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=============================== warnings summary ===============================
tests/test_core/test_param_domain.py:146
  /home/rem/repos/LizyML/tests/test_core/test_param_domain.py:146: RuntimeWarning: overflow encountered in cast
    atoms.append(dtype(value))

tests/test_calibration/test_beta_calibration.py: 1 warning
tests/test_calibration/test_calibration.py: 10 warnings
tests/test_calibration/test_calibration_failed_optimisation.py: 2 warnings
tests/test_calibration/test_calibration_param_names.py: 1 warning
tests/test_calibration/test_calibration_split.py: 2 warnings
tests/test_calibration/test_h0058_outer_reuse.py: 2 warnings
tests/test_calibration/test_i298_pr3c_evidence.py: 4 warnings
tests/test_calibration/test_raw_score_calibration.py: 4 warnings
tests/test_codegen/test_calibration_params_codegen.py: 14 warnings
tests/test_config/test_knob_reachability.py: 8 warnings
tests/test_core/test_calibration_params_reach.py: 10 warnings
tests/test_core/test_config_propagation.py: 5 warnings
tests/test_core/test_error_code_raising.py: 4 warnings
tests/test_core/test_facade_orchestration.py: 7 warnings
tests/test_core/test_fit_params_override.py: 130 warnings
tests/test_core/test_fit_smoke_regressions.py: 1 warning
tests/test_core/test_param_refusal_origin.py: 1 warning
tests/test_core/test_refusal_matrix.py: 1 warning
tests/test_core/test_seed_propagation.py: 8 warnings
tests/test_core/test_smart_managed_model_params.py: 19 warnings
tests/test_e2e/test_binary_full.py: 8 warnings
tests/test_e2e/test_column_drift.py: 1 warning
tests/test_e2e/test_leakage_all.py: 4 warnings
tests/test_e2e/test_model_facade.py: 7 warnings
tests/test_e2e/test_pairwise.py: 2 warnings
tests/test_e2e/test_readme_example.py: 1 warning
tests/test_e2e/test_reproducibility.py: 4 warnings
tests/test_estimators/test_feval_probabilities.py: 4 warnings
tests/test_estimators/test_h0125_binary_objectives.py: 3 warnings
tests/test_estimators/test_h0125_native_metric_params.py: 1 warning
tests/test_estimators/test_lgbm_objective_identity.py: 2 warnings
tests/test_estimators/test_lightgbm_parameter_names.py: 2 warnings
tests/test_estimators/test_param_behavioral_effect.py: 2 warnings
tests/test_estimators/test_provider_protocol_drift.py: 9 warnings
tests/test_evaluation/test_confusion.py: 5 warnings
tests/test_evaluation/test_evaluation.py: 1 warning
tests/test_explain/test_explain.py: 3 warnings
tests/test_features/test_column_dtype_check.py: 49 warnings
tests/test_persistence/test_applied_training_params.py: 40 warnings
tests/test_persistence/test_artifact_compat.py: 3 warnings
tests/test_persistence/test_h0125_load_refuses_non_probability_objective.py: 42 warnings
tests/test_persistence/test_h0133_acceptance.py: 38 warnings
tests/test_persistence/test_persistence.py: 8 warnings
tests/test_plots/test_calibration_plots.py: 10 warnings
tests/test_plots/test_classification_plots.py: 4 warnings
tests/test_plots/test_plots.py: 2 warnings
tests/test_plots/test_residuals.py: 2 warnings
tests/test_plots/test_theme.py: 1 warning
tests/test_training/test_cv_refit_parity.py: 2 warnings
tests/test_tuning/test_dimension_consumption.py: 1 warning
tests/test_tuning/test_tune_fit_identity.py: 1 warning
  /home/rem/repos/LizyML/lizyml/core/model.py:286: UserWarning: task='binary' with split.method='kfold' does not preserve class distribution. Consider using 'stratified_kfold' instead.
    splitter = build_splitter(

tests/test_calibration/test_calibration_param_names.py::test_unknown_calibration_param_is_refused_before_any_training
tests/test_calibration/test_calibration_param_names.py::test_a_calibrated_run_still_succeeds
  /home/rem/repos/LizyML/.venv/lib/python3.12/site-packages/pydantic/main.py:716: UserWarning: calibration.n_splits is deprecated and will be ignored. Calibration cross-fit now reuses outer CV splits (H-0058). Will be removed in v1.0.
    return cls.__pydantic_validator__.validate_python(

tests/test_calibration/test_calibration_param_names.py: 1 warning
tests/test_core/test_calibration_params_reach.py: 6 warnings
tests/test_core/test_fit_params_override.py: 22 warnings
tests/test_core/test_param_refusal_origin.py: 1 warning
tests/test_core/test_refusal_matrix.py: 3 warnings
tests/test_core/test_smart_managed_model_params.py: 37 warnings
tests/test_persistence/test_applied_training_params.py: 22 warnings
tests/test_tuning/test_dimension_consumption.py: 23 warnings
tests/test_tuning/test_direction_reconciliation.py: 11 warnings
tests/test_tuning/test_resume_identity.py: 63 warnings
tests/test_tuning/test_search_space_name_validation.py: 12 warnings
tests/test_tuning/test_smart_dimension_admission.py: 11 warnings
tests/test_tuning/test_tune_fit_identity.py: 1 warning
  /home/rem/repos/LizyML/lizyml/core/_model_tuning.py:333: UserWarning: task='binary' with split.method='kfold' does not preserve class distribution. Consider using 'stratified_kfold' instead.
    splitter = build_splitter(

tests/test_calibration/test_i298_pr3c_evidence.py::test_4a_written_tol_is_not_defeated_by_the_default_options[SLSQP-beta]
tests/test_calibration/test_i298_pr3c_evidence.py::test_4b_written_options_beat_written_tol_key_by_key[SLSQP-beta]
tests/test_calibration/test_i298_pr3c_evidence.py::test_4c_defaults_belong_to_their_method[SLSQP-beta]
  /home/rem/repos/LizyML/lizyml/calibration/beta.py:35: RuntimeWarning: overflow encountered in exp
    np.exp(x) / (1.0 + np.exp(x)),

tests/test_calibration/test_i298_pr3c_evidence.py::test_4a_written_tol_is_not_defeated_by_the_default_options[SLSQP-beta]
tests/test_calibration/test_i298_pr3c_evidence.py::test_4b_written_options_beat_written_tol_key_by_key[SLSQP-beta]
tests/test_calibration/test_i298_pr3c_evidence.py::test_4c_defaults_belong_to_their_method[SLSQP-beta]
  /home/rem/repos/LizyML/lizyml/calibration/beta.py:35: RuntimeWarning: invalid value encountered in divide
    np.exp(x) / (1.0 + np.exp(x)),

tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[beta-params4]
tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[beta-params4]
  /home/rem/repos/LizyML/lizyml/calibration/beta.py:108: OptimizeWarning: Initial guess is not within the specified bounds
    result = minimize(neg_log_likelihood, **kwargs)

tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[beta-params4]
  /tmp/claude-1000/pytest-of-rem/pytest-143/test_generated_fitter_matches_4/eq_beta_2/train.py:1561: OptimizeWarning: Initial guess is not within the specified bounds
    result = minimize(objective, jac=jac, **kwargs)

tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[platt-params5]
tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[platt-params5]
  /home/rem/repos/LizyML/lizyml/calibration/platt.py:138: OptimizeWarning: Initial guess is not within the specified bounds
    result = minimize(objective, jac=True if gradient else None, **kwargs)

tests/test_codegen/test_calibration_params_codegen.py::test_generated_fitter_matches_the_runtime_calibrator[platt-params5]
  /tmp/claude-1000/pytest-of-rem/pytest-143/test_generated_fitter_matches_5/eq_platt_2/train.py:1561: OptimizeWarning: Initial guess is not within the specified bounds
    result = minimize(objective, jac=jac, **kwargs)

tests/test_codegen/test_equivalence.py: 1 warning
tests/test_codegen/test_predict_subprocess_equivalence.py: 1 warning
tests/test_config/test_knob_reachability.py: 1 warning
tests/test_core/test_facade_orchestration.py: 4 warnings
tests/test_core/test_fit_params_override.py: 1 warning
tests/test_core/test_smart_managed_model_params.py: 18 warnings
tests/test_e2e/test_golden_contracts.py: 1 warning
tests/test_e2e/test_model_facade.py: 6 warnings
tests/test_e2e/test_multiclass_full.py: 7 warnings
tests/test_e2e/test_pairwise.py: 2 warnings
tests/test_e2e/test_reproducibility.py: 4 warnings
tests/test_estimators/test_feval_probabilities.py: 1 warning
tests/test_estimators/test_lgbm_objective_identity.py: 2 warnings
tests/test_estimators/test_lightgbm_parameter_names.py: 2 warnings
tests/test_estimators/test_provider_protocol_drift.py: 6 warnings
tests/test_evaluation/test_confusion.py: 1 warning
tests/test_explain/test_explain.py: 3 warnings
tests/test_persistence/test_applied_training_params.py: 1 warning
tests/test_plots/test_classification_plots.py: 3 warnings
tests/test_plots/test_plots.py: 1 warning
tests/test_training/test_cv_refit_parity.py: 7 warnings
  /home/rem/repos/LizyML/lizyml/core/model.py:286: UserWarning: task='multiclass' with split.method='kfold' does not preserve class distribution. Consider using 'stratified_kfold' instead.
    splitter = build_splitter(

tests/test_config/test_inner_valid_roundtrip.py::test_legacy_validation_ratio_stays_auto_resolve
  /home/rem/repos/LizyML/.venv/lib/python3.12/site-packages/pydantic/main.py:250: DeprecationWarning: `validation_ratio` is deprecated; use `inner_valid.ratio` instead. Will be removed in v1.0.
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)

tests/test_config/test_knob_reachability.py: 8 warnings
tests/test_core/test_config_propagation.py: 2 warnings
tests/test_core/test_fit_params_override.py: 12 warnings
tests/test_e2e/test_model_facade.py: 1 warning
tests/test_e2e/test_pairwise.py: 9 warnings
tests/test_persistence/test_applied_training_params.py: 37 warnings
  /home/rem/repos/LizyML/.venv/lib/python3.12/site-packages/pydantic/main.py:716: DeprecationWarning: `validation_ratio` is deprecated; use `inner_valid.ratio` instead. Will be removed in v1.0.
    return cls.__pydantic_validator__.validate_python(

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/cv_trainer.py:195: UserWarning: Too few groups (1) for group-isolated inner valid (need >= 4). Falling back to StratifiedTimeHoldout.
    iv_result = self.inner_valid.split(

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/cv_trainer.py:195: UserWarning: Too few groups (2) for group-isolated inner valid (need >= 4). Falling back to StratifiedTimeHoldout.
    iv_result = self.inner_valid.split(

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/refit_trainer.py:105: UserWarning: Too few groups (3) for group-isolated inner valid (need >= 4). Falling back to StratifiedTimeHoldout.
    iv_result = self.inner_valid.split(n_samples, y=y.to_numpy(), groups=groups)

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/cv_trainer.py:195: UserWarning: Too few groups (1) for group-isolated inner valid (need >= 4). Falling back to TimeHoldout.
    iv_result = self.inner_valid.split(

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/cv_trainer.py:195: UserWarning: Too few groups (2) for group-isolated inner valid (need >= 4). Falling back to TimeHoldout.
    iv_result = self.inner_valid.split(

tests/test_config/test_knob_reachability.py::test_config_value_reaches_the_constructor[BetaCalibrator.params-0]
  /home/rem/repos/LizyML/lizyml/training/refit_trainer.py:105: UserWarning: Too few groups (3) for group-isolated inner valid (need >= 4). Falling back to TimeHoldout.
    iv_result = self.inner_valid.split(n_samples, y=y.to_numpy(), groups=groups)

tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
tests/test_core/test_fit_params_override.py::test_categorical_feature_from_fit_params_reaches_the_dataset
  /home/rem/repos/LizyML/.venv/lib/python3.12/site-packages/lightgbm/basic.py:2137: UserWarning: categorical_feature keyword has been found in `params` and will be ignored.
  Please use categorical_feature argument of the Dataset constructor to pass this parameter.
    _log_warning(

tests/test_core/test_param_domain.py::test_a_numpy_array_subclass_is_refused_for_the_same_reason_a_scalar_is
  /home/rem/repos/LizyML/tests/test_core/test_param_domain.py:1030: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal with linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    ("numpy matrix", np.matrix([[1.0, 2.0]])),

tests/test_core/test_smart_managed_model_params.py: 35 warnings
tests/test_persistence/test_applied_training_params.py: 1 warning
tests/test_tuning/test_direction_reconciliation.py: 7 warnings
tests/test_tuning/test_search_space_name_validation.py: 12 warnings
  /home/rem/repos/LizyML/lizyml/core/_model_tuning.py:333: UserWarning: task='multiclass' with split.method='kfold' does not preserve class distribution. Consider using 'stratified_kfold' instead.
    splitter = build_splitter(

tests/test_e2e/test_pairwise.py::TestTuningThenCalibration::test_tune_then_fit_with_calibration
  /home/rem/repos/LizyML/lizyml/tuning/tuner.py:503: UserWarning: LightGBM will train with num_leaves=3647 (derived by auto_num_leaves from max_depth=12). LightGBM allocates memory for every configured leaf, not only the leaves a tree grows: about 1.2 GiB of extra memory is expected (approximate: the histogram cache and the trees of 2 booster(s) kept at once; an upper bound under early stopping; isotonic calibration is not counted). To lower it, use a shallower max_depth, or set auto_num_leaves=False with a smaller num_leaves.
    return objective(trial)

tests/test_e2e/test_pairwise.py::TestTuningThenCalibration::test_tune_then_fit_with_calibration
  /home/rem/repos/LizyML/tests/test_e2e/test_pairwise.py:287: UserWarning: LightGBM will train with num_leaves=3647 (derived by auto_num_leaves from max_depth=12). LightGBM allocates memory for every configured leaf, not only the leaves a tree grows: about 1.7 GiB of extra memory is expected (approximate: the histogram cache and the trees of 3 booster(s) kept at once; an upper bound under early stopping; isotonic calibration is not counted). To lower it, use a shallower max_depth, or set auto_num_leaves=False with a smaller num_leaves.
    fit_result = m.fit(data=df)

tests/test_explain/test_explain.py: 5 warnings
tests/test_explain/test_shap_importance_per_fold_pipeline.py: 12 warnings
tests/test_persistence/test_artifact_compat.py: 4 warnings
tests/test_persistence/test_h0133_acceptance.py: 12 warnings
  /home/rem/repos/LizyML/.venv/lib/python3.12/site-packages/shap/explainers/_tree.py:586: UserWarning: LightGBM binary classifier with TreeExplainer shap values output has changed to a list of ndarray
    warnings.warn(

tests/test_splitters/test_blocked_group_kfold.py::TestFoldCount::test_single_cutoff
  /home/rem/repos/LizyML/tests/test_splitters/test_blocked_group_kfold.py:119: UserWarning: Skipping fold: train=0 rows, valid=4 rows (min_train=1, min_valid=1)
    folds = list(splitter.split(len(block_values), y=y, groups=groups))

tests/test_splitters/test_blocked_group_kfold.py::TestLeakPrevention::test_no_temporal_leak
  /home/rem/repos/LizyML/tests/test_splitters/test_blocked_group_kfold.py:168: UserWarning: Skipping fold: train=0 rows, valid=4 rows (min_train=1, min_valid=1)
    for train_idx, valid_idx in splitter.split(

tests/test_splitters/test_blocked_group_kfold.py::TestEdgeCases::test_index_dtype_is_intp
  /home/rem/repos/LizyML/tests/test_splitters/test_blocked_group_kfold.py:461: UserWarning: Skipping fold: train=0 rows, valid=4 rows (min_train=1, min_valid=1)
    for train_idx, valid_idx in splitter.split(

tests/test_training/test_blocked_group_inner_valid.py::TestBlockedGroupInnerValidFallback::test_fallback_with_2_groups
  /home/rem/repos/LizyML/tests/test_training/test_blocked_group_inner_valid.py:159: UserWarning: Too few groups (2) for group-isolated inner valid (need >= 4). Falling back to StratifiedTimeHoldout.
    result = strategy.split(len(y), y=y, groups=groups)

tests/test_tuning/test_resume_open_round.py::test_crash_mid_round2_reattach_finishes_round2[subprocess]
  /home/rem/repos/LizyML/tests/test_tuning/test_resume_open_round.py:150: UserWarning: study 's' was created with other library versions (lizyml 0.17.2.dev71+g289f591a8 -> 0.17.2.dev70+g3f8b65fc6). The objective identity matches, so the study continues.
    result = model.tune(resume=True, **kwargs)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
22486 passed, 246 skipped, 31 deselected, 982 warnings in 219.82s (0:03:39)
[run-exclusive] h0139-census-pd3 finished in 223s, exit 0
