is intentional, prefix it with an underscore: `_mean` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_classes` [INFO] [stderr] --> src/uncertainty/conformal.rs:149:25 [INFO] [stderr] | [INFO] [stderr] 149 | let (n_samples, n_classes) = test_scores.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_classes` [INFO] [stderr] --> src/uncertainty/conformal.rs:188:25 [INFO] [stderr] | [INFO] [stderr] 188 | let (n_samples, n_classes) = scores.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: variable `position` is assigned to, but never used [INFO] [stderr] --> src/uncertainty/conformal.rs:284:13 [INFO] [stderr] | [INFO] [stderr] 284 | let mut position = 0; [INFO] [stderr] | ^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = note: consider using `_position` instead [INFO] [stderr] [INFO] [stderr] warning: value assigned to `position` is never read [INFO] [stderr] --> src/uncertainty/conformal.rs:290:17 [INFO] [stderr] | [INFO] [stderr] 290 | position = i + 1; [INFO] [stderr] | ^^^^^^^^^^^^^^^^ [INFO] [stderr] | [INFO] [stderr] = help: maybe it is overwritten before being read? [INFO] [stderr] [INFO] [stderr] warning: value assigned to `conformity_score` is never read [INFO] [stderr] --> src/uncertainty/conformal.rs:378:36 [INFO] [stderr] | [INFO] [stderr] 378 | let mut conformity_score = 0.0; [INFO] [stderr] | ^^^ [INFO] [stderr] | [INFO] [stderr] = help: maybe it is overwritten before being read? [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/uncertainty/intervals.rs:99:14 [INFO] [stderr] | [INFO] [stderr] 99 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_classes` [INFO] [stderr] --> src/uncertainty/intervals.rs:99:25 [INFO] [stderr] | [INFO] [stderr] 99 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/uncertainty/mod.rs:126:14 [INFO] [stderr] | [INFO] [stderr] 126 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_classes` [INFO] [stderr] --> src/uncertainty/mod.rs:126:25 [INFO] [stderr] | [INFO] [stderr] 126 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_classes` [INFO] [stderr] --> src/uncertainty/mod.rs:162:25 [INFO] [stderr] | [INFO] [stderr] 162 | let (n_samples, n_classes) = probabilities.dim(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/boosting.rs:266:14 [INFO] [stderr] | [INFO] [stderr] 266 | 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/dynamic_ensemble.rs:362:25 [INFO] [stderr] | [INFO] [stderr] 362 | 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: `validation_labels` [INFO] [stderr] --> src/dynamic_ensemble.rs:531:13 [INFO] [stderr] | [INFO] [stderr] 531 | let validation_labels = &self.base_estimator.validation_y; [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_validation_labels` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/ecoc.rs:300:17 [INFO] [stderr] | [INFO] [stderr] 300 | for i in 0..(n_classes / 2) { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/ecoc.rs:303:17 [INFO] [stderr] | [INFO] [stderr] 303 | for i in (n_classes / 2)..n_classes { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `attempt` [INFO] [stderr] --> src/ecoc.rs:427:13 [INFO] [stderr] | [INFO] [stderr] 427 | for attempt in 0..max_attempts { [INFO] [stderr] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_attempt` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/ecoc.rs:565:14 [INFO] [stderr] | [INFO] [stderr] 565 | 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/one_vs_one.rs:185:14 [INFO] [stderr] | [INFO] [stderr] 185 | 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_classes` [INFO] [stderr] --> src/one_vs_one.rs:658:13 [INFO] [stderr] | [INFO] [stderr] 658 | let n_classes = self.base_estimator.classes.len(); [INFO] [stderr] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_classes` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `method` [INFO] [stderr] --> src/one_vs_one.rs:715:9 [INFO] [stderr] | [INFO] [stderr] 715 | method: &ConsensusMethod, [INFO] [stderr] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_method` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `n_samples` [INFO] [stderr] --> src/one_vs_rest.rs:186:14 [INFO] [stderr] | [INFO] [stderr] 186 | 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/rotation_forest.rs:301:14 [INFO] [stderr] | [INFO] [stderr] 301 | 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: `estimator_idx` [INFO] [stderr] --> src/rotation_forest.rs:312:13 [INFO] [stderr] | [INFO] [stderr] 312 | for estimator_idx in 0..self.config.n_estimators { [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator_idx` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `rng` [INFO] [stderr] --> src/rotation_forest.rs:421:9 [INFO] [stderr] | [INFO] [stderr] 421 | rng: &mut Random, [INFO] [stderr] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stderr] [INFO] [stderr] warning: type `IsotonicPoint` is more private than the item `IsotonicRegression::points` [INFO] [stderr] --> src/calibration/isotonic_regression.rs:26:5 [INFO] [stderr] | [INFO] [stderr] 26 | pub points: Vec, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ field `IsotonicRegression::points` is reachable at visibility `pub` [INFO] [stderr] | [INFO] [stderr] note: but type `IsotonicPoint` is only usable at visibility `pub(self)` [INFO] [stderr] --> src/calibration/isotonic_regression.rs:13:1 [INFO] [stderr] | [INFO] [stderr] 13 | struct IsotonicPoint { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] = note: `#[warn(private_interfaces)]` on by default [INFO] [stderr] [INFO] [stderr] warning: `sklears-multiclass` (lib) generated 50 warnings (run `cargo fix --lib -p sklears-multiclass` to apply 43 suggestions) [INFO] [stderr] warning: unused variable: `weights_low_norm` [INFO] [stderr] --> src/calibration/dirichlet_calibration.rs:554:13 [INFO] [stderr] | [INFO] [stderr] 554 | let weights_low_norm: f64 = calibrator_low_reg.weights.iter().map(|&x| x.abs()).sum(); [INFO] [stderr] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights_low_norm` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `weights_high_norm` [INFO] [stderr] --> src/calibration/dirichlet_calibration.rs:555:13 [INFO] [stderr] | [INFO] [stderr] 555 | let weights_high_norm: f64 = calibrator_high_reg.weights.iter().map(|&x| x.abs()).sum(); [INFO] [stderr] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights_high_norm` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `initial_temp` [INFO] [stderr] --> src/calibration/temperature_scaling.rs:553:13 [INFO] [stderr] | [INFO] [stderr] 553 | let initial_temp = scaler.temperature; [INFO] [stderr] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_initial_temp` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/incremental/drift_detection.rs:359:13 [INFO] [stderr] | [INFO] [stderr] 359 | for i in 0..50 { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `i` [INFO] [stderr] --> src/incremental/drift_detection.rs:370:13 [INFO] [stderr] | [INFO] [stderr] 370 | for i in 0..50 { [INFO] [stderr] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `predictions` [INFO] [stderr] --> src/uncertainty/mod.rs:304:13 [INFO] [stderr] | [INFO] [stderr] 304 | let predictions = array![0, 1, 2]; [INFO] [stderr] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_predictions` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `probabilities` [INFO] [stderr] --> src/uncertainty/mod.rs:305:13 [INFO] [stderr] | [INFO] [stderr] 305 | let probabilities = array![[0.8, 0.1, 0.1], [0.1, 0.8, 0.1], [0.1, 0.1, 0.8]]; [INFO] [stderr] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_probabilities` [INFO] [stderr] [INFO] [stderr] warning: unused variable: `quantifier` [INFO] [stderr] --> src/uncertainty/mod.rs:307:13 [INFO] [stderr] | [INFO] [stderr] 307 | let quantifier = UncertaintyQuantifier::new(); [INFO] [stderr] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_quantifier` [INFO] [stderr] [INFO] [stderr] warning: type `isotonic_regression::IsotonicPoint` is more private than the item `isotonic_regression::IsotonicRegression::points` [INFO] [stderr] --> src/calibration/isotonic_regression.rs:26:5 [INFO] [stderr] | [INFO] [stderr] 26 | pub points: Vec, [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ field `isotonic_regression::IsotonicRegression::points` is reachable at visibility `pub` [INFO] [stderr] | [INFO] [stderr] note: but type `isotonic_regression::IsotonicPoint` is only usable at visibility `pub(self)` [INFO] [stderr] --> src/calibration/isotonic_regression.rs:13:1 [INFO] [stderr] | [INFO] [stderr] 13 | struct IsotonicPoint { [INFO] [stderr] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stderr] = note: `#[warn(private_interfaces)]` on by default [INFO] [stderr] [INFO] [stderr] warning: `sklears-multiclass` (lib test) generated 58 warnings (49 duplicates) (run `cargo fix --lib -p sklears-multiclass --tests` to apply 8 suggestions) [INFO] [stderr] Finished `test` profile [unoptimized + debuginfo] target(s) in 0.22s [INFO] [stderr] Running unittests src/lib.rs (/opt/rustwide/target/debug/deps/sklears_multiclass-9d6f53377587f9d8) [INFO] [stdout] test advanced::hierarchical::tests::test_hierarchical_classifier_creation ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_hierarchical_builder ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_hierarchy_creation ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_hierarchy_path_to_leaf ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_rbp_builder ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_nested_dichotomies_builder ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_rbp_basic ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_nested_dichotomies_basic ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_taxonomy_aware_builder ... ok [INFO] [stdout] test advanced::stacking::tests::test_adaptive_selection_rules ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_taxonomy_aware_classifier_creation ... ok [INFO] [stdout] test advanced::hierarchical::tests::test_taxonomy_creation ... ok [INFO] [stdout] test advanced::stacking::tests::test_adaptation_event_creation ... ok [INFO] [stdout] test advanced::stacking::tests::test_dynamic_meta_learner_selection ... ok [INFO] [stdout] test advanced::stacking::tests::test_adaptive_meta_learner_selection ... ok [INFO] [stdout] test advanced::stacking::tests::test_online_adaptation_configuration ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_basic ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_blending_method ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_builder ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_clone ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_configuration_methods ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_empty_base_estimators ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_creation ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_insufficient_classes ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_estimator_trait ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_cv_method ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_holdout_method ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_binary ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_mismatched_dimensions ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_empty_data ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_prediction_logits ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_passthrough ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_basic ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_transform_unfitted ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_calibration_function_trait ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_basic ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_decreasing ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_empty_data ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_extrapolation ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_numerical_stability ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_interpolation ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_mismatched_lengths ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_perfect_monotonic ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_single_point ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_isotonic_regression_with_weights ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_multiclass_isotonic_regression ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_multiclass_platt_scaling ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_multiclass_platt_scaling_dimension_mismatch ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_basic ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_calibration_function ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_empty_data ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_mismatched_lengths ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_sigmoid ... ok [INFO] [stdout] test calibration::platt_scaling::tests::test_platt_scaling_single_class ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_softmax ... ok [INFO] [stdout] test calibration::isotonic_regression::tests::test_pool_adjacent_violators_complex ... ok [INFO] [stdout] test advanced::stacking::tests::test_trained_data_with_dynamic_fields ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_softmax_numerical_stability ... ok [INFO] [stdout] test advanced::stacking::tests::test_stacking_predict_proba ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_binary_calibration_function ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_edge_cases ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_multiclass_temperature_scaling ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_mismatched_dimensions ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_positive_constraint ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_probabilities ... ok [INFO] [stdout] test calibration::tests::test_all_calibration_methods ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_empty_data ... ok [INFO] [stdout] test calibration::tests::test_calibrated_classifier_builder ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_basic ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_regularization ... ok [INFO] [stdout] test calibration::tests::test_calibration_config_default ... ok [INFO] [stdout] test calibration::tests::test_calibration_method_default ... ok [INFO] [stdout] test calibration::tests::test_stratified_kfold_invalid_splits ... ok [INFO] [stdout] test calibration::tests::test_stratified_kfold_split ... ok [INFO] [stdout] test core::ecoc::tests::test_code_matrix_dense ... ok [INFO] [stdout] test core::ecoc::tests::test_code_matrix_sparse ... ok [INFO] [stdout] test core::ecoc::tests::test_compression_ratio_calculation ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_builder ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_builder_sparse_options ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_classifier_creation ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_classifier_sparse_methods ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_config_default ... ok [INFO] [stdout] test calibration::tests::test_calibration_edge_cases ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_config_sparse_settings ... ok [INFO] [stdout] test core::ecoc::tests::test_ecoc_strategy_default ... ok [INFO] [stdout] test core::ecoc::tests::test_memory_usage_calculation ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_from_dense ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_creation ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_get_row ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_to_dense ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_threshold_clamping ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_basic ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_get_set ... ok [INFO] [stdout] test core::ecoc::tests::test_sparse_matrix_sparsity ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_clone ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_builder ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_estimator_trait ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_insufficient_classes ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_multiclass ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_config_default ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_config_default ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_configuration ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_multiclass_temperature_scaling_with_probabilities ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_builder ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_parallel_training ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_new_classes ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_partial_fit ... ok [INFO] [stdout] test ensemble::bagging::tests::test_bagging_warm_start_without_flag ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_basic ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_estimator_trait ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_clone ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_builder ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_insufficient_classes ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_reproducibility ... ok [INFO] [stdout] test ensemble::dynamic_ensemble::tests::test_dynamic_ensemble_selection_config_default ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_basic ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_builder ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_early_stopping_config_default ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_clone ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_accessor_methods ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_config_default ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_builder_with_new_features ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_config_with_new_fields ... ok [INFO] [stdout] test calibration::tests::test_calibrated_classifier_comprehensive ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_configuration_methods ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_detailed_training ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_feature_importances ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_huber_loss ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_insufficient_classes ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_early_stopping ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_loss_computation ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_loss_default ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_loss_functions ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_multiclass ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_multinomial_loss ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_empty_dataset ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_estimator_trait ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_warm_start ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_subsample ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_convergence ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_warm_start_config ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_feature_selection_strategy_default ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_warm_start_with_early_stopping ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_loss_function_computations ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_config_default ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_empty_dataset ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_basic ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_insufficient_classes ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_feature_subset_generation ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_rotation_matrix_creation ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_builder ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_config_default ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_configuration ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_builder ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_new_classes ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_without_flag ... ok [INFO] [stdout] test incremental::drift_detection::tests::test_adwin_detector ... ok [INFO] [stdout] test ensemble::rotation_forest::tests::test_rotation_forest_warm_start_partial_fit ... ok [INFO] [stdout] test incremental::drift_detection::tests::test_drift_status_enum ... ok [INFO] [stdout] test incremental::drift_detection::tests::test_page_hinkley_detector ... ok [INFO] [stdout] test incremental::drift_detection::tests::test_drift_detector_creation ... ok [INFO] [stdout] test incremental::memory_management::tests::test_memory_config_builder ... ok [INFO] [stdout] test incremental::memory_management::tests::test_add_example ... ok [INFO] [stdout] test incremental::memory_management::tests::test_class_weights ... ok [INFO] [stdout] test incremental::memory_management::tests::test_memory_manager_creation ... ok [INFO] [stdout] test incremental::online_learning::tests::test_online_learner_creation ... ok [INFO] [stdout] test incremental::memory_management::tests::test_sample_examples ... ok [INFO] [stdout] test incremental::online_learning::tests::test_builder_pattern ... ok [INFO] [stdout] test incremental::online_learning::tests::test_partial_fit_batch ... ok [INFO] [stdout] test incremental::online_learning::tests::test_partial_fit_single ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_confidence_detailed ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_combined_confidence ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_confidence_builder ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_entropy_confidence ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_margin_confidence ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_temperature_scaling ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_ratio_confidence ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_conformal_predictor_builder ... ok [INFO] [stdout] test uncertainty::confidence::tests::test_max_probability_confidence ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_conformal_predictor_creation ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_mismatched_dimensions ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_empty_calibration_data ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_jackknife_conformal_score ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_prediction_set_coverage ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_raps_conformal_score ... ok [INFO] [stdout] test uncertainty::conformal::tests::test_split_conformal_fit_predict ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_bayesian_intervals ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_detailed_intervals ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_interval_estimator_builder ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_interval_estimator_creation ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_normal_approximation_intervals ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_normal_quantile ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_wilson_intervals ... ok [INFO] [stdout] test uncertainty::tests::test_uncertainty_decomposition ... ok [INFO] [stdout] test uncertainty::tests::test_uncertainty_quantifier_builder ... ok [INFO] [stdout] test uncertainty::tests::test_uncertainty_quantifier_creation ... ok [INFO] [stdout] test uncertainty::tests::test_uncertainty_result_structure ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_batch_config_creation ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_batch_iterator ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_batch_processing ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_batch_processing_probabilities ... ok [INFO] [stdout] test uncertainty::intervals::tests::test_bootstrap_intervals ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_batch_processor_optimal_size_calculation ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_empty_data_handling ... ok [INFO] [stdout] test utils::caching::tests::test_array_key_creation ... ok [INFO] [stdout] test utils::caching::tests::test_cache_clear ... ok [INFO] [stdout] test utils::caching::tests::test_cache_config_default ... ok [INFO] [stdout] test utils::caching::tests::test_cache_disabled ... ok [INFO] [stdout] test utils::caching::tests::test_cache_eviction ... ok [INFO] [stdout] test utils::caching::tests::test_cache_stats ... ok [INFO] [stdout] test utils::caching::tests::test_prediction_cache_basic ... ok [INFO] [stdout] test utils::caching::tests::test_prediction_cache_proba ... ok [INFO] [stdout] test utils::evaluation::tests::test_classification_report ... ok [INFO] [stdout] test utils::evaluation::tests::test_confusion_matrix_creation ... ok [INFO] [stdout] test utils::evaluation::tests::test_confusion_matrix_metrics ... ok [INFO] [stdout] test utils::evaluation::tests::test_empty_arrays ... ok [INFO] [stdout] test utils::evaluation::tests::test_mismatched_lengths ... ok [INFO] [stdout] test utils::evaluation::tests::test_per_class_metrics ... ok [INFO] [stdout] test utils::batch_optimization::tests::test_performance_stats ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_all_new_loss_functions ... ok [INFO] [stdout] test ensemble::gradient_boosting::tests::test_gradient_boosting_reproducibility ... ok [INFO] [stdout] test calibration::dirichlet_calibration::tests::test_dirichlet_calibration_with_cv ... ok [INFO] [stdout] test calibration::temperature_scaling::tests::test_temperature_scaling_convergence ... ok [INFO] [stdout] [INFO] [stdout] test result: ok. 223 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.10s [INFO] [stdout] [INFO] [stderr] Doc-tests sklears_multiclass [INFO] [stdout] [INFO] [stdout] running 18 tests [INFO] [stdout] test src/calibration/mod.rs - calibration (line 16) ... ignored [INFO] [stdout] test src/advanced/stacking.rs - advanced::stacking::MulticlassStackingClassifier (line 207) ... ok [INFO] [stdout] test src/core/ecoc.rs - core::ecoc::ECOCClassifier (line 710) ... ok [INFO] [stdout] test src/core/one_vs_rest.rs - core::one_vs_rest::OneVsRestClassifier (line 34) ... ok [INFO] [stdout] test src/dynamic_ensemble.rs - dynamic_ensemble::DynamicEnsembleSelectionClassifier (line 137) ... ok [INFO] [stdout] test src/boosting.rs - boosting::GradientBoostingClassifier (line 700) ... ok [INFO] [stdout] test src/advanced/hierarchical.rs - advanced::hierarchical::HierarchicalClassifier (line 917) ... ok [INFO] [stdout] test src/core/one_vs_one.rs - core::one_vs_one::OneVsOneClassifier (line 34) ... ok [INFO] [stdout] test src/advanced/hierarchical.rs - advanced::hierarchical::TaxonomyAwareClassifier (line 1155) ... ok [INFO] [stdout] test src/ensemble/bagging.rs - ensemble::bagging::BaggingClassifier (line 59) ... ok [INFO] [stdout] test src/uncertainty/mod.rs - uncertainty (line 16) ... ignored [INFO] [stdout] test src/one_vs_rest.rs - one_vs_rest::OneVsRestClassifier (line 36) ... ok [INFO] [stdout] test src/ensemble/dynamic_ensemble.rs - ensemble::dynamic_ensemble::DynamicEnsembleSelectionClassifier (line 140) ... ok [INFO] [stdout] test src/ensemble/rotation_forest.rs - ensemble::rotation_forest::RotationForestClassifier (line 97) ... ok [INFO] [stdout] test src/ensemble/gradient_boosting.rs - ensemble::gradient_boosting::GradientBoostingClassifier (line 251) ... ok [INFO] [stdout] test src/ecoc.rs - ecoc::ECOCClassifier (line 75) ... ok [INFO] [stdout] test src/one_vs_one.rs - one_vs_one::OneVsOneClassifier (line 36) ... ok [INFO] [stdout] test src/rotation_forest.rs - rotation_forest::RotationForestClassifier (line 91) ... ok [INFO] [stdout] [INFO] [stdout] test result: ok. 16 passed; 0 failed; 2 ignored; 0 measured; 0 filtered out; finished in 6.82s [INFO] [stdout] [INFO] running `Command { std: "docker" "inspect" "b3e0fa5ecac26607adb59745d061aecebe83acaf28ff40c9f83c5ccd83e5fad8", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "b3e0fa5ecac26607adb59745d061aecebe83acaf28ff40c9f83c5ccd83e5fad8", kill_on_drop: false }` [INFO] [stdout] b3e0fa5ecac26607adb59745d061aecebe83acaf28ff40c9f83c5ccd83e5fad8