[INFO] fetching crate sklears-mixture 0.1.0-alpha.1...
[INFO] checking sklears-mixture-0.1.0-alpha.1 against master#bad50269f8eb0fda214f0478c3afb2c6fbb427fd for pr-149195-1
[INFO] extracting crate sklears-mixture 0.1.0-alpha.1 into /workspace/builds/worker-2-tc1/source
[INFO] started tweaking crates.io crate sklears-mixture 0.1.0-alpha.1
[INFO] finished tweaking crates.io crate sklears-mixture 0.1.0-alpha.1
[INFO] tweaked toml for crates.io crate sklears-mixture 0.1.0-alpha.1 written to /workspace/builds/worker-2-tc1/source/Cargo.toml
[INFO] validating manifest of crates.io crate sklears-mixture 0.1.0-alpha.1 on toolchain bad50269f8eb0fda214f0478c3afb2c6fbb427fd
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+bad50269f8eb0fda214f0478c3afb2c6fbb427fd" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }`
[INFO] crate crates.io crate sklears-mixture 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" "+bad50269f8eb0fda214f0478c3afb2c6fbb427fd" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
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[INFO] [stderr]     Checking sklears-mixture v0.1.0-alpha.1 (/opt/rustwide/workdir)
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/stochastic_variational.rs:629:9
[INFO] [stdout]     |
[INFO] [stdout] 629 |           /// OptimizerState
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 630 | /         OptimizerState {
[INFO] [stdout] 631 | |             m_pi: Array1::zeros(self.n_components),
[INFO] [stdout] 632 | |             m_mu_mean: Array2::zeros((self.n_components, n_features)),
[INFO] [stdout] 633 | |             m_mu_precision: Array2::zeros((self.n_components, n_features)),
[INFO] [stdout] ...   |
[INFO] [stdout] 641 | |             t: 0,
[INFO] [stdout] 642 | |         }
[INFO] [stdout]     | |_________- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout]     = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]   --> src/time_series.rs:50:9
[INFO] [stdout]    |
[INFO] [stdout] 50 |         /// HiddenMarkovModel
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 51 |         HiddenMarkovModel
[INFO] [stdout]    |         ----------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]    |
[INFO] [stdout]    = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]   --> src/time_series.rs:94:9
[INFO] [stdout]    |
[INFO] [stdout] 94 |         /// RegimeSwitchingModel
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 95 |         RegimeSwitchingModel
[INFO] [stdout]    |         -------------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]    |
[INFO] [stdout]    = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:121:9
[INFO] [stdout]     |
[INFO] [stdout] 121 |         /// SwitchingStateSpaceModel
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 122 |         SwitchingStateSpaceModel
[INFO] [stdout]     |         ------------------------ rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:144:9
[INFO] [stdout]     |
[INFO] [stdout] 144 |         /// TemporalGaussianMixture
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 145 |         TemporalGaussianMixture
[INFO] [stdout]     |         ----------------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:178:9
[INFO] [stdout]     |
[INFO] [stdout] 178 |         /// DynamicMixture
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 179 |         DynamicMixture
[INFO] [stdout]     |         -------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/stochastic_variational.rs:629:9
[INFO] [stdout]     |
[INFO] [stdout] 629 |           /// OptimizerState
[INFO] [stdout]     |           ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 630 | /         OptimizerState {
[INFO] [stdout] 631 | |             m_pi: Array1::zeros(self.n_components),
[INFO] [stdout] 632 | |             m_mu_mean: Array2::zeros((self.n_components, n_features)),
[INFO] [stdout] 633 | |             m_mu_precision: Array2::zeros((self.n_components, n_features)),
[INFO] [stdout] ...   |
[INFO] [stdout] 641 | |             t: 0,
[INFO] [stdout] 642 | |         }
[INFO] [stdout]     | |_________- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout]     = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]   --> src/time_series.rs:50:9
[INFO] [stdout]    |
[INFO] [stdout] 50 |         /// HiddenMarkovModel
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 51 |         HiddenMarkovModel
[INFO] [stdout]    |         ----------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]    |
[INFO] [stdout]    = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]   --> src/time_series.rs:94:9
[INFO] [stdout]    |
[INFO] [stdout] 94 |         /// RegimeSwitchingModel
[INFO] [stdout]    |         ^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 95 |         RegimeSwitchingModel
[INFO] [stdout]    |         -------------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]    |
[INFO] [stdout]    = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:121:9
[INFO] [stdout]     |
[INFO] [stdout] 121 |         /// SwitchingStateSpaceModel
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 122 |         SwitchingStateSpaceModel
[INFO] [stdout]     |         ------------------------ rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:144:9
[INFO] [stdout]     |
[INFO] [stdout] 144 |         /// TemporalGaussianMixture
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 145 |         TemporalGaussianMixture
[INFO] [stdout]     |         ----------------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused doc comment
[INFO] [stdout]    --> src/time_series.rs:178:9
[INFO] [stdout]     |
[INFO] [stdout] 178 |         /// DynamicMixture
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 179 |         DynamicMixture
[INFO] [stdout]     |         -------------- rustdoc does not generate documentation for expressions
[INFO] [stdout]     |
[INFO] [stdout]     = help: use `//` for a plain comment
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Distribution`
[INFO] [stdout]   --> src/prior_sensitivity.rs:10:39
[INFO] [stdout]    |
[INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Distribution, RandNormal, Rng, SeedableRng};
[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 variable: `n_features`
[INFO] [stdout]    --> src/advi.rs:437:25
[INFO] [stdout]     |
[INFO] [stdout] 437 |         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]     = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/advi.rs:506:14
[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_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `f0`
[INFO] [stdout]    --> src/advi.rs:962:13
[INFO] [stdout]     |
[INFO] [stdout] 962 |         let f0 = self.evaluate_objective(X, params, rng)?;
[INFO] [stdout]     |             ^^ help: if this is intentional, prefix it with an underscore: `_f0`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]     --> src/advi.rs:1044:9
[INFO] [stdout]      |
[INFO] [stdout] 1044 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]      |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `scale_matrix`
[INFO] [stdout]     --> src/advi.rs:1181:9
[INFO] [stdout]      |
[INFO] [stdout] 1181 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]     --> src/advi.rs:1215:9
[INFO] [stdout]      |
[INFO] [stdout] 1215 |         mean_precision: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]     --> src/advi.rs:1221:25
[INFO] [stdout]      |
[INFO] [stdout] 1221 |         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: `scale_matrix`
[INFO] [stdout]     --> src/advi.rs:1597:9
[INFO] [stdout]      |
[INFO] [stdout] 1597 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `cov`
[INFO] [stdout]   --> src/common.rs:43:5
[INFO] [stdout]    |
[INFO] [stdout] 43 |     cov: &ArrayView2<f64>,
[INFO] [stdout]    |     ^^^ help: if this is intentional, prefix it with an underscore: `_cov`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/empirical_bayes.rs:310:25
[INFO] [stdout]     |
[INFO] [stdout] 310 |         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: `weights`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:18
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                  ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:27
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                           ^^^^^ help: if this is intentional, prefix it with an underscore: `_means`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `covariances`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:34
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                                  ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/empirical_bayes.rs:477:25
[INFO] [stdout]     |
[INFO] [stdout] 477 |         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: `lambda_nu`
[INFO] [stdout]    --> src/empirical_bayes.rs:807:9
[INFO] [stdout]     |
[INFO] [stdout] 807 |         lambda_nu: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_nu`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `lambda_w`
[INFO] [stdout]    --> src/empirical_bayes.rs:808:9
[INFO] [stdout]     |
[INFO] [stdout] 808 |         lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/empirical_bayes.rs:841:14
[INFO] [stdout]     |
[INFO] [stdout] 841 |         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: `total_responsibility`
[INFO] [stdout]    --> src/empirical_bayes.rs:844:13
[INFO] [stdout]     |
[INFO] [stdout] 844 |         let total_responsibility: f64 = variational_params.pi_alpha.sum()
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_total_responsibility`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `variational_params`
[INFO] [stdout]    --> src/empirical_bayes.rs:930:9
[INFO] [stdout]     |
[INFO] [stdout] 930 |         variational_params: &VariationalParameters,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/empirical_bayes.rs:934:14
[INFO] [stdout]     |
[INFO] [stdout] 934 |         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: `variational_params`
[INFO] [stdout]     --> src/empirical_bayes.rs:1061:9
[INFO] [stdout]      |
[INFO] [stdout] 1061 |         variational_params: &VariationalParameters,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/exponential_family.rs:189:14
[INFO] [stdout]     |
[INFO] [stdout] 189 |         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/exponential_family.rs:189:25
[INFO] [stdout]     |
[INFO] [stdout] 189 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/exponential_family.rs:555:28
[INFO] [stdout]     |
[INFO] [stdout] 555 |     fn n_parameters(&self, n_features: usize) -> usize {
[INFO] [stdout]     |                            ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/gaussian.rs:276:14
[INFO] [stdout]     |
[INFO] [stdout] 276 |         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/gaussian.rs:276:25
[INFO] [stdout]     |
[INFO] [stdout] 276 |         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: `k`
[INFO] [stdout]    --> src/gaussian.rs:445:13
[INFO] [stdout]     |
[INFO] [stdout] 445 |         for k in 0..self.n_components {
[INFO] [stdout]     |             ^ help: if this is intentional, prefix it with an underscore: `_k`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/gaussian.rs:464:14
[INFO] [stdout]     |
[INFO] [stdout] 464 |         let (n_samples, _) = X.dim();
[INFO] [stdout]     |              ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `Distribution`
[INFO] [stdout]   --> src/prior_sensitivity.rs:10:39
[INFO] [stdout]    |
[INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Distribution, RandNormal, Rng, SeedableRng};
[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 variable: `new_q_z`
[INFO] [stdout]    --> src/mean_field_variational.rs:245:18
[INFO] [stdout]     |
[INFO] [stdout] 245 |             let (new_q_z, grad_z) = self.update_q_z(
[INFO] [stdout]     |                  ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_z`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_pi_alpha`
[INFO] [stdout]    --> src/mean_field_variational.rs:267:18
[INFO] [stdout]     |
[INFO] [stdout] 267 |             let (new_q_pi_alpha, grad_pi) = self.update_q_pi(&q_z)?;
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_mu_mean`
[INFO] [stdout]    --> src/mean_field_variational.rs:275:18
[INFO] [stdout]     |
[INFO] [stdout] 275 |             let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) =
[INFO] [stdout]     |                  ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_mean`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_mu_precision`
[INFO] [stdout]    --> src/mean_field_variational.rs:275:33
[INFO] [stdout]     |
[INFO] [stdout] 275 |             let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) =
[INFO] [stdout]     |                                 ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/mean_field_variational.rs:476:13
[INFO] [stdout]     |
[INFO] [stdout] 476 |         let n_samples = q_z.nrows();
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `q_lambda_w`
[INFO] [stdout]    --> src/mean_field_variational.rs:495:9
[INFO] [stdout]     |
[INFO] [stdout] 495 |         q_lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_q_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/advi.rs:437:25
[INFO] [stdout]     |
[INFO] [stdout] 437 |         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]     = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/advi.rs:506:14
[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_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means_map`
[INFO] [stdout]    --> src/multi_modal.rs:401:27
[INFO] [stdout]     |
[INFO] [stdout] 401 |         let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?;
[INFO] [stdout]     |                           ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_means_map`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `covariances_map`
[INFO] [stdout]    --> src/multi_modal.rs:401:38
[INFO] [stdout]     |
[INFO] [stdout] 401 |         let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?;
[INFO] [stdout]     |                                      ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances_map`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `f0`
[INFO] [stdout]    --> src/advi.rs:962:13
[INFO] [stdout]     |
[INFO] [stdout] 962 |         let f0 = self.evaluate_objective(X, params, rng)?;
[INFO] [stdout]     |             ^^ help: if this is intentional, prefix it with an underscore: `_f0`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]     --> src/advi.rs:1044:9
[INFO] [stdout]      |
[INFO] [stdout] 1044 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]      |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/multi_modal.rs:711:13
[INFO] [stdout]     |
[INFO] [stdout] 711 |         let n_samples = X.values().next().unwrap().nrows();
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `scale_matrix`
[INFO] [stdout]     --> src/advi.rs:1181:9
[INFO] [stdout]      |
[INFO] [stdout] 1181 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]     --> src/advi.rs:1215:9
[INFO] [stdout]      |
[INFO] [stdout] 1215 |         mean_precision: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]     --> src/advi.rs:1221:25
[INFO] [stdout]      |
[INFO] [stdout] 1221 |         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: `X`
[INFO] [stdout]     --> src/multi_modal.rs:1039:9
[INFO] [stdout]      |
[INFO] [stdout] 1039 |         X: &HashMap<String, Array2<f64>>,
[INFO] [stdout]      |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `scale_matrix`
[INFO] [stdout]     --> src/advi.rs:1597:9
[INFO] [stdout]      |
[INFO] [stdout] 1597 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `cov`
[INFO] [stdout]   --> src/common.rs:43:5
[INFO] [stdout]    |
[INFO] [stdout] 43 |     cov: &ArrayView2<f64>,
[INFO] [stdout]    |     ^^^ help: if this is intentional, prefix it with an underscore: `_cov`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/empirical_bayes.rs:310:25
[INFO] [stdout]     |
[INFO] [stdout] 310 |         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: `weights`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:18
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                  ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:27
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                           ^^^^^ help: if this is intentional, prefix it with an underscore: `_means`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `covariances`
[INFO] [stdout]    --> src/empirical_bayes.rs:349:34
[INFO] [stdout]     |
[INFO] [stdout] 349 |             let (weights, means, covariances, variational_params, marginal_likelihood) =
[INFO] [stdout]     |                                  ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/empirical_bayes.rs:477:25
[INFO] [stdout]     |
[INFO] [stdout] 477 |         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: `X`
[INFO] [stdout]     --> src/nonparametric.rs:1549:25
[INFO] [stdout]      |
[INFO] [stdout] 1549 |     pub fn score(&self, X: &ArrayView2<'_, Float>) -> SklResult<f64> {
[INFO] [stdout]      |                         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `lambda_nu`
[INFO] [stdout]    --> src/empirical_bayes.rs:807:9
[INFO] [stdout]     |
[INFO] [stdout] 807 |         lambda_nu: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_nu`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `lambda_w`
[INFO] [stdout]    --> src/empirical_bayes.rs:808:9
[INFO] [stdout]     |
[INFO] [stdout] 808 |         lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/empirical_bayes.rs:841:14
[INFO] [stdout]     |
[INFO] [stdout] 841 |         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: `total_responsibility`
[INFO] [stdout]    --> src/empirical_bayes.rs:844:13
[INFO] [stdout]     |
[INFO] [stdout] 844 |         let total_responsibility: f64 = variational_params.pi_alpha.sum()
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_total_responsibility`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `variational_params`
[INFO] [stdout]    --> src/empirical_bayes.rs:930:9
[INFO] [stdout]     |
[INFO] [stdout] 930 |         variational_params: &VariationalParameters,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/empirical_bayes.rs:934:14
[INFO] [stdout]     |
[INFO] [stdout] 934 |         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: `variational_params`
[INFO] [stdout]     --> src/empirical_bayes.rs:1061:9
[INFO] [stdout]      |
[INFO] [stdout] 1061 |         variational_params: &VariationalParameters,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/nuts.rs:354:9
[INFO] [stdout]     |
[INFO] [stdout] 354 |         X: &Array2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/nuts.rs:356:9
[INFO] [stdout]     |
[INFO] [stdout] 356 |         n_features: usize,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `subtree`
[INFO] [stdout]    --> src/nuts.rs:591:51
[INFO] [stdout]     |
[INFO] [stdout] 591 |     fn check_uturn(&self, tree_state: &TreeState, subtree: &TreeState) -> bool {
[INFO] [stdout]     |                                                   ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_subtree`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/exponential_family.rs:189:14
[INFO] [stdout]     |
[INFO] [stdout] 189 |         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/exponential_family.rs:189:25
[INFO] [stdout]     |
[INFO] [stdout] 189 |         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: `position`
[INFO] [stdout]    --> src/nuts.rs:670:9
[INFO] [stdout]     |
[INFO] [stdout] 670 |         position: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_position`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/exponential_family.rs:555:28
[INFO] [stdout]     |
[INFO] [stdout] 555 |     fn n_parameters(&self, n_features: usize) -> usize {
[INFO] [stdout]     |                            ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/gaussian.rs:276:14
[INFO] [stdout]     |
[INFO] [stdout] 276 |         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/gaussian.rs:276:25
[INFO] [stdout]     |
[INFO] [stdout] 276 |         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: `k`
[INFO] [stdout]    --> src/gaussian.rs:445:13
[INFO] [stdout]     |
[INFO] [stdout] 445 |         for k in 0..self.n_components {
[INFO] [stdout]     |             ^ help: if this is intentional, prefix it with an underscore: `_k`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/gaussian.rs:464:14
[INFO] [stdout]     |
[INFO] [stdout] 464 |         let (n_samples, _) = X.dim();
[INFO] [stdout]     |              ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_z`
[INFO] [stdout]    --> src/mean_field_variational.rs:245:18
[INFO] [stdout]     |
[INFO] [stdout] 245 |             let (new_q_z, grad_z) = self.update_q_z(
[INFO] [stdout]     |                  ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_z`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_pi_alpha`
[INFO] [stdout]    --> src/mean_field_variational.rs:267:18
[INFO] [stdout]     |
[INFO] [stdout] 267 |             let (new_q_pi_alpha, grad_pi) = self.update_q_pi(&q_z)?;
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_mu_mean`
[INFO] [stdout]    --> src/mean_field_variational.rs:275:18
[INFO] [stdout]     |
[INFO] [stdout] 275 |             let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) =
[INFO] [stdout]     |                  ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_mean`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `new_q_mu_precision`
[INFO] [stdout]    --> src/mean_field_variational.rs:275:33
[INFO] [stdout]     |
[INFO] [stdout] 275 |             let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) =
[INFO] [stdout]     |                                 ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/mean_field_variational.rs:476:13
[INFO] [stdout]     |
[INFO] [stdout] 476 |         let n_samples = q_z.nrows();
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `q_lambda_w`
[INFO] [stdout]    --> src/mean_field_variational.rs:495:9
[INFO] [stdout]     |
[INFO] [stdout] 495 |         q_lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_q_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]    --> src/prior_elicitation.rs:433:9
[INFO] [stdout]     |
[INFO] [stdout] 433 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]     |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/prior_elicitation.rs:523:9
[INFO] [stdout]     |
[INFO] [stdout] 523 |         X: &ArrayView2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]    --> src/prior_elicitation.rs:644:9
[INFO] [stdout]     |
[INFO] [stdout] 644 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]     |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/prior_elicitation.rs:701:9
[INFO] [stdout]     |
[INFO] [stdout] 701 |         X: &ArrayView2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `prior_spec`
[INFO] [stdout]    --> src/prior_elicitation.rs:783:9
[INFO] [stdout]     |
[INFO] [stdout] 783 |         prior_spec: &PriorSpecification,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prior_spec`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_characteristics`
[INFO] [stdout]     --> src/prior_elicitation.rs:1016:9
[INFO] [stdout]      |
[INFO] [stdout] 1016 |         data_characteristics: &DataCharacteristics,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_characteristics`
[INFO] [stdout]     --> src/prior_elicitation.rs:1032:9
[INFO] [stdout]      |
[INFO] [stdout] 1032 |         data_characteristics: &DataCharacteristics,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/prior_elicitation.rs:1247:9
[INFO] [stdout]      |
[INFO] [stdout] 1247 |         X: &ArrayView2<f64>,
[INFO] [stdout]      |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means_map`
[INFO] [stdout]    --> src/multi_modal.rs:401:27
[INFO] [stdout]     |
[INFO] [stdout] 401 |         let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?;
[INFO] [stdout]     |                           ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_means_map`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `covariances_map`
[INFO] [stdout]    --> src/multi_modal.rs:401:38
[INFO] [stdout]     |
[INFO] [stdout] 401 |         let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?;
[INFO] [stdout]     |                                      ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances_map`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_arrays`
[INFO] [stdout]    --> src/prior_sensitivity.rs:624:13
[INFO] [stdout]     |
[INFO] [stdout] 624 |         let n_arrays = arrays.len();
[INFO] [stdout]     |             ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_arrays`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/multi_modal.rs:711:13
[INFO] [stdout]     |
[INFO] [stdout] 711 |         let n_samples = X.values().next().unwrap().nrows();
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/multi_modal.rs:1039:9
[INFO] [stdout]      |
[INFO] [stdout] 1039 |         X: &HashMap<String, Array2<f64>>,
[INFO] [stdout]      |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:144:25
[INFO] [stdout]     |
[INFO] [stdout] 144 |         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: `trained_state`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:168:13
[INFO] [stdout]     |
[INFO] [stdout] 168 |         let trained_state = GeographicMixtureTrained {
[INFO] [stdout]     |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:253:14
[INFO] [stdout]     |
[INFO] [stdout] 253 |         let (n_samples, n_features) = features.dim();
[INFO] [stdout]     |              ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `iteration`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:267:13
[INFO] [stdout]     |
[INFO] [stdout] 267 |         for iteration in 0..self.max_iter {
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: value passed to `weights` is never read
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:305:9
[INFO] [stdout]     |
[INFO] [stdout] 305 |         mut weights: Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = help: maybe it is overwritten before being read?
[INFO] [stdout]     = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/nonparametric.rs:1549:25
[INFO] [stdout]      |
[INFO] [stdout] 1549 |     pub fn score(&self, X: &ArrayView2<'_, Float>) -> SklResult<f64> {
[INFO] [stdout]      |                         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `weights`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:152:13
[INFO] [stdout]     |
[INFO] [stdout] 152 |         let weights = Array1::from_elem(self.n_components, 1.0 / self.n_components as f64);
[INFO] [stdout]     |             ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:155:13
[INFO] [stdout]     |
[INFO] [stdout] 155 |         let means = self.initialize_means(X)?;
[INFO] [stdout]     |             ^^^^^ help: if this is intentional, prefix it with an underscore: `_means`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `interaction_parameters`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:166:13
[INFO] [stdout]     |
[INFO] [stdout] 166 |         let interaction_parameters: Array2<f64> =
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_interaction_parameters`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `neighborhood_graph`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:170:13
[INFO] [stdout]     |
[INFO] [stdout] 170 |         let neighborhood_graph = self.build_neighborhood_graph(X)?;
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_neighborhood_graph`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/nuts.rs:354:9
[INFO] [stdout]     |
[INFO] [stdout] 354 |         X: &Array2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/nuts.rs:356:9
[INFO] [stdout]     |
[INFO] [stdout] 356 |         n_features: usize,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `subtree`
[INFO] [stdout]    --> src/nuts.rs:591:51
[INFO] [stdout]     |
[INFO] [stdout] 591 |     fn check_uturn(&self, tree_state: &TreeState, subtree: &TreeState) -> bool {
[INFO] [stdout]     |                                                   ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_subtree`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `position`
[INFO] [stdout]    --> src/nuts.rs:670:9
[INFO] [stdout]     |
[INFO] [stdout] 670 |         position: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_position`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `w_sum`
[INFO] [stdout]    --> src/spatial/spatial_statistics.rs:333:49
[INFO] [stdout]     |
[INFO] [stdout] 333 |     fn compute_morans_i_variance(&self, n: f64, w_sum: f64) -> SklResult<f64> {
[INFO] [stdout]     |                                                 ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `w_sum`
[INFO] [stdout]    --> src/spatial/spatial_statistics.rs:340:49
[INFO] [stdout]     |
[INFO] [stdout] 340 |     fn compute_gearys_c_variance(&self, n: f64, w_sum: f64) -> SklResult<f64> {
[INFO] [stdout]     |                                                 ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `trained_state`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:197:13
[INFO] [stdout]     |
[INFO] [stdout] 197 |         let trained_state = SpatiallyConstrainedGMMTrained {
[INFO] [stdout]     |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `coords`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:379:9
[INFO] [stdout]     |
[INFO] [stdout] 379 |         coords: &Array2<f64>,
[INFO] [stdout]     |         ^^^^^^ help: if this is intentional, prefix it with an underscore: `_coords`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:385:14
[INFO] [stdout]     |
[INFO] [stdout] 385 |         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/spatial/spatially_constrained_gmm.rs:385:25
[INFO] [stdout]     |
[INFO] [stdout] 385 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_components`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:386:13
[INFO] [stdout]     |
[INFO] [stdout] 386 |         let n_components = self.config.n_components;
[INFO] [stdout]     |             ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `iteration`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:389:13
[INFO] [stdout]     |
[INFO] [stdout] 389 |         for iteration in 0..self.config.max_iter {
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]    --> src/prior_elicitation.rs:433:9
[INFO] [stdout]     |
[INFO] [stdout] 433 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]     |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/prior_elicitation.rs:523:9
[INFO] [stdout]     |
[INFO] [stdout] 523 |         X: &ArrayView2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `rng`
[INFO] [stdout]    --> src/prior_elicitation.rs:644:9
[INFO] [stdout]     |
[INFO] [stdout] 644 |         rng: &mut scirs2_core::random::rngs::StdRng,
[INFO] [stdout]     |         ^^^ help: if this is intentional, prefix it with an underscore: `_rng`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]    --> src/prior_elicitation.rs:701:9
[INFO] [stdout]     |
[INFO] [stdout] 701 |         X: &ArrayView2<f64>,
[INFO] [stdout]     |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `prior_spec`
[INFO] [stdout]    --> src/prior_elicitation.rs:783:9
[INFO] [stdout]     |
[INFO] [stdout] 783 |         prior_spec: &PriorSpecification,
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prior_spec`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_pi_alpha`
[INFO] [stdout]    --> src/stochastic_variational.rs:718:9
[INFO] [stdout]     |
[INFO] [stdout] 718 |         global_pi_alpha: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:722:9
[INFO] [stdout]     |
[INFO] [stdout] 722 |         global_lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `epoch`
[INFO] [stdout]    --> src/stochastic_variational.rs:809:9
[INFO] [stdout]     |
[INFO] [stdout] 809 |         epoch: usize,
[INFO] [stdout]     |         ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:896:9
[INFO] [stdout]     |
[INFO] [stdout] 896 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:942:9
[INFO] [stdout]     |
[INFO] [stdout] 942 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:990:9
[INFO] [stdout]     |
[INFO] [stdout] 990 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_characteristics`
[INFO] [stdout]     --> src/prior_elicitation.rs:1016:9
[INFO] [stdout]      |
[INFO] [stdout] 1016 |         data_characteristics: &DataCharacteristics,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_pi_alpha`
[INFO] [stdout]     --> src/stochastic_variational.rs:1062:9
[INFO] [stdout]      |
[INFO] [stdout] 1062 |         global_pi_alpha: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_characteristics`
[INFO] [stdout]     --> src/prior_elicitation.rs:1032:9
[INFO] [stdout]      |
[INFO] [stdout] 1032 |         data_characteristics: &DataCharacteristics,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `decay_rate`
[INFO] [stdout]     --> src/stochastic_variational.rs:1204:39
[INFO] [stdout]      |
[INFO] [stdout] 1204 |     fn decay_learning_rate(&mut self, decay_rate: f64) {
[INFO] [stdout]      |                                       ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_decay_rate`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/stochastic_variational.rs:1380:35
[INFO] [stdout]      |
[INFO] [stdout] 1380 |     pub fn partial_fit(&mut self, X: &ArrayView2<'_, Float>) -> SklResult<()> {
[INFO] [stdout]      |                                   ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/prior_elicitation.rs:1247:9
[INFO] [stdout]      |
[INFO] [stdout] 1247 |         X: &ArrayView2<f64>,
[INFO] [stdout]      |         ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/structured_variational.rs:252:25
[INFO] [stdout]     |
[INFO] [stdout] 252 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:324:14
[INFO] [stdout]     |
[INFO] [stdout] 324 |         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: `iter`
[INFO] [stdout]    --> src/structured_variational.rs:525:13
[INFO] [stdout]     |
[INFO] [stdout] 525 |         for iter in 0..self.max_iter {
[INFO] [stdout]     |             ^^^^ help: if this is intentional, prefix it with an underscore: `_iter`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:659:14
[INFO] [stdout]     |
[INFO] [stdout] 659 |         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/structured_variational.rs:659:25
[INFO] [stdout]     |
[INFO] [stdout] 659 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:707:14
[INFO] [stdout]     |
[INFO] [stdout] 707 |         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/structured_variational.rs:707:25
[INFO] [stdout]     |
[INFO] [stdout] 707 |         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: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:788:9
[INFO] [stdout]     |
[INFO] [stdout] 788 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `structured_cov`
[INFO] [stdout]    --> src/structured_variational.rs:791:9
[INFO] [stdout]     |
[INFO] [stdout] 791 |         structured_cov: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_structured_cov`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:854:9
[INFO] [stdout]     |
[INFO] [stdout] 854 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:925:9
[INFO] [stdout]     |
[INFO] [stdout] 925 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:997:9
[INFO] [stdout]     |
[INFO] [stdout] 997 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_arrays`
[INFO] [stdout]    --> src/prior_sensitivity.rs:624:13
[INFO] [stdout]     |
[INFO] [stdout] 624 |         let n_arrays = arrays.len();
[INFO] [stdout]     |             ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_arrays`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `scale_matrix`
[INFO] [stdout]     --> src/structured_variational.rs:1095:9
[INFO] [stdout]      |
[INFO] [stdout] 1095 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]     --> src/structured_variational.rs:1137:9
[INFO] [stdout]      |
[INFO] [stdout] 1137 |         mean_precision: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]     --> src/structured_variational.rs:1144:25
[INFO] [stdout]      |
[INFO] [stdout] 1144 |         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: `scale_matrix`
[INFO] [stdout]     --> src/structured_variational.rs:1450:9
[INFO] [stdout]      |
[INFO] [stdout] 1450 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:144:25
[INFO] [stdout]     |
[INFO] [stdout] 144 |         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: `trained_state`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:168:13
[INFO] [stdout]     |
[INFO] [stdout] 168 |         let trained_state = GeographicMixtureTrained {
[INFO] [stdout]     |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:253:14
[INFO] [stdout]     |
[INFO] [stdout] 253 |         let (n_samples, n_features) = features.dim();
[INFO] [stdout]     |              ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `iteration`
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:267:13
[INFO] [stdout]     |
[INFO] [stdout] 267 |         for iteration in 0..self.max_iter {
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: value passed to `weights` is never read
[INFO] [stdout]    --> src/spatial/geographic_mixture.rs:305:9
[INFO] [stdout]     |
[INFO] [stdout] 305 |         mut weights: Array1<f64>,
[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_features`
[INFO] [stdout]    --> src/variational.rs:182:25
[INFO] [stdout]     |
[INFO] [stdout] 182 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/variational.rs:303:14
[INFO] [stdout]     |
[INFO] [stdout] 303 |         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: `degrees_of_freedom`
[INFO] [stdout]    --> src/variational.rs:522:9
[INFO] [stdout]     |
[INFO] [stdout] 522 |         degrees_of_freedom: f64,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `k`
[INFO] [stdout]    --> src/variational.rs:580:13
[INFO] [stdout]     |
[INFO] [stdout] 580 |         for k in 0..self.n_components {
[INFO] [stdout]     |             ^ help: if this is intentional, prefix it with an underscore: `_k`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]    --> src/variational.rs:603:9
[INFO] [stdout]     |
[INFO] [stdout] 603 |         mean_precision: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `degrees_of_freedom`
[INFO] [stdout]    --> src/variational.rs:605:9
[INFO] [stdout]     |
[INFO] [stdout] 605 |         degrees_of_freedom: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `weights`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:152:13
[INFO] [stdout]     |
[INFO] [stdout] 152 |         let weights = Array1::from_elem(self.n_components, 1.0 / self.n_components as f64);
[INFO] [stdout]     |             ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `means`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:155:13
[INFO] [stdout]     |
[INFO] [stdout] 155 |         let means = self.initialize_means(X)?;
[INFO] [stdout]     |             ^^^^^ help: if this is intentional, prefix it with an underscore: `_means`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `interaction_parameters`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:166:13
[INFO] [stdout]     |
[INFO] [stdout] 166 |         let interaction_parameters: Array2<f64> =
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_interaction_parameters`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `neighborhood_graph`
[INFO] [stdout]    --> src/spatial/markov_random_field.rs:170:13
[INFO] [stdout]     |
[INFO] [stdout] 170 |         let neighborhood_graph = self.build_neighborhood_graph(X)?;
[INFO] [stdout]     |             ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_neighborhood_graph`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `w_sum`
[INFO] [stdout]    --> src/spatial/spatial_statistics.rs:333:49
[INFO] [stdout]     |
[INFO] [stdout] 333 |     fn compute_morans_i_variance(&self, n: f64, w_sum: f64) -> SklResult<f64> {
[INFO] [stdout]     |                                                 ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `w_sum`
[INFO] [stdout]    --> src/spatial/spatial_statistics.rs:340:49
[INFO] [stdout]     |
[INFO] [stdout] 340 |     fn compute_gearys_c_variance(&self, n: f64, w_sum: f64) -> SklResult<f64> {
[INFO] [stdout]     |                                                 ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `trained_state`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:197:13
[INFO] [stdout]     |
[INFO] [stdout] 197 |         let trained_state = SpatiallyConstrainedGMMTrained {
[INFO] [stdout]     |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `coords`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:379:9
[INFO] [stdout]     |
[INFO] [stdout] 379 |         coords: &Array2<f64>,
[INFO] [stdout]     |         ^^^^^^ help: if this is intentional, prefix it with an underscore: `_coords`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:385:14
[INFO] [stdout]     |
[INFO] [stdout] 385 |         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/spatial/spatially_constrained_gmm.rs:385:25
[INFO] [stdout]     |
[INFO] [stdout] 385 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_components`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:386:13
[INFO] [stdout]     |
[INFO] [stdout] 386 |         let n_components = self.config.n_components;
[INFO] [stdout]     |             ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `iteration`
[INFO] [stdout]    --> src/spatial/spatially_constrained_gmm.rs:389:13
[INFO] [stdout]     |
[INFO] [stdout] 389 |         for iteration in 0..self.config.max_iter {
[INFO] [stdout]     |             ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_pi_alpha`
[INFO] [stdout]    --> src/stochastic_variational.rs:718:9
[INFO] [stdout]     |
[INFO] [stdout] 718 |         global_pi_alpha: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:722:9
[INFO] [stdout]     |
[INFO] [stdout] 722 |         global_lambda_w: &Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `epoch`
[INFO] [stdout]    --> src/stochastic_variational.rs:809:9
[INFO] [stdout]     |
[INFO] [stdout] 809 |         epoch: usize,
[INFO] [stdout]     |         ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:896:9
[INFO] [stdout]     |
[INFO] [stdout] 896 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:942:9
[INFO] [stdout]     |
[INFO] [stdout] 942 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_lambda_w`
[INFO] [stdout]    --> src/stochastic_variational.rs:990:9
[INFO] [stdout]     |
[INFO] [stdout] 990 |         global_lambda_w: &mut Vec<Array2<f64>>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `global_pi_alpha`
[INFO] [stdout]     --> src/stochastic_variational.rs:1062:9
[INFO] [stdout]      |
[INFO] [stdout] 1062 |         global_pi_alpha: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `decay_rate`
[INFO] [stdout]     --> src/stochastic_variational.rs:1204:39
[INFO] [stdout]      |
[INFO] [stdout] 1204 |     fn decay_learning_rate(&mut self, decay_rate: f64) {
[INFO] [stdout]      |                                       ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_decay_rate`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `X`
[INFO] [stdout]     --> src/stochastic_variational.rs:1380:35
[INFO] [stdout]      |
[INFO] [stdout] 1380 |     pub fn partial_fit(&mut self, X: &ArrayView2<'_, Float>) -> SklResult<()> {
[INFO] [stdout]      |                                   ^ help: if this is intentional, prefix it with an underscore: `_X`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/structured_variational.rs:252:25
[INFO] [stdout]     |
[INFO] [stdout] 252 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:324:14
[INFO] [stdout]     |
[INFO] [stdout] 324 |         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: `iter`
[INFO] [stdout]    --> src/structured_variational.rs:525:13
[INFO] [stdout]     |
[INFO] [stdout] 525 |         for iter in 0..self.max_iter {
[INFO] [stdout]     |             ^^^^ help: if this is intentional, prefix it with an underscore: `_iter`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:659:14
[INFO] [stdout]     |
[INFO] [stdout] 659 |         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/structured_variational.rs:659:25
[INFO] [stdout]     |
[INFO] [stdout] 659 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/structured_variational.rs:707:14
[INFO] [stdout]     |
[INFO] [stdout] 707 |         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/structured_variational.rs:707:25
[INFO] [stdout]     |
[INFO] [stdout] 707 |         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: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:788:9
[INFO] [stdout]     |
[INFO] [stdout] 788 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `structured_cov`
[INFO] [stdout]    --> src/structured_variational.rs:791:9
[INFO] [stdout]     |
[INFO] [stdout] 791 |         structured_cov: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_structured_cov`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:854:9
[INFO] [stdout]     |
[INFO] [stdout] 854 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:925:9
[INFO] [stdout]     |
[INFO] [stdout] 925 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `precision_values`
[INFO] [stdout]    --> src/structured_variational.rs:997:9
[INFO] [stdout]     |
[INFO] [stdout] 997 |         precision_values: &mut Array3<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `scale_matrix`
[INFO] [stdout]     --> src/structured_variational.rs:1095:9
[INFO] [stdout]      |
[INFO] [stdout] 1095 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]     --> src/structured_variational.rs:1137:9
[INFO] [stdout]      |
[INFO] [stdout] 1137 |         mean_precision: &Array1<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]     --> src/structured_variational.rs:1144:25
[INFO] [stdout]      |
[INFO] [stdout] 1144 |         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: `scale_matrix`
[INFO] [stdout]     --> src/structured_variational.rs:1450:9
[INFO] [stdout]      |
[INFO] [stdout] 1450 |         scale_matrix: &ArrayView2<f64>,
[INFO] [stdout]      |         ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_features`
[INFO] [stdout]    --> src/variational.rs:182:25
[INFO] [stdout]     |
[INFO] [stdout] 182 |         let (n_samples, n_features) = X.dim();
[INFO] [stdout]     |                         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `n_samples`
[INFO] [stdout]    --> src/variational.rs:303:14
[INFO] [stdout]     |
[INFO] [stdout] 303 |         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: `degrees_of_freedom`
[INFO] [stdout]    --> src/variational.rs:522:9
[INFO] [stdout]     |
[INFO] [stdout] 522 |         degrees_of_freedom: f64,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `k`
[INFO] [stdout]    --> src/variational.rs:580:13
[INFO] [stdout]     |
[INFO] [stdout] 580 |         for k in 0..self.n_components {
[INFO] [stdout]     |             ^ help: if this is intentional, prefix it with an underscore: `_k`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `mean_precision`
[INFO] [stdout]    --> src/variational.rs:603:9
[INFO] [stdout]     |
[INFO] [stdout] 603 |         mean_precision: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `degrees_of_freedom`
[INFO] [stdout]    --> src/variational.rs:605:9
[INFO] [stdout]     |
[INFO] [stdout] 605 |         degrees_of_freedom: &Array1<f64>,
[INFO] [stdout]     |         ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr]     Finished `dev` profile [unoptimized + debuginfo] target(s) in 2m 44s
[INFO] running `Command { std: "docker" "inspect" "18a7a4620eefdd44c0af9edc92c5c502d0f56865fa97ad0e6a3dc753cd690268", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "18a7a4620eefdd44c0af9edc92c5c502d0f56865fa97ad0e6a3dc753cd690268", kill_on_drop: false }`
[INFO] [stdout] 18a7a4620eefdd44c0af9edc92c5c502d0f56865fa97ad0e6a3dc753cd690268
