Repository Analysis

optuna/optuna

A hyperparameter optimization framework

29.8 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of optuna/optuna, a Python project with 14,499 GitHub stars. SynthScan v2.0 examined 71,420 lines of code across 412 source files, recording 1804 pattern matches distributed across 18 syntactic categories. The overall adjusted score of 29.8 places this repository in the Moderate AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

29.8
Adjusted Score
29.8
Raw Score
100%
Time Factor
2026-07-14
Last Push
14.5K
Stars
Python
Language
71.4K
Lines of Code
412
Files
1.8K
Pattern Hits
2026-07-14
Scan Date
0.07
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 30MEDIUM 89LOW 1685

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 1804 distinct pattern matches across 18 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Hyper-Verbose Identifiers921 hits · 907 pts
SeverityFileLineSnippetContext
LOWtutorial/20_recipes/005_user_defined_sampler.py96 def infer_relative_search_space(self, study, trial):CODE
LOWtests/test_transform.py28def test_search_space_transform_shapes_dtypes(param: Any, distribution: BaseDistribution) -> None:CODE
LOWtests/test_transform.py44def test_search_space_transform_encoding() -> None:CODE
LOWtests/test_transform.py92def test_search_space_transform_numerical(CODE
LOWtests/test_transform.py146def test_search_space_transform_values_categorical(CODE
LOWtests/test_transform.py161def test_search_space_transform_untransform_params() -> None:CODE
LOWtests/test_transform.py208def test_transform_untransform_params_at_bounds(CODE
LOWtests/test_imports.py6def test_try_import_is_successful() -> None:CODE
LOWtests/test_imports.py13def test_try_import_is_successful_other_error() -> None:CODE
LOWtests/test_imports.py21def test_try_import_not_successful() -> None:CODE
LOWtests/test_convert_positional_args.py24def test_convert_positional_args_decorator() -> None:CODE
LOWtests/test_convert_positional_args.py36def test_convert_positional_args_future_warning_for_methods() -> None:CODE
LOWtests/test_convert_positional_args.py49def test_convert_positional_args_future_warning() -> None:CODE
LOWtests/test_convert_positional_args.py70def test_convert_positional_args_mypy_type_inference() -> None:CODE
LOWtests/test_convert_positional_args.py104def test_convert_positional_args_invalid_previous_positional_arg_names(CODE
LOWtests/test_convert_positional_args.py125def test_convert_positional_args_invalid_positional_args() -> None:CODE
LOWtests/test_deprecated.py36def test_deprecation_raises_error_for_invalid_version(CODE
LOWtests/test_deprecated.py46def test_deprecation_decorator() -> None:CODE
LOWtests/test_deprecated.py65def test_deprecation_instance_method_decorator() -> None:CODE
LOWtests/test_deprecated.py79def test_deprecation_class_decorator() -> None:CODE
LOWtests/test_deprecated.py96def test_deprecation_class_decorator_name() -> None:CODE
LOWtests/test_deprecated.py108def test_deprecation_decorator_name() -> None:CODE
LOWtests/test_deprecated.py124def test_deprecation_text_specified(text: str | None) -> None:CODE
LOWtests/test_deprecated.py152def test_deprecation_class_text_specified(text: str | None) -> None:CODE
LOWtests/test_deprecated.py182def test_deprecation_decorator_default_removed_version() -> None:CODE
LOWtests/test_distributions.py74def test_json_to_distribution() -> None:CODE
LOWtests/test_distributions.py83def test_abbreviated_json_to_distribution() -> None:CODE
LOWtests/test_distributions.py525def test_categorical_init_error() -> None:CODE
LOWtests/test_distributions.py530def test_categorical_distribution_different_sequence_types() -> None:CODE
LOWtests/test_distributions.py538def test_convert_old_distribution_to_new_distribution() -> None:CODE
LOWtests/test_distributions.py108def test_distribution_to_json() -> None:CODE
LOWtests/test_distributions.py119def test_check_distribution_compatibility() -> None:CODE
LOWtests/test_distributions.py200def test_int_internal_representation(value: Any) -> None:CODE
LOWtests/test_distributions.py224def test_int_internal_representation_error(value: Any, kwargs: dict[str, Any]) -> None:CODE
LOWtests/test_distributions.py234def test_float_internal_representation(value: Any) -> None:CODE
LOWtests/test_distributions.py258def test_float_internal_representation_error(value: Any, kwargs: dict[str, Any]) -> None:CODE
LOWtests/test_distributions.py264def test_categorical_internal_representation() -> None:CODE
LOWtests/test_distributions.py330def test_categorical_contains() -> None:CODE
LOWtests/test_distributions.py339def test_empty_range_contains() -> None:CODE
LOWtests/test_distributions.py419def test_invalid_distribution() -> None:CODE
LOWtests/test_distributions.py459def test_int_distribution_asdict(key: str, low: int, high: int, log: bool, step: int) -> None:CODE
LOWtests/test_distributions.py472def test_float_distribution_asdict(CODE
LOWtests/test_distributions.py570def test_convert_old_distribution_to_new_distribution_noop() -> None:CODE
LOWtests/test_multi_objective.py24def assert_is_output_equal_to_ans(CODE
LOWtests/test_multi_objective.py46def test_get_pareto_front_trials(CODE
LOWtests/test_multi_objective.py73def test_get_pareto_front_trials_with_constraint(CODE
LOWtests/test_cli.py139def test_create_study_command_with_study_name() -> None:CODE
LOWtests/test_cli.py154def test_create_study_command_without_storage_url() -> None:CODE
LOWtests/test_cli.py164def test_create_study_command_with_storage_env() -> None:CODE
LOWtests/test_cli.py48def objective_func_branched_search_space(trial: Trial) -> float:CODE
LOWtests/test_cli.py59def objective_func_multi_objective(trial: Trial) -> tuple[float, float]:CODE
LOWtests/test_cli.py121def test_create_study_command() -> None:CODE
LOWtests/test_cli.py183def test_create_study_command_with_direction() -> None:CODE
LOWtests/test_cli.py205def test_create_study_command_with_multiple_directions() -> None:CODE
LOWtests/test_cli.py257def test_delete_study_command() -> None:CODE
LOWtests/test_cli.py274def test_delete_study_command_without_storage_url() -> None:CODE
LOWtests/test_cli.py282def test_study_set_user_attr_command() -> None:CODE
LOWtests/test_cli.py366def test_study_names_command_without_storage_url() -> None:CODE
LOWtests/test_cli.py442def test_studies_command_flatten(output_format: str | None) -> None:CODE
LOWtests/test_cli.py611def test_trials_command_flatten(CODE
861 more matches not shown…
Unused Imports482 hits · 474 pts
SeverityFileLineSnippetContext
LOWtutorial/20_recipes/012_artifact_tutorial.py252CODE
LOWtutorial/10_key_features/002_configurations.py17CODE
LOWtests/test_convert_positional_args.py1CODE
LOWtests/test_deprecated.py1CODE
LOWtests/test_distributions.py1CODE
LOWtests/test_multi_objective.py1CODE
LOWtests/test_cli.py1CODE
LOWtests/trial_tests/test_frozen.py1CODE
LOWtests/trial_tests/test_trials.py1CODE
LOWtests/trial_tests/test_trial.py1CODE
LOWtests/trial_tests/test_fixed.py1CODE
LOWtests/pruners_tests/test_percentile.py1CODE
LOWtests/pruners_tests/test_median.py1CODE
LOWtests/pruners_tests/test_patient.py1CODE
LOWtests/pruners_tests/test_wilcoxon.py1CODE
LOWtests/pruners_tests/test_successive_halving.py1CODE
LOWtests/pruners_tests/test_hyperband.py1CODE
LOWtests/study_tests/test_optimize.py1CODE
LOWtests/study_tests/test_study.py1CODE
LOWtests/study_tests/test_multi_objective.py1CODE
LOWtests/study_tests/test_dataframe.py1CODE
LOWtests/hypervolume_tests/test_hssp.py1CODE
LOWtests/hypervolume_tests/test_box_decomposition.py1CODE
LOWtests/importance_tests/test_importance_evaluators.py1CODE
LOWtests/importance_tests/test_init.py1CODE
LOWtests/importance_tests/fanova_tests/test_tree.py1CODE
LOWtests/importance_tests/pedanova_tests/test_evaluator.py1CODE
LOW…ce_tests/pedanova_tests/test_scott_parzen_estimator.py1CODE
LOWtests/artifacts_tests/test_upload_artifact.py1CODE
LOWtests/artifacts_tests/test_boto3.py1CODE
LOWtests/artifacts_tests/test_download_artifact.py1CODE
LOWtests/artifacts_tests/test_gcs.py1CODE
LOWtests/artifacts_tests/stubs.py1CODE
LOWtests/artifacts_tests/test_list_artifact_meta.py1CODE
LOWtests/storages_tests/test_grpc.py1CODE
LOWtests/storages_tests/test_heartbeat.py1CODE
LOWtests/storages_tests/test_cached_storage.py1CODE
LOWtests/storages_tests/test_storages.py1CODE
LOWtests/storages_tests/test_with_server.py1CODE
LOWtests/storages_tests/rdb_tests/test_storage.py1CODE
LOWtests/storages_tests/rdb_tests/test_storage.py19CODE
LOWtests/storages_tests/rdb_tests/test_models.py1CODE
LOWtests/storages_tests/rdb_tests/create_db.py39CODE
LOWtests/storages_tests/journal_tests/test_journal.py1CODE
LOW…ages_tests/journal_tests/test_combination_with_grpc.py1CODE
LOWtests/samplers_tests/test_grid.py1CODE
LOWtests/samplers_tests/test_gp.py1CODE
LOWtests/samplers_tests/test_cmaes.py1CODE
LOWtests/samplers_tests/test_samplers.py1CODE
LOWtests/samplers_tests/test_base_gasampler.py1CODE
LOWtests/samplers_tests/test_nsgaii.py1CODE
LOWtests/samplers_tests/test_nsgaiii.py1CODE
LOWtests/samplers_tests/test_brute_force.py1CODE
LOWtests/samplers_tests/test_qmc.py1CODE
LOWtests/samplers_tests/tpe_tests/test_parzen_estimator.py1CODE
LOWtests/samplers_tests/tpe_tests/test_truncnorm.py1CODE
LOW…mplers_tests/tpe_tests/test_multi_objective_sampler.py1CODE
LOWtests/samplers_tests/tpe_tests/test_sampler.py1CODE
LOWtests/gp_tests/test_batched_lbfgsb.py1CODE
LOWtests/gp_tests/test_search_space.py1CODE
422 more matches not shown…
Decorative Section Separators54 hits · 200 pts
SeverityFileLineSnippetContext
MEDIUMtutorial/20_recipes/003_attributes.py12# ---------------------------------COMMENT
MEDIUMtutorial/20_recipes/003_attributes.py52# --------------------------------COMMENT
MEDIUMtutorial/20_recipes/001_rdb.py48# ------------COMMENT
MEDIUMtutorial/20_recipes/001_rdb.py78# --------------------COMMENT
MEDIUMtutorial/20_recipes/009_ask_and_tell.py154# ---------------COMMENT
MEDIUMtutorial/20_recipes/009_ask_and_tell.py156# ---------------COMMENT
MEDIUMtutorial/20_recipes/009_ask_and_tell.py193# -------------------COMMENT
MEDIUMtutorial/20_recipes/009_ask_and_tell.py195# -------------------COMMENT
MEDIUMtutorial/20_recipes/010_reuse_best_trial.py87# ----------------------------------------------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/013_wilcoxon_pruner.py186# ---------------------------------------------------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/013_wilcoxon_pruner.py195# -----------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py40# ---------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py42# ---------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py87# ----------------------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py89# ----------------------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py134# -------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py136# -------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py199# -------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py201# -------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/008_specify_params.py102# ----------------------------------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/008_specify_params.py104# ----------------------------------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/007_optuna_callback.py17# -------------------------------------------------------COMMENT
MEDIUMtutorial/20_recipes/012_artifact_tutorial.py440# ----------COMMENT
MEDIUMtutorial/20_recipes/002_multi_objective.py117# --------------------------------COMMENT
MEDIUM…_key_features/003_efficient_optimization_algorithms.py67# ------------------COMMENT
MEDIUM…_key_features/003_efficient_optimization_algorithms.py96# ------------------COMMENT
MEDIUM…_key_features/003_efficient_optimization_algorithms.py151# ----------------------------------------COMMENT
MEDIUM…_key_features/003_efficient_optimization_algorithms.py179# -------------------------------COMMENT
MEDIUMtutorial/10_key_features/002_configurations.py45# -------------------------COMMENT
MEDIUMtutorial/10_key_features/001_first.py72# ------------COMMENT
MEDIUMtutorial/10_key_features/005_visualization.py172# --------------COMMENT
MEDIUMtutorial/10_key_features/005_visualization.py228# ---------------------------COMMENT
MEDIUMtutorial/10_key_features/004_distributed.py152# ----------------------------------------------COMMENT
MEDIUMtutorial/10_key_features/004_distributed.py218# ---------------------------------------COMMENT
MEDIUMtutorial/10_key_features/004_distributed.py278# ---------------------------------------------COMMENT
MEDIUMtests/study_tests/test_multi_objective.py46 # ╔═════╤═════╤═════╤═════╤═════╗COMMENT
MEDIUMtests/study_tests/test_multi_objective.py48 # ╟─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/study_tests/test_multi_objective.py50 # ╟─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/study_tests/test_multi_objective.py52 # value0 ╟─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/study_tests/test_multi_objective.py54 # ╟─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/study_tests/test_multi_objective.py56 # ╚═════╧═════╧═════╧═════╧═════╝COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py308 # ╔═════╤═════╤═════╤═════╤═════╤═════╗COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py310 # ╟─────┼─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py312 # ╟─────┼─feasible ─┼─────┼─────┼─────╢COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py314 # c1 ╟─────┼─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py316 # ╟─────┼─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py318 # ╟─────┼─────┼─────┼─────┼─────┼─────╢COMMENT
MEDIUMtests/samplers_tests/test_nsgaii.py320 # ╚═════╧═════╧═════╧═════╧═════╧═════╝COMMENT
MEDIUMoptuna/samplers/_brute_force.py62 # ┌────────────┬─────────────────┬────────────┐COMMENT
MEDIUMoptuna/samplers/_brute_force.py64 # ├────────────┼─────────────────┼────────────┤COMMENT
MEDIUMoptuna/samplers/_brute_force.py66 # ├────────────┼─────────────────┼────────────┤COMMENT
MEDIUMoptuna/samplers/_brute_force.py68 # ├────────────┼─────────────────┼────────────┤COMMENT
MEDIUMoptuna/samplers/_brute_force.py70 # ├────────────┼─────────────────┼────────────┤COMMENT
MEDIUMoptuna/samplers/_brute_force.py72 # └────────────┴─────────────────┴────────────┘COMMENT
Docstring Block Structure20 hits · 100 pts
SeverityFileLineSnippetContext
HIGHoptuna/visualization/_timeline.py38Plot the timeline of a study. Args: study: A :class:`~optuna.study.Study` object whose trials aSTRING
HIGHoptuna/visualization/matplotlib/_timeline.py24Plot the timeline of a study. .. seealso:: Please refer to :func:`optuna.visualization.plot_timeline` for aSTRING
HIGHoptuna/storages/_base.py55Create a new study from a name. If no name is specified, the storage class generates a name. The returnSTRING
HIGHoptuna/storages/_base.py135Read the ID of a study. Args: study_name: Name of the study. Returns: STRING
HIGHoptuna/storages/_base.py152Read the study name of a study. Args: study_id: ID of the study. Returns: STRING
HIGHoptuna/storages/_base.py169Read whether a study maximizes or minimizes an objective. Args: study_id: ID of a sSTRING
HIGHoptuna/storages/_base.py186Read the user-defined attributes of a study. Args: study_id: ID of the study. STRING
HIGHoptuna/storages/_base.py203Read the optuna-internal attributes of a study. Args: study_id: ID of the study. STRING
HIGHoptuna/storages/_base.py232Create and add a new trial to a study. The returned trial ID is unique among all current and deleted trials. STRING
HIGHoptuna/storages/_base.py281Read the trial ID of a trial. Args: study_id: ID of the study. trial_nuSTRING
HIGHoptuna/storages/_base.py302Read the trial number of a trial. .. note:: The trial number is only unique within a study, and isSTRING
HIGHoptuna/storages/_base.py322Read the parameter of a trial. Args: trial_id: ID of the trial. param_nSTRING
HIGHoptuna/storages/_base.py345Update the state and values of a trial. Set return values of an objective function to values argument. STRING
HIGHoptuna/storages/_base.py445Read a trial. Args: trial_id: ID of the trial. Returns: Trial STRING
HIGHoptuna/storages/_base.py467Read all trials in a study. Args: study_id: ID of the study. deepcopy: STRING
HIGHoptuna/storages/_base.py490Count the number of trials in a study. Args: study_id: ID of the study. STRING
HIGHoptuna/storages/_base.py512Return the trial with the best value in a study. This method is valid only during single-objective optimizationSTRING
HIGHoptuna/storages/_base.py551Read the parameter dictionary of a trial. Args: trial_id: ID of the trial. STRING
HIGHoptuna/storages/_base.py568Read the user-defined attributes of a trial. Args: trial_id: ID of the trial. STRING
HIGHoptuna/storages/_base.py584Read the optuna-internal attributes of a trial. Args: trial_id: ID of the trial. STRING
Modern Structural Boilerplate98 hits · 99 pts
SeverityFileLineSnippetContext
LOW…mplers_tests/tpe_tests/test_multi_objective_sampler.py21 def set_trial_system_attr(self, _: int, key: str, value: dict) -> None:CODE
LOWoptuna/logging.py17__all__ = [CODE
LOWoptuna/logging.py146def set_verbosity(verbosity: int) -> None:CODE
LOWoptuna/_typing.py18__all__ = ["JSONSerializable"]CODE
LOWoptuna/__init__.py28__all__ = [CODE
LOWoptuna/_warnings.py41__all__ = ["optuna_warn"]CODE
LOWoptuna/cli.py945def _set_verbosity(args: Namespace) -> None:CODE
LOWoptuna/cli.py963def _set_log_file(args: Namespace) -> None:CODE
LOWoptuna/visualization/_plotly_imports.py23__all__ = ["_imports", "plotly", "go", "Contour", "Scatter", "make_subplots"]CODE
LOWoptuna/visualization/__init__.py17__all__ = [CODE
LOWoptuna/visualization/_utils.py22__all__ = ["is_available"]CODE
LOWoptuna/visualization/matplotlib/__init__.py16__all__ = [CODE
LOWoptuna/visualization/matplotlib/_param_importances.py120def _set_bar_labels(info: _ImportancesInfo, fig: "Figure", ax: "Axes", offset: float) -> None:CODE
LOWoptuna/visualization/matplotlib/_matplotlib_imports.py30__all__ = [CODE
LOWoptuna/visualization/matplotlib/_utils.py16__all__ = ["is_available"]CODE
LOWoptuna/artifacts/__init__.py11__all__ = [CODE
LOWoptuna/storages/_base.py92 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_base.py112 def set_study_system_attr(self, study_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_base.py398 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_base.py420 def set_trial_system_attr(self, trial_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_cached_storage.py102 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_cached_storage.py105 def set_study_system_attr(self, study_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_cached_storage.py201 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_cached_storage.py204 def set_trial_system_attr(self, trial_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/__init__.py22__all__ = [CODE
LOWoptuna/storages/_in_memory.py102 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_in_memory.py108 def set_study_system_attr(self, study_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_in_memory.py292 def _update_cache(self, trial_id: int, study_id: int) -> None:CODE
LOWoptuna/storages/_in_memory.py337 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_in_memory.py348 def set_trial_system_attr(self, trial_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_in_memory.py367 def _set_trial(self, trial_id: int, trial: FrozenTrial) -> None:CODE
LOWoptuna/storages/journal/__init__.py12__all__ = [CODE
LOWoptuna/storages/journal/_storage.py185 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/journal/_storage.py191 def set_study_system_attr(self, study_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/journal/_storage.py363 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/journal/_storage.py373 def set_trial_system_attr(self, trial_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_grpc/client.py80 def _setup(self) -> None:CODE
LOWoptuna/storages/_grpc/client.py143 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_grpc/client.py154 def set_study_system_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_grpc/client.py318 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_grpc/client.py332 def set_trial_system_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_grpc/__init__.py5__all__ = [CODE
LOWoptuna/storages/_rdb/storage.py763 def set_trial_user_attr(self, trial_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_rdb/storage.py773 def set_trial_system_attr(self, trial_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_rdb/storage.py337 def set_study_user_attr(self, study_id: int, key: str, value: Any) -> None:CODE
LOWoptuna/storages/_rdb/storage.py349 def set_study_system_attr(self, study_id: int, key: str, value: JSONSerializable) -> None:CODE
LOWoptuna/storages/_rdb/storage.py991 def _set_default_engine_kwargs_for_mysql(url: str, engine_kwargs: dict[str, Any]) -> None:CODE
LOWoptuna/storages/_rdb/storage.py1145 def _set_alembic_revision(self, revision: str) -> None:CODE
LOWoptuna/study/_dataframe.py19__all__ = ["pd"]CODE
LOWoptuna/study/__init__.py13__all__ = [CODE
LOWoptuna/study/study.py707 def set_user_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/study/study.py752 def set_system_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/study/study.py1049 def set_metric_names(self, metric_names: list[str]) -> None:CODE
LOWoptuna/search_space/__init__.py7__all__ = [CODE
LOWoptuna/pruners/__init__.py19__all__ = [CODE
LOWoptuna/trial/_base.py102 def set_user_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/trial/_base.py107 def set_system_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/trial/_fixed.py139 def set_user_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/trial/_fixed.py143 def set_system_attr(self, key: str, value: Any) -> None:CODE
LOWoptuna/trial/_trial.py549 def set_user_attr(self, key: str, value: Any) -> None:CODE
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Self-Referential Comments26 hits · 82 pts
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MEDIUMtutorial/20_recipes/014_ablation_study_by_optuna.py45# Define an objective function using ``suggest_categorical`` and ``suggest_float``COMMENT
MEDIUMtutorial/20_recipes/008_specify_params.py42# Define the objective function.COMMENT
MEDIUMtutorial/10_key_features/005_visualization.py125# Define the objective function.COMMENT
MEDIUMtests/test_cli.py322 # Create a study.COMMENT
MEDIUMtests/study_tests/test_study.py405 # Create a new study.COMMENT
MEDIUMtests/study_tests/test_study.py1150 # Create a trial to retrieve it as the `study.best_trial`.COMMENT
MEDIUMtests/study_tests/test_study.py1652 # Create a study and ask for a new trial.COMMENT
MEDIUMtests/storages_tests/test_callbacks.py24 # Create a trial and manually set it as failed.COMMENT
MEDIUMtests/storages_tests/test_cached_storage.py134 # Create a trial via CachedStorage and update it via backend storage directly.COMMENT
MEDIUMtests/storages_tests/test_with_server.py69 # Create a studyCOMMENT
MEDIUMtests/storages_tests/test_with_server.py130 # Create a new study to confirm the study can load trial properly.COMMENT
MEDIUMtests/storages_tests/rdb_tests/test_storage.py225 # Create a new study.COMMENT
MEDIUMtests/storages_tests/rdb_tests/test_storage.py275 # Create a new study.COMMENT
MEDIUMtests/storages_tests/rdb_tests/create_db.py85 # Create an empty study.COMMENT
MEDIUMtests/storages_tests/rdb_tests/create_db.py88 # Create a study for single-objective optimization.COMMENT
MEDIUMtests/storages_tests/rdb_tests/create_db.py93 # Create a study for multi-objective optimization.COMMENT
MEDIUMtests/storages_tests/rdb_tests/create_db.py106 # Create a study for distributions upgrade.COMMENT
MEDIUMtests/samplers_tests/test_samplers.py67# This function is used only in test_reproducible_in_other_process, but declared at top-levelCOMMENT
MEDIUM…ion_examples/optuna.visualization.plot_pareto_front.py32# The following code snippet shows how to plot a 2-dimensional Pareto frontCOMMENT
MEDIUMoptuna/visualization/_utils.py132 # This function is not raising when target is missing, since we'reCOMMENT
MEDIUMoptuna/storages/journal/_file.py63 open(self._file_path, "ab").close() # Create a file if it does not exist.CODE
MEDIUMoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py398 # This class is part of an EXPERIMENTAL API.COMMENT
MEDIUMoptuna/study/study.py803 # Create a dataframe from the study.STRING
MEDIUMoptuna/pruners/_hyperband.py269 # This class is assumed to be passed toCOMMENT
MEDIUM…plers/_nsgaiii/_elite_population_selection_strategy.py22# Define a coefficient for scaling intervals, used in _filter_inf() to replace +-inf.COMMENT
MEDIUMoptuna/samplers/_tpe/_truncnorm.py1# This file contains the codes from SciPy project.COMMENT
Over-Commented Block67 hits · 66 pts
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LOWtutorial/20_recipes/001_rdb.py61# reproducibility, you need to restore the sampler with using ``pickle`` as follows::COMMENT
LOWtutorial/20_recipes/001_rdb.py81#COMMENT
LOWtutorial/20_recipes/009_ask_and_tell.py81 clf.fit(X_train, y_train)COMMENT
LOWtutorial/20_recipes/009_ask_and_tell.py101# from sklearn.linear_model import SGDClassifierCOMMENT
LOWtutorial/20_recipes/009_ask_and_tell.py121# trial = study.ask()COMMENT
LOWtutorial/20_recipes/009_ask_and_tell.py141# score = clf.score(X_valid, y_valid)COMMENT
LOWtutorial/20_recipes/009_ask_and_tell.py241# :class:`optuna.samplers.TPESampler` class can take a boolean parameter ``constant_liar``,COMMENT
LOWtutorial/20_recipes/010_reuse_best_trial.py81# Pass ``study.best_trial`` as the argument of ``detailed_objective``.COMMENT
LOWtutorial/20_recipes/013_wilcoxon_pruner.py181COMMENT
LOWtutorial/20_recipes/013_wilcoxon_pruner.py201# too often, the optimization may get stuck in a local optimum, so we must tune the thresholdCOMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py41# Basic Ablation StudyCOMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py81# a finite ``step``. Using ``suggest_float`` without ``step`` will raise an error becauseCOMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py121# The sampler explores all valid paths through the conditional search space:COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py141#COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py161# )COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py181# python run_ablation.pyCOMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py201# -------------------------------------------COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py221# def objective(trial: optuna.Trial) -> float:COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py241# )COMMENT
LOWtutorial/20_recipes/014_ablation_study_by_optuna.py261# if trial.state == optuna.trial.TrialState.RUNNING:COMMENT
LOWtutorial/20_recipes/008_specify_params.py101#COMMENT
LOWtutorial/20_recipes/012_artifact_tutorial.py321# Each function is as follows.COMMENT
LOWtutorial/20_recipes/012_artifact_tutorial.py421 write("best_atoms.png", best_atoms, rotation=("315x,0y,0z"))COMMENT
LOWtutorial/20_recipes/012_artifact_tutorial.py441#COMMENT
LOWtutorial/20_recipes/011_journal_storage.py41COMMENT
LOWtutorial/20_recipes/004_cli.py41COMMENT
LOWtutorial/20_recipes/004_cli.py61#COMMENT
LOWtutorial/20_recipes/002_multi_objective.py121# Specifically, in this example, we want to minimize the FLOPS (we want a faster model)COMMENT
LOW…_key_features/003_efficient_optimization_algorithms.py61study = optuna.create_study(sampler=optuna.samplers.CmaEsSampler())COMMENT
LOW…_key_features/003_efficient_optimization_algorithms.py81#COMMENT
LOW…_key_features/003_efficient_optimization_algorithms.py141optuna.logging.get_logger("optuna").addHandler(logging.StreamHandler(sys.stdout))COMMENT
LOW…_key_features/003_efficient_optimization_algorithms.py161# This table is from the `Ozaki et al., Hyperparameter Optimization Methods: Overview and Characteristics, in IEICE TranCOMMENT
LOW…_key_features/003_efficient_optimization_algorithms.py181#COMMENT
LOWtutorial/10_key_features/002_configurations.py41COMMENT
LOWtutorial/10_key_features/002_configurations.py61 if classifier_name == "SVC":COMMENT
LOWtutorial/10_key_features/002_configurations.py81# layers = []COMMENT
LOWtutorial/10_key_features/001_first.py41#COMMENT
LOWtutorial/10_key_features/001_first.py61# We can see that the ``x`` value found by Optuna is close to the optimal value of ``2``.COMMENT
LOWtutorial/10_key_features/004_distributed.py141study = optuna.create_study(COMMENT
LOWtutorial/10_key_features/004_distributed.py161# it cannot be used for multi-process optimization.COMMENT
LOWtutorial/10_key_features/004_distributed.py181# def run_optimization(_):COMMENT
LOWtutorial/10_key_features/004_distributed.py201# Running trial trial.number=3 in process 4607COMMENT
LOWtutorial/10_key_features/004_distributed.py221# it is likely to cause race conditions when accessed by multiple machines.COMMENT
LOWtutorial/10_key_features/004_distributed.py241# x = trial.suggest_float("x", -10, 10)COMMENT
LOWtutorial/10_key_features/004_distributed.py261# [I 2025-06-03 14:07:45,306] A new study created in RDB with name: distributed_testCOMMENT
LOWtutorial/10_key_features/004_distributed.py281# In that case, you can use :class:`~optuna.storages.GrpcStorageProxy`COMMENT
LOWtutorial/10_key_features/004_distributed.py301#COMMENT
LOWtutorial/10_key_features/004_distributed.py321#COMMENT
LOWtests/study_tests/test_multi_objective.py41COMMENT
LOWtests/samplers_tests/test_nsgaii.py301 directions = [direction]COMMENT
LOWdocs/source/conf.py1# -*- coding: utf-8 -*-COMMENT
LOWdocs/source/conf.py121# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',COMMENT
LOWdocs/source/conf.py141 #COMMENT
LOWoptuna/visualization/matplotlib/_contour.py321 zmap[(xindex, yindex)] = zCOMMENT
LOWoptuna/storages/journal/_storage.py321 if state == TrialState.RUNNING:COMMENT
LOWoptuna/storages/_rdb/alembic.ini1# A generic, single database configuration.COMMENT
LOWoptuna/storages/_rdb/alembic.ini21# the 'revision' command, regardless of autogenerateCOMMENT
LOWoptuna/samplers/_brute_force.py61 # A node takes one of the following four states:COMMENT
LOWoptuna/samplers/_brute_force.py81 # Examples:COMMENT
LOWoptuna/samplers/_brute_force.py101 # └ 2: a2_node (Unexpanded)COMMENT
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Deep Nesting72 hits · 65 pts
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LOWtests/test_transform.py92CODE
LOWtests/test_cli.py64CODE
LOWtests/test_cli.py533CODE
LOWtests/test_cli.py611CODE
LOWtests/test_cli.py687CODE
LOWtests/test_cli.py768CODE
LOWtests/test_cli.py843CODE
LOWtests/test_cli.py928CODE
LOWtests/study_tests/test_study.py1087CODE
LOWtests/study_tests/test_dataframe.py51CODE
LOWtests/storages_tests/journal_tests/test_journal.py124CODE
LOWtests/samplers_tests/test_nsgaii.py297CODE
LOWtests/samplers_tests/test_nsgaii.py373CODE
LOWtests/visualization_tests/test_contour.py396CODE
LOWtests/visualization_tests/test_hypervolume_history.py25CODE
LOWtests/visualization_tests/test_hypervolume_history.py28CODE
LOWtests/visualization_tests/test_hypervolume_history.py29CODE
LOWtests/visualization_tests/test_rank.py128CODE
LOWoptuna/distributions.py565CODE
LOWoptuna/distributions.py709CODE
LOWoptuna/distributions.py531CODE
LOWoptuna/cli.py82CODE
LOWoptuna/cli.py98CODE
LOWoptuna/cli.py244CODE
LOWoptuna/progress_bar.py76CODE
LOWoptuna/_transform.py175CODE
LOWoptuna/_transform.py246CODE
LOWoptuna/_transform.py269CODE
LOWoptuna/visualization/_rank.py117CODE
LOWoptuna/visualization/_rank.py308CODE
LOWoptuna/visualization/_parallel_coordinate.py124CODE
LOWoptuna/visualization/_optimization_history.py51CODE
LOWoptuna/visualization/_optimization_history.py139CODE
LOWoptuna/visualization/_slice.py183CODE
LOWoptuna/visualization/_contour.py109CODE
LOWoptuna/visualization/_contour.py260CODE
LOWoptuna/visualization/matplotlib/_utils.py37CODE
LOWoptuna/visualization/matplotlib/_contour.py81CODE
LOWoptuna/visualization/matplotlib/_contour.py326CODE
LOWoptuna/storages/_cached_storage.py89CODE
LOWoptuna/storages/_in_memory.py371CODE
LOWoptuna/storages/journal/_file.py148CODE
LOWoptuna/storages/journal/_file.py239CODE
LOWoptuna/storages/journal/_storage.py414CODE
LOWoptuna/storages/journal/_storage.py578CODE
LOWoptuna/storages/_grpc/client.py257CODE
LOWoptuna/storages/_rdb/storage.py675CODE
LOWoptuna/storages/_rdb/storage.py783CODE
LOWoptuna/storages/_rdb/storage.py863CODE
LOWoptuna/storages/_rdb/alembic/versions/v3.0.0.c.py68CODE
LOWoptuna/storages/_rdb/alembic/versions/v3.0.0.d.py78CODE
LOWoptuna/study/_dataframe.py22CODE
LOWoptuna/study/_optimize.py39CODE
LOWoptuna/study/_optimize.py186CODE
LOWoptuna/study/_tell.py80CODE
LOWoptuna/study/study.py1204CODE
LOWoptuna/study/study.py1607CODE
LOWoptuna/trial/_trial.py624CODE
LOWoptuna/importance/_base.py115CODE
LOWoptuna/importance/_fanova/_tree.py80CODE
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Cross-Language Confusion6 hits · 38 pts
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HIGHtutorial/20_recipes/004_cli.py56# --search-space '{"x": {"name": "FloatDistribution", "attributes": {"step": null, "low": -10.0, "high": 10.0, COMMENT
HIGHtests/test_distributions.py65 "f": '{"type": "float", "low": 1.0, "high": 2.0, "log": false, "step": null}',CODE
HIGHtests/test_distributions.py66 "fl": '{"type": "float", "low": 0.001, "high": 100, "log": true, "step": null}',CODE
HIGHtests/test_distributions.py16_choices_json = '[null, true, false, 0, 1, 0.0, 1.0, NaN, Infinity, -Infinity, "", "a"]'CODE
HIGHtests/test_distributions.py47 '"attributes": {"low": 1.0, "high": 2.0, "log": false, "step": null}}',CODE
HIGHtests/test_distributions.py49 '"attributes": {"low": 0.001, "high": 100.0, "log": true, "step": null}}',CODE
AI Structural Patterns25 hits · 24 pts
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LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py405CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py432CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py459CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py486CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py513CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py540CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py567CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py594CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py621CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py648CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py675CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py702CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py729CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py756CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py783CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py810CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py837CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py864CODE
LOWoptuna/storages/_grpc/auto_generated/api_pb2_grpc.py891CODE
LOWoptuna/trial/_frozen.py483CODE
LOWoptuna/_gp/batched_lbfgsb.py89CODE
LOWoptuna/samplers/_cmaes.py271CODE
LOWoptuna/samplers/_nsgaiii/_sampler.py83CODE
LOWoptuna/samplers/nsgaii/_sampler.py166CODE
LOWoptuna/samplers/_tpe/sampler.py357CODE
AI Slop Vocabulary6 hits · 16 pts
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MEDIUMtutorial/20_recipes/013_wilcoxon_pruner.py205# Some samplers, including the default ``TPESampler``, currently cannot utilize theCOMMENT
MEDIUMtutorial/20_recipes/008_specify_params.py103# Second scenario: Have Optuna utilize already evaluated hyperparametersCOMMENT
LOWoptuna/_gp/gp.py314 # Note that we cannot just use the constraint because of the numerical instabilityCOMMENT
LOWoptuna/_gp/acqf.py385 # Since all the objectives are equally important, we simply use the mean ofCOMMENT
LOWoptuna/_gp/acqf.py451 # Since all the objectives are equally important, we simply use the mean ofCOMMENT
MEDIUMoptuna/samplers/_brute_force.py110 # Essentially, each node represents a param value, and a path from the first node to the leafCOMMENT
Cross-File Repetition3 hits · 15 pts
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HIGHoptuna/visualization/_parallel_coordinate.py0plot the high-dimensional parameter relationships in a study with matplotlib. note that, if a parameter contains missingSTRING
HIGHoptuna/visualization/_contour.py0plot the high-dimensional parameter relationships in a study with matplotlib. note that, if a parameter contains missingSTRING
HIGHoptuna/visualization/matplotlib/_parallel_coordinate.py0plot the high-dimensional parameter relationships in a study with matplotlib. note that, if a parameter contains missingSTRING
Slop Phrases4 hits · 12 pts
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MEDIUMtutorial/10_key_features/002_configurations.py49# Also, you can use branches or loops depending on the parameter values.COMMENT
MEDIUMtutorial/10_key_features/004_distributed.py232# Then, you can use this MySQL database as a storage backend by setting theCOMMENT
MEDIUMtutorial/10_key_features/004_distributed.py281# In that case, you can use :class:`~optuna.storages.GrpcStorageProxy`COMMENT
MEDIUMoptuna/_hypervolume/wfg.py104 # which is guaranteed. As mentioned earlier, if all ``False`` in on_front is correct, theCOMMENT
Redundant / Tautological Comments8 hits · 12 pts
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LOWtests/test_cli.py149 # Check if study_name is stored in the storage.COMMENT
LOWtests/test_cli.py1016 # Check if study_name is stored in the storage.COMMENT
LOWtests/storages_tests/rdb_tests/test_storage.py334 # Check if Study.optimize can run on new storage.COMMENT
LOWtests/samplers_tests/test_base_gasampler.py109 assert len(mock_study.mock_calls) == 2 # Check if only the two calls above were madeCODE
LOWoptuna/testing/pytest_storages.py338 # Check if trial_number starts from 0.COMMENT
LOWoptuna/testing/pytest_storages.py441 # Set params to another trial.COMMENT
LOWoptuna/samplers/_partial_fixed.py101 # Check if a parameter value is contained in the range of this distribution.COMMENT
LOWoptuna/samplers/_tpe/sampler.py901 weights_below = np.where(is_feasible, 1.0, EPS) # Assign EPS to infeasible trials.CODE
Excessive Try-Catch Wrapping9 hits · 10 pts
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LOWtests/visualization_tests/test_utils.py52 except Exception:CODE
MEDIUMtests/visualization_tests/test_utils.py47def _is_plotly_available() -> bool:CODE
LOWoptuna/progress_bar.py28 except Exception:CODE
LOWoptuna/artifacts/_backoff.py75 except Exception as e:CODE
LOWoptuna/artifacts/_backoff.py90 except Exception as e:CODE
LOWoptuna/artifacts/_backoff.py104 except Exception as e:CODE
LOWoptuna/storages/journal/_storage.py597 except Exception:CODE
LOWoptuna/storages/_rdb/storage.py99 except Exception:CODE
LOWoptuna/study/_optimize.py225 except Exception:CODE
AI Response Leakage1 hit · 8 pts
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HIGHoptuna/pruners/_hyperband.py204 # In this implementation, we combine this formula and that of ASHA paperCOMMENT
Dead Code1 hit · 2 pts
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MEDIUMtests/study_tests/test_dataframe.py131CODE
Fake / Example Data1 hit · 0 pts
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LOWoptuna/testing/pytest_storages.py415 storage.get_trial_param(existent_trial_id, "dummy-key")CODE