Repository Analysis

pytorch/ignite

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

22.2 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of pytorch/ignite, a Python project with 4,769 GitHub stars. SynthScan v2.0 examined 91,736 lines of code across 436 source files, recording 1812 pattern matches distributed across 15 syntactic categories. The overall adjusted score of 22.2 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).

22.2
Adjusted Score
22.2
Raw Score
100%
Time Factor
2026-07-06
Last Push
4.8K
Stars
Python
Language
91.7K
Lines of Code
436
Files
1.8K
Pattern Hits
2026-07-14
Scan Date
0.13
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 57MEDIUM 55LOW 1700

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 1812 distinct pattern matches across 15 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 Identifiers1176 hits · 1196 pts
SeverityFileLineSnippetContext
LOWCONTRIBUTING.md130- naming of testing functions `def test_*`, e.g. `def test_precision_on_random_data()`CODE
LOWignite/metrics/top_k_categorical_accuracy.py48 def one_hot_to_binary_output_transform(output):STRING
LOWignite/metrics/ssim.py156 def _gaussian_or_uniform_kernel(CODE
LOWignite/metrics/recall.py200 def thresholded_output_transform(output):CODE
LOWignite/metrics/fbeta.py126 def thresholded_output_transform(output):CODE
LOWignite/metrics/precision_recall_curve.py11def precision_recall_curve_compute_fn(y_preds: torch.Tensor, y_targets: torch.Tensor) -> tuple[Any, Any, Any]:CODE
LOWignite/metrics/average_precision.py8def average_precision_compute_fn(y_preds: torch.Tensor, y_targets: torch.Tensor) -> float:CODE
LOWignite/metrics/average_precision.py41 def activated_output_transform(output):STRING
LOWignite/metrics/metric.py674 def _load_state_dict_per_rank(self, state_dict: Mapping) -> None:CODE
LOWignite/metrics/metric.py903def _is_list_of_tensors_or_numbers(x: Sequence[torch.Tensor | float]) -> bool:CODE
LOWignite/metrics/precision.py361 def thresholded_output_transform(output):CODE
LOWignite/metrics/mean_average_precision.py90 def _compute_average_precision(self, recall: torch.Tensor, precision: torch.Tensor) -> torch.Tensor:STRING
LOWignite/metrics/mean_average_precision.py244 def _check_binary_multilabel_cases(self, output: Sequence[torch.Tensor]) -> None:STRING
LOWignite/metrics/mean_average_precision.py320 def _compute_recall_and_precision(STRING
LOWignite/metrics/accuracy.py52 def _check_binary_multilabel_cases(self, output: Sequence[torch.Tensor]) -> None:CODE
LOWignite/metrics/accuracy.py254 def thresholded_output_transform(output):CODE
LOWignite/metrics/confusion_matrix.py85 def binary_one_hot_output_transform(output):STRING
LOWignite/metrics/matthews_corrcoef.py8def matthews_corrcoef_compute_fn(y_preds: torch.Tensor, y_targets: torch.Tensor) -> float:CODE
LOW…cs/vision/object_detection_average_precision_recall.py11def coco_tensor_list_to_dict_list(CODE
LOW…cs/vision/object_detection_average_precision_recall.py180 def _compute_recall_and_precision(STRING
LOW…cs/vision/object_detection_average_precision_recall.py221 def _compute_average_precision(self, recall: torch.Tensor, precision: torch.Tensor) -> torch.Tensor:STRING
LOWignite/metrics/nlp/bleu.py191 def _brevity_penalty_smoothing(STRING
LOW…metrics/regression/median_absolute_percentage_error.py9def median_absolute_percentage_error_compute_fn(y_pred: torch.Tensor, y: torch.Tensor) -> float:CODE
LOWignite/metrics/regression/median_absolute_error.py10def median_absolute_error_compute_fn(y_pred: torch.Tensor, y: torch.Tensor) -> float:CODE
LOW…e/metrics/regression/median_relative_absolute_error.py10def median_relative_absolute_error_compute_fn(y_pred: torch.Tensor, y: torch.Tensor) -> float:CODE
LOWignite/distributed/utils.py356def all_gather_tensors_with_shapes(CODE
LOWignite/distributed/comp_models/__init__.py16def setup_available_computation_models() -> tuple[CODE
LOWignite/distributed/comp_models/native.py185 def _compute_node_and_local_ranks(rank: int, hostnames: list[tuple[str, ...]]) -> tuple[int, int]:CODE
LOWignite/distributed/comp_models/native.py195 def _compute_local_rank_via_hostname(self) -> int:CODE
LOWignite/distributed/comp_models/native.py573 def _setup_ddp_vars_from_slurm_env(environ: dict[str, str]) -> dict[str, str | int]:CODE
LOWignite/contrib/engines/common.py51def setup_common_training_handlers(CODE
LOWignite/contrib/engines/common.py155def _setup_common_training_handlers(CODE
LOWignite/contrib/engines/common.py239def _setup_common_distrib_training_handlers(CODE
LOWignite/contrib/engines/common.py310def gen_save_best_models_by_val_score(CODE
LOWignite/contrib/engines/common.py372def save_best_model_by_val_score(CODE
LOWignite/contrib/engines/common.py417def add_early_stopping_by_val_score(CODE
LOWignite/contrib/engines/tbptt.py35def create_supervised_tbptt_trainer(CODE
LOWignite/engine/events.py152 def before_and_after_event_filter(before: int | None = None, after: int | None = None) -> Callable:CODE
LOWignite/engine/events.py165 def every_before_and_after_event_filter(CODE
LOWignite/engine/events.py344 def call_every_itr_before_after(engine):STRING
LOWignite/engine/__init__.py141def supervised_training_step_amp(CODE
LOWignite/engine/__init__.py237def supervised_training_step_apex(CODE
LOWignite/engine/__init__.py324def supervised_training_step_tpu(CODE
LOWignite/engine/__init__.py440def create_supervised_trainer(CODE
LOWignite/engine/__init__.py638def supervised_evaluation_step(CODE
LOWignite/engine/__init__.py696def supervised_evaluation_step_amp(CODE
LOWignite/engine/__init__.py759def create_supervised_evaluator(CODE
LOWignite/engine/engine.py829 def _check_and_set_termination_param(CODE
LOWignite/engine/engine.py846 def _check_and_set_max_epochs(self, max_epochs: int | None = None) -> None:CODE
LOWignite/engine/engine.py1179 def _maybe_terminate_or_interrupt(self) -> Generator:CODE
LOWignite/engine/engine.py1191 def _run_once_on_dataset_as_gen(self) -> Generator[State, None, float]:CODE
LOWignite/engine/engine.py1378 def _run_once_on_dataset_legacy(self) -> float:CODE
LOWignite/handlers/param_scheduler.py1062def create_lr_scheduler_with_warmup(CODE
LOWignite/handlers/mlflow_logger.py175 def _create_opt_params_handler(self, *args: Any, **kwargs: Any) -> "OptimizerParamsHandler":CODE
LOWignite/handlers/polyaxon_logger.py147 def _create_opt_params_handler(self, *args: Any, **kwargs: Any) -> "OptimizerParamsHandler":CODE
LOWignite/handlers/tensorboard_logger.py231 def _create_opt_params_handler(self, *args: Any, **kwargs: Any) -> "OptimizerParamsHandler":CODE
LOWignite/handlers/wandb_logger.py169 def _create_opt_params_handler(self, *args: Any, **kwargs: Any) -> "OptimizerParamsHandler":CODE
LOWignite/handlers/visdom_logger.py220 def _create_opt_params_handler(self, *args: Any, **kwargs: Any) -> "OptimizerParamsHandler":CODE
LOWignite/handlers/base_logger.py112 def _setup_output_metrics_state_attrs(CODE
LOWignite/handlers/base_logger.py285 def attach_opt_params_handler(CODE
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Unused Imports275 hits · 232 pts
SeverityFileLineSnippetContext
LOWignite/__init__.py1CODE
LOWignite/__init__.py2CODE
LOWignite/__init__.py3CODE
LOWignite/__init__.py4CODE
LOWignite/__init__.py5CODE
LOWignite/__init__.py6CODE
LOWignite/__init__.py7CODE
LOWignite/utils.py1CODE
LOWignite/_utils.py2CODE
LOWignite/_utils.py2CODE
LOWignite/_utils.py2CODE
LOWignite/_utils.py2CODE
LOWignite/metrics/__init__.py1CODE
LOWignite/metrics/__init__.py2CODE
LOWignite/metrics/__init__.py3CODE
LOWignite/metrics/__init__.py5CODE
LOWignite/metrics/__init__.py5CODE
LOWignite/metrics/__init__.py5CODE
LOWignite/metrics/__init__.py6CODE
LOWignite/metrics/__init__.py7CODE
LOWignite/metrics/__init__.py8CODE
LOWignite/metrics/__init__.py9CODE
LOWignite/metrics/__init__.py10CODE
LOWignite/metrics/__init__.py10CODE
LOWignite/metrics/__init__.py10CODE
LOWignite/metrics/__init__.py10CODE
LOWignite/metrics/__init__.py10CODE
LOWignite/metrics/__init__.py11CODE
LOWignite/metrics/__init__.py12CODE
LOWignite/metrics/__init__.py13CODE
LOWignite/metrics/__init__.py14CODE
LOWignite/metrics/__init__.py15CODE
LOWignite/metrics/__init__.py16CODE
LOWignite/metrics/__init__.py17CODE
LOWignite/metrics/__init__.py18CODE
LOWignite/metrics/__init__.py19CODE
LOWignite/metrics/__init__.py20CODE
LOWignite/metrics/__init__.py21CODE
LOWignite/metrics/__init__.py22CODE
LOWignite/metrics/__init__.py23CODE
LOWignite/metrics/__init__.py24CODE
LOWignite/metrics/__init__.py25CODE
LOWignite/metrics/__init__.py26CODE
LOWignite/metrics/__init__.py27CODE
LOWignite/metrics/__init__.py28CODE
LOWignite/metrics/__init__.py29CODE
LOWignite/metrics/__init__.py29CODE
LOWignite/metrics/__init__.py29CODE
LOWignite/metrics/__init__.py29CODE
LOWignite/metrics/__init__.py29CODE
LOWignite/metrics/__init__.py30CODE
LOWignite/metrics/__init__.py31CODE
LOWignite/metrics/__init__.py32CODE
LOWignite/metrics/__init__.py33CODE
LOWignite/metrics/__init__.py34CODE
LOWignite/metrics/__init__.py35CODE
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LOWignite/metrics/__init__.py36CODE
LOWignite/metrics/__init__.py37CODE
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Docstring Block Structure44 hits · 220 pts
SeverityFileLineSnippetContext
HIGHignite/utils.py249Setups logger: name, level, format etc. Args: name: new name for the logger. If None, the standard logger iSTRING
HIGHignite/metrics/fbeta.py21Calculates F-beta score. .. math:: F_\beta = \left( 1 + \beta^2 \right) * \frac{ \text{precision} * \text{rSTRING
HIGHignite/metrics/metric.py224 Base class for all Metrics. Args: output_transform: a callable that is used to transform the STRING
HIGHignite/metrics/loss.py12 Calculates the average loss according to the passed loss_fn. Args: loss_fn: a callable taking a predicSTRING
HIGHignite/metrics/confusion_matrix.py206Calculates Intersection over Union using :class:`~ignite.metrics.confusion_matrix.ConfusionMatrix` metric. .. math:STRING
HIGHignite/metrics/confusion_matrix.py275Calculates mean Intersection over Union using :class:`~ignite.metrics.confusion_matrix.ConfusionMatrix` metric. ArgSTRING
HIGHignite/metrics/confusion_matrix.py434Calculates the Jaccard Index using :class:`~ignite.metrics.confusion_matrix.ConfusionMatrix` metric. Implementation STRING
HIGHignite/distributed/utils.py359Helper method to gather tensors of possibly different shapes but with the same number of dimensions across processesSTRING
HIGHignite/distributed/utils.py438Helper method to perform broadcast operation. Args: tensor: tensor, number, str or pathlib.Path to broadcasSTRING
HIGHignite/distributed/utils.py572Initializes distributed configuration according to provided ``backend`` Args: backend: backend: `nccl`, `glSTRING
HIGHignite/distributed/auto.py24Helper method to create a dataloader adapted for non-distributed and distributed configurations (supporting all avaiSTRING
HIGHignite/distributed/auto.py145Helper method to adapt provided model for non-distributed and distributed configurations (supporting all available bSTRING
HIGHignite/distributed/auto.py239Helper method to adapt optimizer for non-distributed and distributed configurations (supporting all available backenSTRING
HIGHignite/engine/__init__.py70Factory function for supervised training. Args: model: the model to train. optimizer: the optimizerSTRING
HIGHignite/engine/__init__.py154Factory function for supervised training using ``torch.amp``. Args: model: the model to train. optiSTRING
HIGHignite/engine/__init__.py249Factory function for supervised training using apex. Args: model: the model to train. optimizer: thSTRING
HIGHignite/engine/__init__.py336Factory function for supervised training using ``torch_xla``. Args: model: the model to train. optiSTRING
HIGHignite/engine/__init__.py455Factory function for creating a trainer for supervised models. Args: model: the model to train. optSTRING
HIGHignite/engine/engine.py21Runs a given ``process_function`` over each batch of a dataset, emitting events as it goes. Args: process_fSTRING
HIGHignite/engine/engine.py280Add an event handler to be executed when the specified event is fired. Args: event_name: An event oSTRING
HIGHignite/handlers/ema_handler.py29Exponential moving average (EMA) handler can be used to compute a smoothed version of model. The EMA model is updateSTRING
HIGHignite/handlers/param_scheduler.py117Method to plot simulated scheduled values during `num_events` events. This class requires `matplotlib package <STRING
HIGHignite/handlers/param_scheduler.py248Method to simulate scheduled values during `num_events` events. Args: num_events: number of events STRING
HIGHignite/handlers/param_scheduler.py1070 Helper method to create a learning rate scheduler with a linear warm-up. Args: lr_scheduler: learning STRING
HIGHignite/handlers/mlflow_logger.py18 `MLflow <https://mlflow.org>`_ tracking client handler to log parameters and metrics during the training and vaSTRING
HIGHignite/handlers/mlflow_logger.py180Helper handler to log engine's output and/or metrics. Args: tag: common title for all produced plots. For eSTRING
HIGHignite/handlers/polyaxon_logger.py16 `Polyaxon tracking client <https://polyaxon.com/>`_ handler to log parameters and metrics during the training aSTRING
HIGHignite/handlers/polyaxon_logger.py152Helper handler to log engine's output and/or metrics. Args: tag: common title for all produced plots. For eSTRING
HIGHignite/handlers/checkpoint.py86Checkpoint handler can be used to periodically save and load objects which have attribute ``state_dict/load_state_diSTRING
HIGHignite/handlers/tensorboard_logger.py236Helper handler to log engine's output, engine's state attributes and/or metrics Args: tag: common title forSTRING
HIGHignite/handlers/visdom_logger.py269Helper handler to log engine's output and/or metrics Args: tag: common title for all produced plots. For exSTRING
HIGHignite/handlers/lr_finder.py395Attaches lr_finder to a given trainer. It also resets model and optimizer at the end of the run. Args: STRING
HIGHignite/handlers/stores.py8EpochOutputStore handler to save output prediction and target history after every epoch, could be useful for e.g., vSTRING
HIGHignite/handlers/state_param_scheduler.py78Method to simulate scheduled engine state parameter values during `num_events` events. Args: num_evSTRING
HIGHignite/handlers/clearml_logger.py230Helper handler to log engine's output and/or metrics Args: tag: common title for all produced plots. For exSTRING
HIGHignite/handlers/timing.py10Timer object can be used to measure (average) time between events. Args: average: if True, then when ``.valSTRING
HIGHignite/handlers/neptune_logger.py216Helper handler to log engine's output and/or metrics. Args: tag: common title for all produced plots. For eSTRING
HIGHignite/handlers/logger_utils.py101Method to setup TensorBoard logging on trainer and a list of evaluators. Logged metrics are: - Training metricsSTRING
HIGHignite/handlers/logger_utils.py165Method to setup Visdom logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, e.gSTRING
HIGHignite/handlers/logger_utils.py232Method to setup MLflow logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, e.gSTRING
HIGHignite/handlers/logger_utils.py294Method to setup Neptune logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, e.STRING
HIGHignite/handlers/logger_utils.py356Method to setup WandB logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, e.g.STRING
HIGHignite/handlers/logger_utils.py418Method to setup Polyaxon logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, eSTRING
HIGHignite/handlers/logger_utils.py480Method to setup ClearML logging on trainer and a list of evaluators. Logged metrics are: - Training metrics, e.STRING
Modern Structural Boilerplate122 hits · 122 pts
SeverityFileLineSnippetContext
LOWignite/utils.py17__all__ = [CODE
LOWignite/exceptions.py1__all__ = ["NotComputableError"]CODE
LOWignite/_utils.py4__all__ = ["apply_to_tensor", "apply_to_type", "convert_tensor", "to_onehot"]CODE
LOWignite/metrics/mean_squared_error.py8__all__ = ["MeanSquaredError"]CODE
LOWignite/metrics/multilabel_confusion_matrix.py8__all__ = ["MultiLabelConfusionMatrix"]CODE
LOWignite/metrics/top_k_categorical_accuracy.py8__all__ = ["TopKCategoricalAccuracy"]CODE
LOWignite/metrics/mutual_information.py7__all__ = ["MutualInformation"]CODE
LOWignite/metrics/mean_absolute_error.py8__all__ = ["MeanAbsoluteError"]CODE
LOWignite/metrics/ssim.py10__all__ = ["SSIM"]CODE
LOWignite/metrics/recall.py8__all__ = ["Recall"]CODE
LOWignite/metrics/fbeta.py10__all__ = ["Fbeta"]CODE
LOWignite/metrics/root_mean_squared_error.py7__all__ = ["RootMeanSquaredError"]CODE
LOWignite/metrics/__init__.py55__all__ = [CODE
LOWignite/metrics/accumulation.py9__all__ = ["VariableAccumulation", "GeometricAverage", "Average"]CODE
LOWignite/metrics/hsic.py9__all__ = ["HSIC"]CODE
LOWignite/metrics/metric.py19__all__ = [CODE
LOWignite/metrics/precision.py13__all__ = ["Precision"]CODE
LOWignite/metrics/epoch_metric.py11__all__ = ["EpochMetric"]CODE
LOWignite/metrics/loss.py8__all__ = ["Loss"]CODE
LOWignite/metrics/js_divergence.py9__all__ = ["JSDivergence"]CODE
LOWignite/metrics/cosine_similarity.py8__all__ = ["CosineSimilarity"]CODE
LOWignite/metrics/psnr.py8__all__ = ["PSNR"]CODE
LOWignite/metrics/running_average.py11__all__ = ["RunningAverage"]CODE
LOWignite/metrics/metrics_lambda.py10__all__ = ["MetricsLambda"]CODE
LOWignite/metrics/kl_divergence.py10__all__ = ["KLDivergence"]CODE
LOWignite/metrics/accuracy.py8__all__ = ["Accuracy"]CODE
LOWignite/metrics/mean_pairwise_distance.py9__all__ = ["MeanPairwiseDistance"]CODE
LOWignite/metrics/confusion_matrix.py10__all__ = ["ConfusionMatrix", "mIoU", "IoU", "DiceCoefficient", "cmAccuracy", "cmPrecision", "cmRecall", "JaccardIndex"]CODE
LOWignite/metrics/entropy.py9__all__ = ["Entropy"]CODE
LOWignite/metrics/maximum_mean_discrepancy.py8__all__ = ["MaximumMeanDiscrepancy"]CODE
LOWignite/metrics/classification_report.py12__all__ = ["ClassificationReport"]CODE
LOWignite/metrics/gan/__init__.py4__all__ = [CODE
LOWignite/metrics/gan/fid.py10__all__ = [CODE
LOWignite/metrics/gan/inception_score.py11__all__ = ["InceptionScore"]CODE
LOWignite/metrics/clustering/silhouette_score.py9__all__ = ["SilhouetteScore"]CODE
LOWignite/metrics/clustering/davies_bouldin_score.py9__all__ = ["DaviesBouldinScore"]CODE
LOWignite/metrics/clustering/calinski_harabasz_score.py9__all__ = ["CalinskiHarabaszScore"]CODE
LOWignite/metrics/vision/__init__.py3__all__ = ["ObjectDetectionAvgPrecisionRecall"]CODE
LOWignite/metrics/fairness/accuracy_difference.py6__all__ = ["SubgroupAccuracyDifference"]CODE
LOWignite/metrics/fairness/demographic_parity.py9__all__ = ["DemographicParityDifference", "SelectionRate"]CODE
LOWignite/metrics/fairness/base.py10__all__ = ["SubgroupMetric", "SubgroupDifference"]CODE
LOWignite/metrics/nlp/bleu.py12__all__ = ["Bleu"]CODE
LOWignite/metrics/nlp/perplexity.py9__all__ = ["Perplexity"]CODE
LOWignite/metrics/nlp/rouge.py13__all__ = ["Rouge", "RougeN", "RougeL"]CODE
LOWignite/metrics/nlp/__init__.py6__all__ = [CODE
LOWignite/metrics/nlp/utils.py5__all__ = ["ngrams", "lcs", "modified_precision"]CODE
LOWignite/metrics/nlp/character_error_rate.py9__all__ = ["CharacterErrorRate"]CODE
LOWignite/metrics/rec_sys/ndcg.py8__all__ = ["NDCG"]CODE
LOWignite/metrics/rec_sys/__init__.py4__all__ = ["HitRate", "NDCG"]CODE
LOWignite/metrics/rec_sys/hitrate.py8__all__ = ["HitRate"]CODE
LOWignite/distributed/utils.py22__all__ = [CODE
LOWignite/distributed/utils.py531def set_local_rank(index: int) -> None:CODE
LOWignite/distributed/utils.py557def _set_model(model: Any, temporary: bool = False) -> None:CODE
LOWignite/distributed/launcher.py9__all__ = [CODE
LOWignite/distributed/auto.py20__all__ = ["auto_dataloader", "auto_model", "auto_optim", "DistributedProxySampler"]CODE
LOWignite/distributed/comp_models/native.py253 def _setup_env_in_slurm(self) -> None:CODE
LOWignite/distributed/comp_models/base.py29 def _setup_attrs(self) -> None:CODE
LOWignite/contrib/metrics/gpu_info.py18__all__ = [CODE
LOWignite/contrib/metrics/roc_auc.py18__all__ = ["RocCurve", "ROC_AUC"]CODE
LOWignite/contrib/metrics/precision_recall_curve.py18__all__ = [CODE
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Self-Referential Comments46 hits · 64 pts
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MEDIUMignite/handlers/mlflow_logger.py36 # Create a loggerSTRING
MEDIUMignite/handlers/mlflow_logger.py202 # Create a loggerSTRING
MEDIUMignite/handlers/mlflow_logger.py334 # Create a loggerSTRING
MEDIUMignite/handlers/polyaxon_logger.py41 # Create a loggerSTRING
MEDIUMignite/handlers/polyaxon_logger.py174 # Create a loggerSTRING
MEDIUMignite/handlers/polyaxon_logger.py292 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py59 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py258 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py376 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py433 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py512 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py593 # Create a loggerSTRING
MEDIUMignite/handlers/tensorboard_logger.py674 # Create a loggerSTRING
MEDIUMignite/handlers/wandb_logger.py37 # Create a logger. All parameters are optional. See documentationSTRING
MEDIUMignite/handlers/wandb_logger.py196 # Create a logger. All parameters are optional. See documentationSTRING
MEDIUMignite/handlers/wandb_logger.py238 # Create a logger. All parameters are optional. See documentationSTRING
MEDIUMignite/handlers/wandb_logger.py332 # Create a logger. All parameters are optional. See documentationSTRING
MEDIUMignite/handlers/visdom_logger.py71 # Create a loggerSTRING
MEDIUMignite/handlers/visdom_logger.py292 # Create a loggerSTRING
MEDIUMignite/handlers/visdom_logger.py413 # Create a loggerSTRING
MEDIUMignite/handlers/visdom_logger.py467 # Create a loggerSTRING
MEDIUMignite/handlers/visdom_logger.py515 # Create a loggerSTRING
MEDIUMignite/handlers/time_profilers.py24 # Create an object of the profiler and attach an engine to itSTRING
MEDIUMignite/handlers/time_profilers.py478 # Create an object of the profiler and attach an engine to itCOMMENT
MEDIUMignite/handlers/clearml_logger.py61 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py252 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py290 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py386 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py448 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py538 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py633 # Create a loggerSTRING
MEDIUMignite/handlers/clearml_logger.py727 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py59 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py238 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py371 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py436 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py539 # Create a loggerSTRING
MEDIUMignite/handlers/neptune_logger.py637 # Create a loggerSTRING
MEDIUMtests/ignite/metrics/test_confusion_matrix.py157 # Create a batch of two images:COMMENT
MEDIUMtests/ignite/metrics/test_confusion_matrix.py162 # Create a batch of 2 logits tensorsCOMMENT
MEDIUMtests/ignite/metrics/test_confusion_matrix.py488 # Create a batch of two images:COMMENT
MEDIUMtests/ignite/metrics/test_confusion_matrix.py494 # Create a batch of 2 logits tensorsCOMMENT
MEDIUM…sts/ignite/metrics/test_multilabel_confusion_matrix.py114 # Create a batch of two images:COMMENT
MEDIUM…sts/ignite/metrics/test_multilabel_confusion_matrix.py163 # Create a batch of two images:COMMENT
MEDIUMtests/ignite/handlers/test_clearml_logger.py777 # Create a mock clearml.Logger() objectCOMMENT
MEDIUMtests/ignite/handlers/test_tensorboard_logger.py36 # Create a mock SummaryWriter objectCOMMENT
Cross-File Repetition11 hits · 55 pts
SeverityFileLineSnippetContext
HIGHignite/metrics/mean_squared_error.py0calculates the `root mean squared error <https://en.wikipedia.org/wiki/root-mean-square_deviation>`_. .. math:: \text{rmSTRING
HIGHignite/metrics/mean_absolute_error.py0calculates the `root mean squared error <https://en.wikipedia.org/wiki/root-mean-square_deviation>`_. .. math:: \text{rmSTRING
HIGHignite/metrics/root_mean_squared_error.py0calculates the `root mean squared error <https://en.wikipedia.org/wiki/root-mean-square_deviation>`_. .. math:: \text{rmSTRING
HIGHignite/distributed/comp_models/horovod.py0this is a private method. please, use `create_from_backend` or `create_from_context`STRING
HIGHignite/distributed/comp_models/native.py0this is a private method. please, use `create_from_backend` or `create_from_context`STRING
HIGHignite/distributed/comp_models/xla.py0this is a private method. please, use `create_from_backend` or `create_from_context`STRING
HIGHignite/handlers/mlflow_logger.py0helper handler to log engine's output and/or metrics args: tag: common title for all produced plots. for example, "trainSTRING
HIGHignite/handlers/polyaxon_logger.py0helper handler to log engine's output and/or metrics args: tag: common title for all produced plots. for example, "trainSTRING
HIGHignite/handlers/tensorboard_logger.py0helper handler to log engine's output and/or metrics args: tag: common title for all produced plots. for example, "trainSTRING
HIGHignite/handlers/visdom_logger.py0helper handler to log engine's output and/or metrics args: tag: common title for all produced plots. for example, "trainSTRING
HIGHignite/handlers/clearml_logger.py0helper handler to log engine's output and/or metrics args: tag: common title for all produced plots. for example, "trainSTRING
Deep Nesting57 hits · 54 pts
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LOWignite/utils.py98CODE
LOWignite/utils.py135CODE
LOWignite/metrics/metric.py825CODE
LOWignite/metrics/metric.py489CODE
LOWignite/metrics/metric.py674CODE
LOWignite/metrics/metric.py838CODE
LOWignite/metrics/metric.py677CODE
LOWignite/metrics/metric.py840CODE
LOWignite/metrics/metrics_lambda.py148CODE
LOWignite/metrics/metrics_lambda.py183CODE
LOW…cs/vision/object_detection_average_precision_recall.py136CODE
LOW…cs/vision/object_detection_average_precision_recall.py255CODE
LOWignite/metrics/fairness/demographic_parity.py65CODE
LOWignite/metrics/nlp/utils.py24CODE
LOWignite/distributed/auto.py23CODE
LOWignite/distributed/auto.py144CODE
LOWignite/distributed/comp_models/native.py573CODE
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LOWignite/contrib/engines/common.py155CODE
LOWignite/engine/deterministic.py202CODE
LOWignite/engine/__init__.py409CODE
LOWignite/engine/engine.py724CODE
LOWignite/engine/engine.py890CODE
LOWignite/engine/engine.py1104CODE
LOWignite/engine/engine.py1191CODE
LOWignite/engine/engine.py1302CODE
LOWignite/engine/engine.py1378CODE
LOWignite/handlers/param_scheduler.py1062CODE
LOWignite/handlers/checkpoint.py528CODE
LOWignite/handlers/lr_finder.py383CODE
LOWignite/handlers/base_logger.py173CODE
LOWignite/handlers/base_logger.py112CODE
LOWtests/ignite/metrics/test_classification_report.py144CODE
LOWtests/ignite/metrics/test_classification_report.py178CODE
LOWtests/ignite/metrics/test_psnr.py32CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py129CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py203CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py338CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py422CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py513CODE
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LOWtests/ignite/metrics/nlp/_pyrouge.py224CODE
LOWtests/ignite/metrics/nlp/_pyrouge.py249CODE
LOWtests/ignite/metrics/nlp/test_bleu.py47CODE
LOWtests/ignite/distributed/utils/__init__.py123CODE
LOWtests/ignite/distributed/utils/__init__.py227CODE
LOWtests/ignite/distributed/utils/__init__.py412CODE
LOWtests/ignite/engine/test_custom_events.py149CODE
LOWtests/ignite/engine/test_create_supervised.py184CODE
LOWtests/ignite/engine/test_create_supervised.py328CODE
LOWtests/ignite/handlers/test_clearml_logger.py851CODE
LOWtests/ignite/handlers/test_checkpoint.py1659CODE
LOWdocs/source/conf.py280CODE
LOWexamples/gan/dcgan.py146CODE
LOWexamples/cifar10_qat/utils.py192CODE
AI Structural Patterns34 hits · 31 pts
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LOWignite/utils.py239CODE
LOWignite/metrics/ssim.py78CODE
LOWignite/metrics/ssim.py179CODE
LOW…cs/vision/object_detection_average_precision_recall.py50CODE
LOW…s/regression/geometric_mean_relative_absolute_error.py108CODE
LOWignite/distributed/comp_models/native.py359CODE
LOWignite/distributed/comp_models/base.py167CODE
LOWignite/contrib/engines/common.py51CODE
LOWignite/contrib/engines/common.py155CODE
LOWignite/contrib/engines/common.py239CODE
LOWignite/engine/deterministic.py119CODE
LOWignite/engine/__init__.py141CODE
LOWignite/engine/__init__.py440CODE
LOWignite/engine/__init__.py759CODE
LOWignite/handlers/checkpoint.py337CODE
LOWignite/handlers/checkpoint.py1012CODE
LOWignite/handlers/time_profilers.py415CODE
LOWtests/ignite/conftest.py295CODE
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LOWtests/ignite/engine/test_engine.py748CODE
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LOWexamples/fast_neural_style/transformer_net.py54CODE
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LOWexamples/fast_neural_style/vgg.py39CODE
LOWexamples/transformers/model.py22CODE
LOWexamples/transformers/main.py129CODE
LOWexamples/siamese_network/siamese_network.py66CODE
LOWexamples/cifar10/main.py133CODE
Excessive Try-Catch Wrapping15 hits · 16 pts
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LOWignite/metrics/epoch_metric.py142 except Exception as e:CODE
LOWignite/engine/engine.py1289 except Exception as e:CODE
LOWignite/engine/engine.py1475 except Exception as e:CODE
LOWignite/handlers/polyaxon_logger.py138 except Exception:CODE
MEDIUMignite/handlers/polyaxon_logger.py135def close(self) -> None:CODE
LOWtests/ignite/handlers/test_neptune_logger.py546 except Exception:CODE
LOWtests/ignite/handlers/test_checkpoint.py645 except Exception:CODE
LOWexamples/mnist/mnist_save_resume_engine.py268 except Exception as e:CODE
LOWexamples/cifar10_qat/main.py113 except Exception as e:CODE
LOWexamples/references/classification/imagenet/main.py322 except Exception as e: # noqaCODE
LOWexamples/references/classification/imagenet/main.py421 except Exception as e: # noqaCODE
LOWexamples/references/segmentation/pascal_voc2012/main.py359 except Exception as e: # noqaCODE
LOWexamples/references/segmentation/pascal_voc2012/main.py465 except Exception as e: # noqaCODE
LOWexamples/transformers/main.py121 except Exception as e:CODE
LOWexamples/cifar10/main.py125 except Exception as e:CODE
Over-Commented Block13 hits · 12 pts
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LOWignite/handlers/mlflow_logger.py121COMMENT
LOWignite/handlers/tensorboard_logger.py181COMMENT
LOWtests/ignite/metrics/test_metric.py1301# class _TestMetric(Metric):COMMENT
LOW…sts/ignite/metrics/test_multilabel_confusion_matrix.py361 predictions_reshaped = predictions.permute(0, 1, 3, 4, 5, 2).reshape(-1, num_classes)COMMENT
LOW…sts/ignite/metrics/test_multilabel_confusion_matrix.py381# _test_distrib_multiclass_images(device)COMMENT
LOW…sts/ignite/metrics/test_multilabel_confusion_matrix.py401#COMMENT
LOW…sts/ignite/metrics/test_multilabel_confusion_matrix.py421# device = idist.device()COMMENT
LOWdocs/source/conf.py1# -*- coding: utf-8 -*-COMMENT
LOWdocs/source/conf.py81# katex optionsCOMMENT
LOWdocs/source/conf.py161# -- Options for HTMLHelp output ---------------------------------------------COMMENT
LOW.github/workflows/triage.yml21 repo-token: "${{ secrets.GITHUB_TOKEN }}"COMMENT
LOW.github/workflows/unit-tests.yml121 - name: Run MNIST ExamplesCOMMENT
LOW.github/workflows/pytorch-version-tests.yml81 # filename: .github/failed_schedule_issue_template.mdCOMMENT
Cross-Language Confusion2 hits · 10 pts
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HIGHignite/metrics/clustering/davies_bouldin_score.py39 (i.e., the index is undefined), ``float('nan')`` is returned.CODE
HIGHignite/metrics/clustering/calinski_harabasz_score.py39 (i.e., the index is undefined), ``float('nan')`` is returned.CODE
Redundant / Tautological Comments5 hits · 8 pts
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LOWignite/engine/engine.py975 # Check if we need to create new state or resumeCOMMENT
LOWignite/handlers/lr_finder.py191 # Check if the loss has diverged; if it has, stop the trainerCOMMENT
LOWignite/handlers/lr_finder.py303 # Check if optimizer has multiple param_groupsCOMMENT
LOWtests/ignite/handlers/test_tensorboard_logger.py658 # Check if event files are presentCOMMENT
LOWtests/ignite/handlers/test_tensorboard_logger.py685 # Check if event files are presentCOMMENT
Slop Phrases6 hits · 6 pts
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MEDIUMignite/handlers/neptune_logger.py239 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
MEDIUMignite/handlers/neptune_logger.py280 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
MEDIUMignite/handlers/neptune_logger.py372 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
MEDIUMignite/handlers/neptune_logger.py437 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
MEDIUMignite/handlers/neptune_logger.py540 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
MEDIUMignite/handlers/neptune_logger.py638 # We are using the api_token for the anonymous user neptuner but you can use your own.STRING
Decorative Section Separators2 hits · 6 pts
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MEDIUMexamples/gan/dcgan.py249 # -----------------------------------------------------------COMMENT
MEDIUMexamples/gan/dcgan.py275 # -----------------------------------------------------------COMMENT
Fake / Example Data4 hits · 4 pts
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LOWtests/ignite/handlers/test_time_profilers.py149 dummy_data = range(true_num_iters)CODE
LOWtests/ignite/handlers/test_time_profilers.py154 dummy_trainer.run(dummy_data_loader(dummy_data), max_epochs=true_max_epochs, epoch_length=true_num_iters)CODE
LOWtests/ignite/handlers/test_time_profilers.py176 dummy_data = range(true_num_iters)CODE
LOWtests/ignite/handlers/test_time_profilers.py181 dummy_trainer.run(dummy_data_loader(dummy_data), max_epochs=true_max_epochs, epoch_length=true_num_iters)CODE