google-research/google-research

15.8

Adjusted Score

15.8

Raw Score

100%

Time Factor

2026-07-11

Last Push

38.4K

Stars

Jupyter Notebook

Language

3.9M

Lines of Code

15.0K

Files

41.8K

Pattern Hits

2026-07-14

Scan Date

0.26

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

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

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 80HIGH 3861MEDIUM 1663LOW 36168

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 41772 distinct pattern matches across 27 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.

Cross-File Repetition2626 hits · 13130 pts

Severity	File	Line	Snippet	Context
HIGH	fm4tlp/models/jodie.py	0	generates predictions from input edges. args: source_nodes: source nodes. target_nodes_pos: target nodes for positive ed	STRING
HIGH	fm4tlp/models/model_template.py	0	generates predictions from input edges. args: source_nodes: source nodes. target_nodes_pos: target nodes for positive ed	STRING
HIGH	fm4tlp/models/dyrep.py	0	generates predictions from input edges. args: source_nodes: source nodes. target_nodes_pos: target nodes for positive ed	STRING
HIGH	fm4tlp/models/tgn.py	0	generates predictions from input edges. args: source_nodes: source nodes. target_nodes_pos: target nodes for positive ed	STRING
HIGH	fm4tlp/models/edgebank.py	0	generates predictions from input edges. args: source_nodes: source nodes. target_nodes_pos: target nodes for positive ed	STRING
HIGH	fm4tlp/models/jodie.py	0	predicts memory embeddings from structural embeddings.	STRING
HIGH	fm4tlp/models/dyrep.py	0	predicts memory embeddings from structural embeddings.	STRING
HIGH	fm4tlp/models/tgn.py	0	predicts memory embeddings from structural embeddings.	STRING
HIGH	nigt_optimizer/nigt_optimizer.py	0	whether to do layer-wise learning rate adaptation for `param_name`.	STRING
HIGH	etcmodel/models/lamb_optimizer.py	0	whether to do layer-wise learning rate adaptation for `param_name`.	STRING
HIGH	mobilebert/lamb_optimizer.py	0	whether to do layer-wise learning rate adaptation for `param_name`.	STRING
HIGH	readtwice/models/lamb_optimizer.py	0	whether to do layer-wise learning rate adaptation for `param_name`.	STRING
HIGH	supcon/utils.py	0	whether to do layer-wise learning rate adaptation for `param_name`.	STRING
HIGH	rce/rce_agent.py	0	returns an op to initialize the agent. copies weights from the q networks to the target q network.	STRING
HIGH	c_learning/c_learning_agent.py	0	returns an op to initialize the agent. copies weights from the q networks to the target q network.	STRING
HIGH	reset_free_learning/agents/sac_agent.py	0	returns an op to initialize the agent. copies weights from the q networks to the target q network.	STRING
HIGH	rce/rce_agent.py	0	returns a train op to update the agent's networks. this method trains with the provided batched experience. args: experi	STRING
HIGH	c_learning/c_learning_agent.py	0	returns a train op to update the agent's networks. this method trains with the provided batched experience. args: experi	STRING
HIGH	reset_free_learning/agents/sac_agent.py	0	returns a train op to update the agent's networks. this method trains with the provided batched experience. args: experi	STRING
HIGH	rce/rce_agent.py	0	performs a soft update of the target network parameters. for each weight w_s in the original network, and its correspond	STRING
HIGH	c_learning/c_learning_agent.py	0	performs a soft update of the target network parameters. for each weight w_s in the original network, and its correspond	STRING
HIGH	reset_free_learning/agents/sac_agent.py	0	performs a soft update of the target network parameters. for each weight w_s in the original network, and its correspond	STRING
HIGH	reset_free_learning/agents/td3_agent.py	0	performs a soft update of the target network parameters. for each weight w_s in the original network, and its correspond	STRING
HIGH	rce/rce_agent.py	0	get actions and corresponding log probabilities from policy.	STRING
HIGH	c_learning/c_learning_agent.py	0	get actions and corresponding log probabilities from policy.	STRING
HIGH	reset_free_learning/agents/sac_agent.py	0	get actions and corresponding log probabilities from policy.	STRING
HIGH	schema_guided_dst/baseline/train_and_predict.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	schema_guided_dst/baseline/extract_schema_embedding.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	cubert/run_classifier.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	cbertscore/bert_lib.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	smith/input_fns.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	bam/data/preprocessing.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	drfact/input_fns.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	etcmodel/models/hotpotqa/run_finetuning_lib.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	etcmodel/models/openkp/run_finetuning_lib.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	etcmodel/models/nq/run_nq_lib.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	etcmodel/models/wikihop/run_wikihop_lib.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	mobilebert/run_squad.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	mobilebert/run_pretraining.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	mobilebert/run_classifier.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	goemotions/bert_classifier.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	goemotions/learn_emotion_relations.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	readtwice/models/run_pretraining_demo.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	readtwice/models/hotpot_qa/run_finetuning.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	readtwice/models/trivia_qa/run_finetuning.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	readtwice/models/narrative_qa/run_finetuning.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	docent/bert/run_pretraining.py	0	creates an `input_fn` closure to be passed to tpuestimator.	STRING
HIGH	schema_guided_dst/baseline/data_utils.py	0	fake example so the num input examples is a multiple of the batch size. when running eval/predict on the tpu, we need to	STRING
HIGH	cubert/run_classifier.py	0	fake example so the num input examples is a multiple of the batch size. when running eval/predict on the tpu, we need to	STRING
HIGH	etcmodel/models/wikihop/data_utils.py	0	fake example so the num input examples is a multiple of the batch size. when running eval/predict on the tpu, we need to	STRING
HIGH	mobilebert/run_classifier.py	0	fake example so the num input examples is a multiple of the batch size. when running eval/predict on the tpu, we need to	STRING
HIGH	bam/data/preprocessing.py	0	fake example so the num input examples is a multiple of the batch size. when running eval/predict on the tpu, we need to	STRING
HIGH	schema_guided_dst/baseline/data_utils.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	cubert/run_classifier.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	bam/data/preprocessing.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	mobilebert/run_classifier.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	goemotions/bert_classifier.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	goemotions/learn_emotion_relations.py	0	convert a set of `inputexample`s to a tfrecord file.	STRING
HIGH	schema_guided_dst/baseline/bert/optimization.py	0	functions and classes related to optimization (weight updates).	STRING
HIGH	smith/bert/optimization.py	0	functions and classes related to optimization (weight updates).	STRING
2566 more matches not shown…

Unused Imports11407 hits · 11272 pts

Severity	File	Line	Context
LOW	fm4tlp/generate_subgraphs.py	33	CODE
LOW	fm4tlp/generate_structural_features_pipeline.py	30	CODE
LOW	fm4tlp/utils/communities.py	20	CODE
LOW	fm4tlp/utils/train_test_helper.py	29	CODE
LOW	fm4tlp/utils/train_test_helper.py	30	CODE
LOW	fm4tlp/utils/train_test_helper.py	33	CODE
LOW	fm4tlp/utils/train_test_helper.py	34	CODE
LOW	fm4tlp/utils/train_test_helper.py	35	CODE
LOW	fm4tlp/utils/train_test_helper.py	36	CODE
LOW	fm4tlp/utils/negative_generator.py	26	CODE
LOW	fm4tlp/utils/negative_generator.py	27	CODE
LOW	fm4tlp/utils/pre_process.py	21	CODE
LOW	fm4tlp/utils/dataset_pyg_transfer.py	16	CODE
LOW	fm4tlp/utils/dataset_pyg_transfer.py	16	CODE
LOW	fm4tlp/utils/dataset.py	18	CODE
LOW	fm4tlp/utils/dataset.py	18	CODE
LOW	fm4tlp/utils/dataset.py	18	CODE
LOW	fm4tlp/utils/dataset.py	18	CODE
LOW	fm4tlp/utils/utils.py	23	CODE
LOW	fm4tlp/utils/evaluate.py	19	CODE
LOW	fm4tlp/utils/dataset_transfer.py	17	CODE
LOW	fm4tlp/utils/dataset_transfer.py	17	CODE
LOW	fm4tlp/utils/dataset_transfer.py	17	CODE
LOW	fm4tlp/utils/dataset_transfer.py	20	CODE
LOW	fm4tlp/utils/dataset_pyg.py	16	CODE
LOW	fm4tlp/utils/dataset_pyg.py	16	CODE
LOW	fm4tlp/models/jodie.py	18	CODE
LOW	fm4tlp/models/jodie.py	21	CODE
LOW	fm4tlp/models/jodie.py	23	CODE
LOW	fm4tlp/models/jodie.py	30	CODE
LOW	fm4tlp/models/model_template.py	20	CODE
LOW	fm4tlp/models/model_template.py	23	CODE
LOW	fm4tlp/models/model_template.py	25	CODE
LOW	fm4tlp/models/model_template.py	26	CODE
LOW	fm4tlp/models/dyrep.py	18	CODE
LOW	fm4tlp/models/dyrep.py	21	CODE
LOW	fm4tlp/models/dyrep.py	23	CODE
LOW	fm4tlp/models/dyrep.py	30	CODE
LOW	fm4tlp/models/tgn.py	18	CODE
LOW	fm4tlp/models/tgn.py	21	CODE
LOW	fm4tlp/models/tgn.py	23	CODE
LOW	fm4tlp/models/tgn.py	30	CODE
LOW	fm4tlp/models/edgebank.py	19	CODE
LOW	fm4tlp/models/edgebank.py	23	CODE
LOW	fm4tlp/models/edgebank.py	25	CODE
LOW	fm4tlp/models/edgebank.py	27	CODE
LOW	fm4tlp/modules/decoder.py	20	CODE
LOW	fm4tlp/modules/neighbor_loader.py	18	CODE
LOW	fm4tlp/modules/early_stopping.py	21	CODE
LOW	fm4tlp/modules/memory_module.py	31	CODE
LOW	fm4tlp/modules/nodebank.py	16	CODE
LOW	cola/contrastive.py	22	CODE
LOW	cola/supervised.py	19	CODE
LOW	ledge/networks.py	21	CODE
LOW	ledge/utils.py	20	CODE
LOW	nigt_optimizer/nigt_test.py	18	CODE
LOW	nigt_optimizer/nigt_test.py	19	CODE
LOW	nigt_optimizer/nigt_test.py	20	CODE
LOW	nigt_optimizer/nigt_optimizer.py	23	CODE
LOW	nigt_optimizer/nigt_optimizer.py	24	CODE
11347 more matches not shown…

Over-Commented Block10810 hits · 10738 pts

Severity	File	Line	Snippet	Context
LOW	compile_protos.sh	1	#!/bin/bash	COMMENT
LOW	__init__.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/experiment_config.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_wiki_subgraph_prep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/model_config.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/generate_structural_features_pipeline_array.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/get_embedding_correlation.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_comment_dataprep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/generate_subgraphs.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_review_dataprep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/test.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_review_subgraph_prep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/generate_structural_features_pipeline.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_flight_negatives.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/train.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_comment_subgraph_prep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_wiki_dataprep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_coin_subgraph_prep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_flight_dataprep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/tgbl_coin_dataprep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/negative_sampler.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/communities.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/train_test_helper.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/negative_generator.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/pre_process.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/dataset_pyg_transfer.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/dataset.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/utils.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/evaluate.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/structural_feature_helper.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/dataset_transfer.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/utils/dataset_pyg.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/jodie.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/model_template.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/all_models.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/dyrep.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/tgn.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/models/edgebank.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/decoder.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/edgebank_predictor.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/emb_module.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/time_enc.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/heuristics.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/message_agg.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/neighbor_loader.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/early_stopping.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/message_func.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/structural_mapper.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/memory_module.py	1	# coding=utf-8	COMMENT
LOW	fm4tlp/modules/nodebank.py	1	# coding=utf-8	COMMENT
LOW	cola/contrastive.py	1	# coding=utf-8	COMMENT
LOW	cola/constants.py	1	# coding=utf-8	COMMENT
LOW	cola/run.sh	1	#!/bin/bash	COMMENT
LOW	cola/network.py	1	# coding=utf-8	COMMENT
LOW	cola/supervised.py	1	# coding=utf-8	COMMENT
LOW	cola/main.py	1	# coding=utf-8	COMMENT
LOW	cola/data.py	1	# coding=utf-8	COMMENT
LOW	ledge/functions.py	1	# coding=utf-8	COMMENT
LOW	ledge/ledge.py	1	# coding=utf-8	COMMENT
LOW	ledge/run.sh	1	#!/bin/bash	COMMENT
10750 more matches not shown…

Hyper-Verbose Identifiers9041 hits · 9131 pts

Severity	File	Line	Snippet	Context
LOW	fm4tlp/utils/communities.py	26	def _sample_community_cluster(	CODE
LOW	fm4tlp/utils/communities.py	60	def _get_edges_in_time_interval(	CODE
LOW	fm4tlp/utils/communities.py	74	def _enough_edges_in_interval(	CODE
LOW	fm4tlp/utils/communities.py	109	def get_community_cluster_nodes(	CODE
LOW	fm4tlp/utils/train_test_helper.py	47	def normalize_structural_features(	CODE
LOW	fm4tlp/utils/train_test_helper.py	417	def split_for_warmstart_quantile(test_data, warmstart_quantile):	STRING
LOW	fm4tlp/utils/train_test_helper.py	426	def split_for_warmstart_batches(test_data, batch_fraction, batch_size):	STRING
LOW	fm4tlp/utils/negative_generator.py	91	def generate_negative_samples(	STRING
LOW	fm4tlp/utils/negative_generator.py	126	def generate_negative_samples_rnd(	STRING
LOW	fm4tlp/utils/negative_generator.py	201	def generate_historical_edge_set(	STRING
LOW	fm4tlp/utils/negative_generator.py	238	def generate_negative_samples_hist_rnd(	STRING
LOW	fm4tlp/utils/utils.py	85	def _compute_total_structural_feature_mean_std(	CODE
LOW	fm4tlp/utils/utils.py	117	def _compute_total_structural_feature_dimension(	CODE
LOW	fm4tlp/utils/utils.py	199	def _get_structural_measurement_filepath_from_model_path(	STRING
LOW	fm4tlp/utils/utils.py	210	def save_structural_feature_measurement(	STRING
LOW	fm4tlp/utils/utils.py	222	def load_structural_feature_measurement(	STRING
LOW	fm4tlp/utils/structural_feature_helper.py	248	def subgraph_isomorphism_vertex_counts(edge_index, **kwargs):	STRING
LOW	fm4tlp/utils/structural_feature_helper.py	426	def get_all_automorphism_counts(self, nx_graph):	STRING
LOW	fm4tlp/models/jodie.py	320	def predict_memory_embeddings(	CODE
LOW	fm4tlp/models/model_template.py	148	def predict_memory_embeddings(	CODE
LOW	fm4tlp/models/model_template.py	153	def initialize_memory_embedding(	CODE
LOW	fm4tlp/models/dyrep.py	310	def predict_memory_embeddings(	CODE
LOW	fm4tlp/models/tgn.py	289	def predict_memory_embeddings(	CODE
LOW	fm4tlp/models/edgebank.py	189	def predict_memory_embeddings(	CODE
LOW	fm4tlp/modules/edgebank_predictor.py	130	def _update_time_window_memory(	STRING
LOW	cola/network.py	88	def get_efficient_net_encoder(input_shape, pooling):	CODE
LOW	cola/supervised.py	59	def _prepare_standard_example(self, example, is_training):	CODE
LOW	cola/supervised.py	78	def _prepare_downstream_task_data(self):	CODE
LOW	cola/data.py	71	def extract_log_mel_spectrogram(waveform,	CODE
LOW	persistent-nature/utils/soat_util.py	69	def bilinear_interpolate_features(feature00, feature01, feature10, feature11):	CODE
LOW	persistent-nature/utils/camera_util.py	127	def get_full_image_parameters(	CODE
LOW	mentormix/code/cifar_data_provider.py	137	def _apply_with_random_selector(x, func, num_cases):	CODE
LOW	mentormix/code/utils.py	46	def summarize_data_utilization(v, tf_global_step, batch_size, epsilon=0.001):	CODE
LOW	mentormix/code/utils.py	189	def loss_thresholding_function(loss, para_lambda=0.75):	CODE
LOW	mentormix/code/utils.py	400	def get_mentornet_network_hyperparameter(checkpoint_path):	CODE
LOW	rce/rce_agent.py	656	def _critic_loss_debug_summaries(self, td_targets, pred_td_targets1,	CODE
LOW	rce/rce_agent.py	671	def _actor_loss_debug_summaries(self, actor_loss, actions, log_pi,	CODE
LOW	rce/train_eval.py	295	def _filter_invalid_transition(trajectories, unused_arg1):	CODE
LOW	schema_guided_dst/metrics.py	186	def get_active_intent_accuracy(frame_ref, frame_hyp):	CODE
LOW	schema_guided_dst/metrics.py	244	def get_average_and_joint_goal_accuracy(frame_ref, frame_hyp, service,	CODE
LOW	schema_guided_dst/metrics_test.py	63	def _assert_dicts_almost_equal(self, ref_dict, other_dict):	CODE
LOW	schema_guided_dst/metrics_test.py	68	def test_active_intent_accuracy(self):	CODE
LOW	schema_guided_dst/metrics_test.py	114	def test_average_and_joint_goal_accuracy(self):	CODE
LOW⚡	schema_guided_dst/schema.py	101	def get_categorical_slot_values(self, slot):	CODE
LOW⚡	schema_guided_dst/schema.py	110	def get_categorical_slot_from_id(self, slot_id):	CODE
LOW⚡	schema_guided_dst/schema.py	113	def get_non_categorical_slot_from_id(self, slot_id):	CODE
LOW⚡	schema_guided_dst/schema.py	116	def get_categorical_slot_value_from_id(self, slot_id, value_id):	CODE
LOW⚡	schema_guided_dst/schema.py	120	def get_categorical_slot_value_id(self, slot, value):	CODE
LOW	schema_guided_dst/baseline/pred_utils.py	118	def write_predictions_to_file(predictions, input_json_files, schema_json_file,	CODE
LOW	schema_guided_dst/baseline/train_and_predict.py	163	def _file_based_input_fn_builder(dataset_config, input_dial_file,	CODE
LOW	schema_guided_dst/baseline/train_and_predict.py	569	def _get_categorical_slot_goals(self, features):	CODE
LOW	schema_guided_dst/baseline/train_and_predict.py	597	def _get_noncategorical_slot_goals(self, features):	CODE
LOW	schema_guided_dst/baseline/train_and_predict.py	714	def _create_schema_embeddings(bert_config, schema_embedding_file,	CODE
LOW	schema_guided_dst/baseline/data_utils.py	73	class Dstc8DataProcessor(object):	CODE
LOW	schema_guided_dst/baseline/data_utils.py	121	def _create_examples_from_dialog(self, dialog, schemas, dataset):	CODE
LOW	schema_guided_dst/baseline/data_utils.py	153	def _create_examples_from_turn(self, turn_id, system_utterance,	CODE
LOW	schema_guided_dst/baseline/data_utils.py	530	def make_copy_with_utterance_features(self):	CODE
LOW	schema_guided_dst/baseline/data_utils.py	621	def file_based_convert_examples_to_features(dial_examples, dataset_config,	CODE
LOW	schema_guided_dst/baseline/extract_schema_embedding.py	258	def _get_intents_input_features(self, service_schema):	CODE
LOW	schema_guided_dst/baseline/extract_schema_embedding.py	286	def _get_req_slots_input_features(self, service_schema):	CODE
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Docstring Block Structure1146 hits · 5718 pts

Severity	File	Line	Snippet	Context
HIGH	fm4tlp/utils/negative_sampler.py	103	For each positive edge in `pos_batch` returns a list of negative edges. `split_mode` specifies whether the valiatio	STRING
HIGH	fm4tlp/utils/structural_feature_helper.py	179	Computes the automorphism group of a given substructure and the orbit partition of the vertices of the substructure.	STRING
HIGH	fm4tlp/utils/structural_feature_helper.py	249	Computes the number of subgraph isomorphisms for each vertex in a graph. Parameters: edge_index: the edge index	STRING
HIGH	persistent-nature/utils/midas.py	23	Read pfm file. Args: path (str): path to file Returns: tuple: (data, scale) Raises: Exception	STRING
HIGH	mentormix/code/cifar_data_provider.py	52	Provides batches of CIFAR images for resnet. Args: dataset_name: Eiether 'cifar10' or 'cifar100'. split_name:	STRING
HIGH	mentormix/code/cifar_data_provider.py	117	Given a dataset name and a split_name returns a Dataset. Args: name: String, name of the dataset. split_name:	STRING
HIGH	mentormix/code/cifar_data_provider.py	157	Distort the color of the image. Each color distortion is non-commutative and thus ordering of the color ops matters	STRING
HIGH	mentormix/code/cifar100_dataset.py	61	Gets a dataset tuple with instructions for reading cifar100. Args: split_name: A train/test split name. datas	STRING
HIGH	mentormix/code/cifar_train_mentormix.py	117	Function that takes a gradient step and specifies whether to stop. Args: sess: The current session. train_op:	STRING
HIGH	mentormix/code/cifar10_dataset.py	60	Gets a dataset tuple with instructions for reading cifar10. Args: split_name: A train/test split name. datase	STRING
HIGH	rce/rce_agent.py	250	Returns a train op to update the agent's networks. This method trains with the provided batched experience. Ar	STRING
HIGH	schema_guided_dst/baseline/data_utils.py	96	Return a list of `InputExample`s of the data splits' dialogues. Args: dataset: str. can be "train", "dev", or	STRING
HIGH	schema_guided_dst/baseline/bert/modeling.py	299	Maps a string to a Python function, e.g., "relu" => `tf.nn.relu`. Args: activation_string: String name of the act	STRING
HIGH	schema_guided_dst/baseline/bert/modeling.py	456	Performs various post-processing on a word embedding tensor. Args: input_tensor: float Tensor of shape [batch_siz	STRING
HIGH	schema_guided_dst/baseline/bert/modeling.py	705	Performs multi-headed attention from `from_tensor` to `to_tensor`. This is an implementation of multi-headed attentio	STRING
HIGH	schema_guided_dst/baseline/bert/modeling.py	848	Multi-headed, multi-layer Transformer from "Attention is All You Need". This is almost an exact implementation of the	STRING
HIGH	loss_functions_transfer/resnet_model.py	79	DropBlock: a regularization method for convolutional neural networks. DropBlock is a form of structured dropout, wher	STRING
HIGH	loss_functions_transfer/resnet_model.py	375	Generator for ResNet v1 models. Args: block_fn: `function` for the block to use within the model. Either	STRING
HIGH	musiq/model/preprocessing.py	306	Gets the preprocessing function for Multiscale Image Quality Transformer. The output preprocessing function expects a	STRING
HIGH	optimizing_interpretability/regularizers.py	188	Computes the specified regularization loss. Args: regularizer: string name of the penalty to apply. logits: t	STRING
HIGH	optimizing_interpretability/metrics_utils.py	26	Checks if two image tensors are compatible for metric computation. This function checks if two sets of images have ra	STRING
HIGH	optimizing_interpretability/imagenet/resnet_model.py	86	Strided 2-D convolution with explicit padding. The padding is consistent and is based only on `kernel_size`, not on t	STRING
HIGH	optimizing_interpretability/imagenet/utils.py	23	Transformation of a single image by adding noise. If a random gaussian distribution of noisy is specified (noise='r_n	STRING
HIGH	optimizing_interpretability/imagenet/utils.py	102	Formats metrics to be callable as tf.summary scalars on tpu's. Args: *dicts: A set of metric dictionaries, contai	STRING
HIGH	…fied_exemplars/pie_dataset_gen/imagenet_predictions.py	63	Outputs predictions as a pandas dataframe. Args: directory_path: The path to the directory where dataset is store	STRING
HIGH	pruning_identified_exemplars/pruning_tools/pruning.py	376	Updates the mask for a given weight tensor for magnitude based pruning. This functions first computes the cdf of th	STRING
HIGH	pruning_identified_exemplars/pruning_tools/pruning.py	424	Randomly identifies subset of weights to be set to zero in the network. If pruning method is specified as 'rando	STRING
HIGH	pruning_identified_exemplars/pruning_tools/pruning.py	487	Performs block-granular masking of the weights. Block pruning occurs only if the block_height or block_width is > 1	STRING
HIGH	…ng_identified_exemplars/pruning_tools/pruning_utils.py	99	Expands a 2D tensor by replicating the tensor values. This is equivalent to the kronecker product of the tensor and a	STRING
HIGH	…ng_identified_exemplars/pruning_tools/pruning_utils.py	172	Performs m x n pooling through a combination of 1xm and 1xn pooling. Args: input_tensor: Input tensor. Must be ra	STRING
HIGH	…ng_identified_exemplars/pruning_tools/pruning_layer.py	41	Returns an initializer that generates tensors without scaling variance. When initializing a deep network, it is in pr	STRING
HIGH	pruning_identified_exemplars/utils/resnet_model.py	125	Strided 2-D convolution with explicit padding. The padding is consistent and is based only on `kernel_size`, not on t	STRING
HIGH	compositional_rl/gwob/CoDE/web_environment.py	363	Visit an element with a given value. Element HTML ids uniquely define a concept for each page. An example would	STRING
HIGH	compositional_rl/gwob/CoDE/web_environment.py	526	Run the action in the WoB environment and get observation and reward. There are two types of actions: (i) (Abstra	STRING
HIGH	compositional_rl/gwob/CoDE/web_observation_wrappers.py	95	Generate dom element sequence from a given observation. Args: obs: Observation from WoB environment state. lo	STRING
HIGH	compositional_rl/gwob/CoDE/web_observation_wrappers.py	173	Wrap intersection between profile and dom elements. For each profile field key and value tokens (such as ["first", "n	STRING
HIGH	compositional_rl/gwob/CoDE/web_observation_wrappers.py	329	Wrap a given observation into numpy arrays. Args: obs: Observation from WoB environment state. structured_fie	STRING
HIGH	compositional_rl/gwob/CoDE/base_web_environment.py	463	Run the action in the WoB environment. The main purpose of the 'step' function is to convert the input action into	STRING
HIGH	compositional_rl/gwob/CoDE/base_web_environment.py	622	Execute miniwob level action on the miniwob environment. Args: miniwob_action: A Low level miniwob action tha	STRING
HIGH	compositional_rl/gwob/CoDE/vocabulary_node.py	124	Add words to the global vocabulary until a specified limit. Args: words_to_add: A list of words to add to the	STRING
HIGH	compositional_rl/gwob/CoDE/utils.py	296	Generate a click or keyboard action. Args: dom_elements: A list of dom elements. action_type: Type of the act	STRING
HIGH	compositional_rl/gwob/CoDE/utils.py	327	Return a list of dom attributes. Args: dom_element: A dom element. num_attributes: If given, use this many a	STRING
HIGH	compositional_rl/gwob/CoDE/utils.py	351	Tokenize and indexify a dom element. Args: dom_element: A dom element instance. local_vocabulary: A dictionar	STRING
HIGH	meta_reward_learning/semantic_parsing/nsm/data_utils.py	534	Helper function for pack_nest_as. Args: structure: Substructure (tuple of elements and/or tuples) to mimic fl	STRING
HIGH	meta_reward_learning/semantic_parsing/nsm/data_utils.py	565	Returns a given flattened sequence packed into a nest. If `structure` is a scalar, `flat_sequence` must be a single-e	STRING
HIGH	meta_reward_learning/semantic_parsing/nsm/data_utils.py	623	Applies `func` to each entry in `structure` and returns a new structure. Applies `func(x[0], x[1], ...)` where x[i] i	STRING
HIGH	…_reward_learning/semantic_parsing/nsm/model_factory.py	128	Run the TF graph for one pass through the data in feed_dict. Args: fetch_list: A list of the names of the nod	STRING
HIGH	meta_reward_learning/semantic_parsing/nsm/tf_utils.py	268	Linear map: sum_i(args[i] * W[i]), where W[i] is a variable. Args: args: a 2D Tensor or a list of 2D, batch x n,	STRING
HIGH	dp_topk/experiment.py	170	Computes 25th, 50th, and 75th percentile errors and times for each method. Args: item_counts: Array of item count	STRING
HIGH	dp_topk/joint.py	99	Computes array of log(sequence count) for each diff in diff_matrix. Args: diff_matrix: Matrix of distinct count d	STRING
HIGH	dp_topk/joint.py	148	Numerically stable method for sampling from an exponential distribution. Args: log_terms: Array of terms of form	STRING
HIGH	dp_topk/joint.py	197	Computes max values from (simulated) draws from the expo distribution. Args: expo_lambda: Exponential distributio	STRING
HIGH	dp_topk/joint.py	235	Samples an index of sorted_diffs according to permute-and-flip (PNF). Args: log_diff_counts: Array of log(# seque	STRING
HIGH	gfsa/sparse_operator.py	162	Pad the number of entries in the operator's `nonzero` axis. We can always expand an operator by adding new entries	STRING
HIGH	gfsa/generic_ast_graphs.py	220	Converts a generic AST into a graph POMDP. The graph returned by this function will conform to the schema produced by	STRING
HIGH	gfsa/jax_util.py	171	Register a dataclass as a JAX pytree and a flax serializable object. This makes it so that wrapped dataclasses can be	STRING
HIGH	gfsa/ast_spec_inference.py	163	Infers an AST spec compatible with all observations. Since nonterminal information is not available when looking at o	STRING
HIGH	gfsa/training/train_util.py	103	Train the model for one step in parallel across devices. Args: optimizer: Optimizer that tracks the model and par	STRING
HIGH	gfsa/training/simple_runner.py	188	Run the main training loop. Args: optimizer: Initial optimizer object. Also responsible for tracking the model	STRING
HIGH	gfsa/datasets/data_loading.py	115	Batch together elements from source. Args: source: Iterable of elements. batch_dim_sizes: Prefix of the shape	STRING
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Deep Nesting2738 hits · 2656 pts

Severity	File	Line	Context
LOW	fm4tlp/utils/communities.py	109	CODE
LOW	fm4tlp/utils/train_test_helper.py	64	CODE
LOW	fm4tlp/utils/train_test_helper.py	193	CODE
LOW	fm4tlp/utils/train_test_helper.py	438	CODE
LOW	fm4tlp/utils/negative_generator.py	238	CODE
LOW	fm4tlp/utils/pre_process.py	95	CODE
LOW	fm4tlp/utils/pre_process.py	176	CODE
LOW	fm4tlp/utils/pre_process.py	260	CODE
LOW	fm4tlp/utils/pre_process.py	382	CODE
LOW	fm4tlp/utils/pre_process.py	510	CODE
LOW	fm4tlp/utils/utils.py	117	CODE
LOW	fm4tlp/utils/structural_feature_helper.py	375	CODE
LOW	fm4tlp/utils/dataset_transfer.py	91	CODE
LOW	fm4tlp/modules/edgebank_predictor.py	161	CODE
LOW	fm4tlp/modules/memory_module.py	481	CODE
LOW	cola/main.py	78	CODE
LOW	ledge/ledge.py	110	CODE
LOW	scrna_benchmark/compute_metrics.py	147	CODE
LOW	warmstart_graphcut_image_segmentation/warmstart.py	37	CODE
LOW	…start_graphcut_image_segmentation/imagesegmentation.py	181	CODE
LOW	…start_graphcut_image_segmentation/imagesegmentation.py	244	CODE
LOW	warmstart_graphcut_image_segmentation/augmentingPath.py	38	CODE
LOW	persistent-nature/utils/soat_util_triplane.py	127	CODE
LOW	persistent-nature/utils/soat_util_triplane.py	234	CODE
LOW	persistent-nature/utils/soat_util_triplane.py	310	CODE
LOW	persistent-nature/utils/show.py	63	CODE
LOW	persistent-nature/utils/soat_util.py	141	CODE
LOW	aloe/aloe/rfill/main_supervised.py	57	CODE
LOW	aloe/aloe/rfill/editor.py	79	CODE
LOW	aloe/aloe/rfill/editor.py	190	CODE
LOW	aloe/aloe/rfill/sampler.py	145	CODE
LOW	aloe/aloe/rfill/main_editor.py	66	CODE
LOW	aloe/aloe/rfill/utils/program_struct.py	26	CODE
LOW	aloe/aloe/rfill/utils/rfill_grammar_short.py	29	CODE
LOW	aloe/aloe/rfill/utils/rfill_grammar_short.py	50	CODE
LOW	aloe/aloe/common/pytorch_util.py	99	CODE
LOW	aloe/aloe/common/synthetic/dataset.py	36	CODE
LOW	aloe/aloe/common/synthetic/toy_data_gen.py	24	CODE
LOW	aloe/aloe/synthetic/reverse_train.py	78	CODE
LOW	aloe/aloe/synthetic/reverse_train.py	115	CODE
LOW	mentormix/code/cifar_train_mentormix.py	153	CODE
LOW	rce/rce_envs.py	43	CODE
LOW	rce/rce_envs.py	276	CODE
LOW	schema_guided_dst/metrics.py	129	CODE
LOW	schema_guided_dst/evaluate.py	81	CODE
LOW	schema_guided_dst/evaluate.py	102	CODE
LOW	schema_guided_dst/baseline/pred_utils.py	35	CODE
LOW	schema_guided_dst/baseline/train_and_predict.py	752	CODE
LOW	schema_guided_dst/baseline/data_utils.py	204	CODE
LOW	schema_guided_dst/baseline/data_utils.py	565	CODE
LOW	schema_guided_dst/baseline/bert/tokenization.py	99	CODE
LOW	schema_guided_dst/baseline/bert/tokenization.py	119	CODE
LOW	schema_guided_dst/baseline/bert/tokenization.py	337	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	298	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	837	CODE
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	164	CODE
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	244	CODE
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	397	CODE
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	463	CODE
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	476	CODE
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Decorative Section Separators770 hits · 2542 pts

Severity	File	Line	Snippet	Context
MEDIUM⚡	fm4tlp/get_embedding_correlation.py	128	# ==========	STRING
MEDIUM⚡	fm4tlp/get_embedding_correlation.py	129	# ==========	STRING
MEDIUM⚡	fm4tlp/get_embedding_correlation.py	130	# ==========	STRING
MEDIUM	fm4tlp/get_embedding_correlation.py	142	# ==========	STRING
MEDIUM⚡	fm4tlp/test.py	187	# ==========	STRING
MEDIUM⚡	fm4tlp/test.py	188	# ==========	STRING
MEDIUM⚡	fm4tlp/test.py	189	# ==========	STRING
MEDIUM	fm4tlp/test.py	201	# ==========	STRING
MEDIUM⚡	fm4tlp/train.py	191	# ==========	STRING
MEDIUM⚡	fm4tlp/train.py	192	# ==========	STRING
MEDIUM⚡	fm4tlp/train.py	193	# ==========	STRING
MEDIUM	fm4tlp/train.py	209	# ==========	STRING
MEDIUM	persistent-nature/utils/camera_util.py	165	# --------------------------------------------------------------------	COMMENT
MEDIUM	persistent-nature/utils/camera_util.py	243	# --------------------------------------------------------------------	COMMENT
MEDIUM	persistent-nature/utils/camera_util.py	299	# --------------------------------------------------------------------	COMMENT
MEDIUM	persistent-nature/utils/sky_util.py	24	# --------------------------------------------------------------------------	COMMENT
MEDIUM	persistent-nature/utils/sky_util.py	100	# --------------------------------------------------------------------------	COMMENT
MEDIUM	persistent-nature/models/misc/networks.py	22	# -------------------------------------------------------------------------------------	COMMENT
MEDIUM	mentormix/code/cifar_data_provider.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/training_mentormix_command.sh	14	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/cifar100_dataset.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/resnet_model.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/cifar_train_mentormix.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/utils.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/cifar_eval.py	29	# ==============================================================================	COMMENT
MEDIUM	mentormix/code/cifar10_dataset.py	29	# ==============================================================================	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	805	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	808	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	811	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	814	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	834	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	839	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	844	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	849	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	870	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	873	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	876	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	879	# -----------------	COMMENT
MEDIUM⚡	gfsa/automaton_builder_test.py	884	# -----------------	COMMENT
MEDIUM	ugsl/tfgnn_datasets.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/residue_encoding.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/model_utils.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/config.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/mutation_encoding.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/dataset_utils.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/util/inference_utils.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/model_training/train_utils.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/model_training/lr.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/model_training/cnn.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/model_training/train.py	29	# ==============================================================================	COMMENT
MEDIUM	aav/model_training/rnn.py	29	# ==============================================================================	COMMENT
MEDIUM	simpdom/block_lstm.py	29	# ==============================================================================	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	393	# ----------------------	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	395	# ----------------------	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	440	# ------------------------------	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	442	# ------------------------------	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	487	# ------------------------	COMMENT
MEDIUM	fast_gradient_clipping/src/custom_registry_functions.py	489	# ------------------------	COMMENT
MEDIUM	imp/max/projects/imp/config/model.py	27	# ----------------------------------------------------------------------	COMMENT
MEDIUM	imp/max/projects/imp/config/model.py	29	# ----------------------------------------------------------------------	COMMENT
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Self-Referential Comments466 hits · 1376 pts

Severity	File	Line	Snippet	Context
MEDIUM	persistent-nature/utils/soat_util_triplane.py	402	# Create a batch of rays for volume rendering	COMMENT
MEDIUM	mentormix/code/cifar_train_mentormix.py	187	# Define the model:	COMMENT
MEDIUM	mentormix/code/cifar_train_mentormix.py	325	# Create an initial assignment function.	COMMENT
MEDIUM	mentormix/code/cifar_eval.py	103	# Define the model:	COMMENT
MEDIUM	mentormix/code/cifar_eval.py	126	# Define the metrics:	COMMENT
MEDIUM	schema_guided_dst/baseline/pred_utils.py	111	# Create a new dict to avoid overwriting the state in previous turns	COMMENT
MEDIUM	schema_guided_dst/baseline/data_utils.py	173	# Create an example for this service.	COMMENT
MEDIUM	schema_guided_dst/baseline/bert/modeling.py	508	# Create the variable outside the assertion to avoid TF2 compatibility	COMMENT
MEDIUM	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	814	# Create a new json file and save the dialogues.	COMMENT
MEDIUM	jrl/evaluation/__init__.py	92	# Create the run loop and return it.	COMMENT
MEDIUM	multi_resolution_rec/model_test.py	111	with self.test_session(graph=tf.Graph()) as sess: # Create a new graph.	CODE
MEDIUM	…fied_exemplars/pie_dataset_gen/generate_pie_dataset.py	59	# Create a single Session to run all image coding calls.	COMMENT
MEDIUM⚡	…positional_rl/gwob/examples/web_environment_example.py	43	# Create a generic web environment to which we will add primitives and	COMMENT
MEDIUM	…positional_rl/gwob/examples/web_environment_example.py	65	# Create a shopping website design with difficulty = 3.	COMMENT
MEDIUM	…_reward_learning/semantic_parsing/nsm/graph_factory.py	330	# Create the update op for theta (model parameters)	COMMENT
MEDIUM	…_reward_learning/semantic_parsing/nsm/graph_factory.py	343	# Create the meta training loss	COMMENT
MEDIUM	meta_reward_learning/semantic_parsing/nsm/data_utils.py	495	# The following code are copied from TensorFlow source code.	COMMENT
MEDIUM	meta_reward_learning/textworld/lib/model.py	249	# Create a trainable weight variable for this layer.	COMMENT
MEDIUM	gfsa/model/automaton_layer_test.py	79	# Create a simple schema and empty encoded graph.	COMMENT
MEDIUM	mave/benchmark/models/crf_layer.py	16	# This file is branched from 'tensorflow_addons/layers/crf.py'	COMMENT
MEDIUM	mave/benchmark/models/crf_utils.py	16	# This file is branched from 'tensorflow_addons/text/crf.py'	COMMENT
MEDIUM	aav/model_training/cnn.py	136	# Define a scope for reusing the variables	COMMENT
MEDIUM	simpdom/extract_xpaths.py	396	# Define the fixed-text nodes and variable nodes.	COMMENT
MEDIUM	imp/max/core/utils.py	789	# Create an empty array with full expected shape	COMMENT
MEDIUM	imp/max/modeling/attention.py	164	# Create a OHE of the current index. NOTE: the index is increased below.	COMMENT
MEDIUM	imp/max/execution/config.py	116	# Create a random seed based on the current time and process to	COMMENT
MEDIUM	imp/max/execution/executors.py	606	# Initialize model variables	COMMENT
MEDIUM	dpok/train_online_pg.py	1476	# Create the pipeline using the trained modules and save it.	COMMENT
MEDIUM	low_rank_local_connectivity/data_provider.py	35	# Create a mask variable to track the real vs padded data in the last batch.	COMMENT
MEDIUM	low_rank_local_connectivity/data_provider.py	193	# Create a mask variable to track the real vs padded data in the last batch.	COMMENT
MEDIUM	jaxbarf/install.sh	5	# Create the virtual environment.	COMMENT
MEDIUM	…aph_compression/compression_lib/compression_op_test.py	517	# Create a compression object using the compression hyperparameters	COMMENT
MEDIUM	…ompression_lib/examples/cifar10/cifar10_compression.py	30	# Create a graph to run one step of training with respect to the loss.	STRING
MEDIUM	…ompression_lib/examples/cifar10/cifar10_compression.py	157	# Create a compression object using the compression hyperparameters	COMMENT
MEDIUM	…sion/compression_lib/examples/cifar10/cifar10_input.py	117	# Create a queue that shuffles the examples, and then	COMMENT
MEDIUM	…sion/compression_lib/examples/cifar10/cifar10_input.py	158	# Create a queue that produces the filenames to read.	COMMENT
MEDIUM	…sion/compression_lib/examples/cifar10/cifar10_input.py	231	# Create a queue that produces the filenames to read.	COMMENT
MEDIUM	…sion/compression_lib/examples/cifar10/cifar10_train.py	59	# Create a compression object using the compression hyperparameters	COMMENT
MEDIUM	hct/tests/test_ndp.py	39	# Create a small model	COMMENT
MEDIUM	hct/tests/test_ndp.py	114	# Create a batch of data, split across devices	COMMENT
MEDIUM	sparse_soft_topk/_src/isotonic_pav.py	448	# Define the expected shape & dtype of output.	COMMENT
MEDIUM	sparse_soft_topk/_src/isotonic_pav.py	917	# Define the expected shape & dtype of output.	COMMENT
MEDIUM	caql/caql_agent_test.py	76	# Create an agent, train 17 steps, and save a checkpoint.	COMMENT
MEDIUM	caql/caql_agent_test.py	109	# Create an agent and restore TF variables from the checkpoint.	COMMENT
MEDIUM	k_norm/ellipse_plot.py	26	# The following code computes the mean squared l_2 norms of samples from the	COMMENT
MEDIUM	k_norm/ellipse_plot.py	48	# The following code plots the data generated by the two experiments above, on a	COMMENT
MEDIUM	k_norm/k_norm_plot.py	30	# The following code computes the mean squared l_2 norms of samples from the	COMMENT
MEDIUM	k_norm/k_norm_plot.py	81	# The following code is similar to the Sum code above but uses the Count ball.	COMMENT
MEDIUM	k_norm/k_norm_plot.py	127	# The following code is similar to the Sum code above, but uses the Vote ball.	COMMENT
MEDIUM	k_norm/k_norm_plot.py	173	# The following code plots the data generated by the three experiments above, on	COMMENT
MEDIUM	smu/pipeline.py	830	# Create a collection of molecules with duplicate information	COMMENT
MEDIUM	smu/parser/smu_utils_lib.py	29	"""This class provides shared utilities for parsing and writing SMU7 files."""	STRING
MEDIUM	smu/parser/smu_parser_lib.py	245	# This function is the only one that uses gfile.	COMMENT
MEDIUM	ara_optimization/synthetic_dataset.py	465	# Create a CSV file	COMMENT
MEDIUM	vila/coca_vila_layers.py	158	# Create the unimodal transformer layers.	COMMENT
MEDIUM	vila/coca_vila_layers.py	176	# Create the crossmodal transformer layers.	COMMENT
MEDIUM	frmt/lexical_accuracy.py	289	# Create a single row for each source language term.	COMMENT
MEDIUM	task_set/tasks/losg_problems/problem_generator.py	321	# Define the network as a list of weight + bias shapes for each layer.	COMMENT
MEDIUM	task_set/tasks/losg_problems/problem_generator.py	469	# Create a mesh over the given coordinate ranges.	COMMENT
MEDIUM	graphqa/graph_task_generator.py	214	# Defining a task on the graphs	COMMENT
406 more matches not shown…

AI Structural Patterns1172 hits · 1130 pts

Severity	File	Line	Context
LOW	fm4tlp/utils/pre_process.py	51	CODE
LOW	fm4tlp/utils/dataset_pyg_transfer.py	193	CODE
LOW	fm4tlp/utils/dataset_pyg_transfer.py	218	CODE
LOW	fm4tlp/utils/dataset_pyg.py	222	CODE
LOW	fm4tlp/utils/dataset_pyg.py	247	CODE
LOW	fm4tlp/modules/structural_mapper.py	33	CODE
LOW	ledge/functions.py	67	CODE
LOW	nigt_optimizer/nigt_optimizer.py	35	CODE
LOW	persistent-nature/utils/regularizers.py	51	CODE
LOW	persistent-nature/utils/utils.py	55	CODE
LOW	persistent-nature/utils/filters.py	137	CODE
LOW	aloe/aloe/rfill/utils/rfill_parser.py	176	CODE
LOW	rce/rce_agent.py	51	CODE
LOW	rce/train_eval.py	98	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	377	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	542	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	446	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	692	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	837	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	36	CODE
LOW	schema_guided_dst/baseline/bert/modeling.py	106	CODE
LOW	learn_to_infer/eval_gmm.py	71	CODE
LOW	learn_to_infer/eval_gmm.py	94	CODE
LOW	learn_to_infer/ring_models.py	34	CODE
LOW	learn_to_infer/run_lda.py	82	CODE
LOW	learn_to_infer/run_lda.py	116	CODE
LOW	learn_to_infer/transformer.py	210	CODE
LOW	learn_to_infer/run_gmm.py	92	CODE
LOW	learn_to_infer/run_gmm.py	115	CODE
LOW	learn_to_infer/run_gmm.py	141	CODE
LOW	learn_to_infer/train.py	42	CODE
LOW	learn_to_infer/gmm_models.py	34	CODE
LOW	learn_to_infer/gmm_models.py	164	CODE
LOW	learn_to_infer/gmm_models.py	300	CODE
LOW	learn_to_infer/lda_models.py	68	CODE
LOW	learn_to_infer/lda_models.py	127	CODE
LOW	learn_to_infer/run_ncp.py	81	CODE
LOW	jrl/agents/msg/networks.py	274	CODE
LOW	jrl/agents/msg/learning.py	64	CODE
LOW	jrl/agents/snr/learning.py	66	CODE
LOW	jrl/agents/bc/learning.py	52	CODE
LOW	jrl/agents/cql/learning.py	56	CODE
LOW	jrl/agents/batch_ensemble_msg/learning.py	62	CODE
LOW	jrl/utils/logger_utils.py	74	CODE
LOW	musiq/model/multiscale_transformer_utils.py	141	CODE
LOW	multi_resolution_rec/modules.py	154	CODE
LOW	cascaded_networks/models/dense_blocks.py	64	CODE
LOW	cascaded_networks/models/dense_blocks.py	88	CODE
LOW	cascaded_networks/models/densenet.py	168	CODE
LOW	cascaded_networks/models/resnet.py	163	CODE
LOW	cascaded_networks/models/layers.py	120	CODE
LOW	cascaded_networks/models/layers.py	141	CODE
LOW	cascaded_networks/models/layers.py	197	CODE
LOW	cascaded_networks/models/layers.py	218	CODE
LOW	pruning_identified_exemplars/pruning_tools/pruning.py	204	CODE
LOW	…ning_identified_exemplars/pruning_tools/core_layers.py	50	CODE
LOW	…ning_identified_exemplars/pruning_tools/core_layers.py	211	CODE
LOW	…ng_identified_exemplars/pruning_tools/pruning_layer.py	173	CODE
LOW	…ng_identified_exemplars/pruning_tools/pruning_layer.py	230	CODE
LOW	pruning_identified_exemplars/utils/resnet_model.py	25	CODE
1112 more matches not shown…

Hallucination Indicators80 hits · 905 pts

Severity	File	Line	Snippet	Context
CRITICAL	private_text_transformers/private_t5x/tasks.py	80	for b in tfds.text.glue.Glue.builder_configs.values():	CODE
CRITICAL	…logue_ope/airdialogue_ope/modeling/modeling_roberta.py	103	self.roberta_qnet.embeddings.token_type_embeddings.weight.data.zero_()	CODE
CRITICAL⚡	smu/parser/smu_parser_lib.py	669	self._molecule.opt_geo.brot.val.extend(float(x) for x in values)	CODE
CRITICAL	…llm-intrinsic-reward/trl/models/modeling_value_head.py	136	self.v_head.summary.weight.data.normal_(mean=0.0, std=initializer_range)	STRING
CRITICAL	…llm-intrinsic-reward/trl/models/modeling_value_head.py	137	self.v_head.summary.bias.data.zero_()	STRING
CRITICAL	…llm-intrinsic-reward/trl/models/modeling_value_head.py	391	self.v_head.summary.weight.data.normal_(mean=0.0, std=initializer_range)	STRING
CRITICAL	…llm-intrinsic-reward/trl/models/modeling_value_head.py	392	self.v_head.summary.bias.data.zero_()	STRING
CRITICAL	postproc_fairness/utils/load_adult.py	314	encoded_feature = tf.keras.layers.experimental.preprocessing.HashedCrossing(	CODE
CRITICAL	postproc_fairness/utils/load_adult.py	321	encoded_feature = tf.keras.layers.experimental.preprocessing.HashedCrossing(	CODE
CRITICAL	…ation/centralized_so_nwp/stackoverflow_basis_models.py	113	return tf.compat.v1.nn.rnn_cell.LSTMStateTuple(self._num_units,	CODE
CRITICAL	genomics_ood/images_ood/utils.py	34	dataset = tf.compat.v1.data.Dataset.from_tensor_slices(	CODE
CRITICAL	genomics_ood/images_ood/train.py	133	tf.compat.v1.keras.backend.set_session(sess)	STRING
CRITICAL	genomics_ood/images_ood/eval.py	110	tf.compat.v1.keras.backend.set_session(sess)	CODE
CRITICAL	ieg/models/basemodel.py	317	tf.compat.v2.profiler.experimental.start(	CODE
CRITICAL	ieg/models/basemodel.py	329	tf.compat.v2.profiler.experimental.stop()	CODE
CRITICAL	distracting_control/background.py	242	with self._env.physics.contexts.gl.make_current() as ctx:	CODE
CRITICAL	gift/pipelines/multi_env_end2end.py	136	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_end2end.py	264	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_domain_adversarial.py	48	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_domain_adversarial.py	224	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/gradual_adaptation_with_mixup.py	87	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/gradual_adaptation_with_mixup.py	289	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_manifold_mixup.py	35	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_manifold_mixup.py	171	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_trainer.py	77	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/multi_env_trainer.py	257	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL	gift/pipelines/self_adaptive_trainer.py	232	map(int, self.task.dataset.data_iters.validation.keys()))	CODE
CRITICAL⚡	kws_streaming/layers/non_scaling_dropout_test.py	30	tf.compat.v1.keras.backend.set_session(self.sess)	CODE
CRITICAL⚡	kws_streaming/layers/non_scaling_dropout_test.py	35	tf.compat.v1.keras.backend.clear_session()	CODE
CRITICAL	kws_streaming/layers/quantize.py	143	scheme = tfmot.quantization.keras.experimental.default_n_bit.DefaultNBitQuantizeScheme(	CODE
CRITICAL	kws_streaming/models/utils.py	687	converter = tf.compat.v2.lite.TFLiteConverter.from_saved_model(	CODE
CRITICAL	…tein_universe/evaluation/model_performance_analysis.py	146	with tf.io.tf.io.gfile.GFile(filename, 'r') as f:	CODE
CRITICAL⚡	structured_multihashing/README.md	35	net = tf.compat.v2.keras.layers.Conv2D(	CODE
CRITICAL⚡	structured_multihashing/README.md	37	net = tf.compat.v2.keras.layers.MaxPool2D(	CODE
CRITICAL⚡	structured_multihashing/README.md	39	net = tf.compat.v2.keras.layers.Flatten()(net)	CODE
CRITICAL⚡	structured_multihashing/README.md	40	logits = tf.compat.v2.keras.layers.Dense(10)(net)	CODE
CRITICAL⚡	structured_multihashing/README.md	140	net = tf.compat.v2.keras.layers.Conv2D(	CODE
CRITICAL⚡	structured_multihashing/README.md	142	net = tf.compat.v2.keras.layers.MaxPool2D(	CODE
CRITICAL⚡	structured_multihashing/README.md	144	net = tf.compat.v2.keras.layers.Flatten()(net)	CODE
CRITICAL⚡	structured_multihashing/README.md	145	logits = tf.compat.v2.keras.layers.Dense(10)(net)	CODE
CRITICAL⚡	sifer/learning/algorithms.py	249	self.aux_network.featurizer.network.conv1.parameters(),	CODE
CRITICAL⚡	sifer/learning/algorithms.py	250	self.aux_network.featurizer.network.bn1.parameters(),	CODE
CRITICAL⚡	sifer/learning/algorithms.py	251	self.aux_network.featurizer.network.layer1.parameters(),	CODE
CRITICAL⚡	sifer/learning/algorithms.py	252	self.aux_network.featurizer.network.layer2.parameters(),	CODE
CRITICAL⚡	sifer/learning/algorithms.py	253	self.aux_network.featurizer.network.layer3.parameters(),	CODE
CRITICAL⚡	sifer/learning/algorithms.py	254	self.aux_network.featurizer.network.layer4.parameters(),	CODE
CRITICAL	sifer/models/networks.py	133	tmp = self.network.conv1.weight.data.clone()	CODE
CRITICAL	sifer/models/networks.py	188	tmp = self.network.conv1.weight.data.clone()	CODE
CRITICAL	uq_benchmark_2019/experiment_utils.py	233	return tf.compat.v1.distribute.experimental.ParameterServerStrategy()	CODE
CRITICAL	l2tl/svhn_data/svhn_small.py	95	data = tfds.core.lazy_imports.scipy.io.loadmat(f)	CODE
CRITICAL	generative_trees/src/Generator_Node.java	193	true); // Feature.copyOf((Feature) gt.myBoost.myDomain.myDS.features.elementAt(fni),	CODE
CRITICAL	…ormer_modifications/transformer_modifications/tasks.py	87	for b in tfds.text.super_glue.SuperGlue.builder_configs.values():	CODE
CRITICAL	factors_of_influence/fids/berkeley_deep_drive.py	211	file_names = tf.io.tf.io.gfile.listdir(test_path)	CODE
CRITICAL	tempered_boosting/PoincareDiskEmbedding.java	111	== boss.myViewer.myExperiments.myAlgos.all_algorithms.elementAt(index_algorithm_plot)	CODE
CRITICAL⚡	tempered_boosting/PoincareDiskEmbedding.java	122	== boss.myViewer.myExperiments.myAlgos.all_algorithms.elementAt(index_algorithm_plot)	CODE
CRITICAL⚡	tempered_boosting/PoincareDiskEmbedding.java	132	if (boss.myViewer.myExperiments.myAlgos.all_algorithms.size() > 0) {	CODE
CRITICAL⚡	tempered_boosting/PoincareDiskEmbedding.java	134	if (nextAlg == boss.myViewer.myExperiments.myAlgos.all_algorithms.size()) nextAlg = 0;	CODE
CRITICAL⚡	tempered_boosting/DecisionTreeNode.java	124	for (i = 0; i < myTree.myBoost.myDomain.myDS.features.size(); i++) {	CODE
CRITICAL⚡	tempered_boosting/DecisionTreeNode.java	127	((Feature) myTree.myBoost.myDomain.myDS.features.elementAt(i)).type))) {	CODE
CRITICAL⚡	tempered_boosting/DecisionTreeNode.java	132	((Feature) myTree.myBoost.myDomain.myDS.features.elementAt(i)).tests.size()));	CODE
20 more matches not shown…

AI Slop Vocabulary264 hits · 702 pts

Severity	File	Line	Snippet	Context
MEDIUM	aloe/aloe/rfill/utils/rfill_parser.py	16	"""Parser for robust fill language."""	STRING
MEDIUM	aloe/aloe/common/configs.py	82	#robust fill	COMMENT
LOW	schema_guided_dst/baseline/bert/modeling.py	315	# function, so we just return it.	COMMENT
MEDIUM	musiq/model/resnet.py	133	if isinstance(num_layers, list): # Be robust to silly mistakes.	CODE
MEDIUM	compositional_rl/gwob/CoDE/q_networks.py	195	# Apply dropout on the value. Essentially, this allows ignoring the value	COMMENT
LOW	…ward_learning/semantic_parsing/nsm/executor_factory.py	618	# entity, otherwise just use hop.	COMMENT
MEDIUM	robust_loss/distribution.py	225	r"""Draw samples from the robust distribution.	STRING
MEDIUM	simpdom/models.py	409	# Reshape the shape into three dims to facilitate the tf.matmul.	COMMENT
MEDIUM	TimesX/dataset_agent/modules/module_01_trends.py	48	"""Create a robust TrendReq instance with optional proxy and retry mechanisms.	STRING
MEDIUM⚡	TimesX/dataset_agent/modules/module_01_trends.py	236	# Check if this is a rate limit error and we haven't switched to robust mode yet	COMMENT
MEDIUM⚡	TimesX/dataset_agent/modules/module_01_trends.py	244	# Switch to robust pytrends instance	COMMENT
MEDIUM⚡	TimesX/dataset_agent/modules/module_01_trends.py	252	# Retry the failed keyword with robust instance	COMMENT
MEDIUM⚡	TimesX/dataset_agent/modules/module_01_trends.py	262	# Additional delay for robust mode	COMMENT
MEDIUM⚡	TimesX/dataset_agent/modules/module_01_trends.py	300	# Either not a rate limit error or already in robust mode	COMMENT
MEDIUM	policy_eval/train_eval.py	244	# Doubly-robust is effectively the same as importance-weighting but	COMMENT
MEDIUM	ara_optimization/synthetic_dataset.py	80	# support, we utilize the following equation:	COMMENT
LOW	task_set/variable_replace.py	132	# If there is no initializer set, just use the initial value.	COMMENT
LOW	data_selection/wmt/clf_infer.py	166	# the targets were decoded above so just use the ones that were decoded	COMMENT
MEDIUM⚡	study_recommend/datasource.py	327	# We get the indices of sequences pertaining to the current student that	COMMENT
MEDIUM⚡	study_recommend/datasource.py	329	# n is the number of sequences pertaining to the current student.	COMMENT
MEDIUM	dvrl/main_corrupted_sample_discovery.py	16	"""Main experiment for corrupted sample discovery and robust learning.	STRING
MEDIUM	eli5_retrieval_large_lm/utils.py	210	# Definitely unnecessary. (len(list(matches)) > 0 felt ugly.)	COMMENT
MEDIUM	…sion/experiments/language/architectures/transformer.py	166	# If we utilize a context, only the embeddings for the data need to be	COMMENT
MEDIUM	smerf/smerf/internal/baking.py	526	# TODO(duckworthd): Use pjitter_rays to leverage all devices.	COMMENT
LOW	mico/dm_control/dbc_agent.py	159	# covariance matrix, we can just use l2.	COMMENT
MEDIUM	hyperbolic/utils/train.py	43	"""Maps FLAGS to dictionnary in order to save it in json format."""	STRING
MEDIUM	weak_disentangle/tensorsketch/modules/base.py	271	# We leverage isinstance to properly handle edge-case where	COMMENT
MEDIUM	dp_posets/sensitivity_space_sampler_test.py	220	# `ground_set` is listed in reversed order to facilitate `order` and	COMMENT
LOW	pvn/offline.py	377	# If we don't have a mesh just use regular jit	COMMENT
LOW	pvn/offline.py	436	# If we don't have a mesh just use regular jit	COMMENT
MEDIUM	betum_tool/models/yolo26/scripts/parse_output.py	88	# Also add stripped stem for robust matching with weird spacing names	COMMENT
MEDIUM	betum_tool/models/owlv2/losses.py	153	# This logic is made robust to a potential off-by-one error in	COMMENT
LOW	smith/bert/modeling.py	485	# function, so we just return it.	COMMENT
MEDIUM	xirl/sac/wrappers.py	281	# like to use it in conjunction with the learned reward.	COMMENT
LOW	…g_prediction/eq_mag_prediction/ingestion/ingest_jma.py	100	# instead I3, 2X whatever that means. We just use the integer and ignore the	COMMENT
LOW	bam/bert/modeling.py	300	# function, so we just return it.	COMMENT
MEDIUM	mol_dqn/experimental/deep_q_networks_noise.py	187	# It will makes the optimization robust.	COMMENT
MEDIUM	mol_dqn/experimental/deep_q_networks_noise.py	524	# It will makes the optimization robust.	COMMENT
MEDIUM	mol_dqn/chemgraph/dqn/deep_q_networks.py	197	# It will makes the optimization robust.	COMMENT
MEDIUM	m_theory/dim4/so8_supergravity_extrema/code/algebra.py	355	# even in conjunction with high-accuracy numerics(!). However,	STRING
MEDIUM	m_theory/dim4/so8/src/dyonic.py	607	# We only resort to very robust methods for writing out data	COMMENT
MEDIUM	m_theory/dim1/papers/gamma_bth/gamma11.py	201	# We henceforth call the left spinor-index on Gamma^I_AB the "row-index",	COMMENT
MEDIUM	m_theory/m_theory_lib/algebra.py	519	# even in conjunction with high-accuracy numerics(!). However,	STRING
LOW	m_theory/m_theory_lib/m_util.py	1134	# there on. This breaks if we just return the cached vector -	COMMENT
MEDIUM	cnn_quantization/tf_cnn_benchmarks/benchmark_cnn.py	545	# NOTE: collective_all_reduce in conjunction with use_fp16 can	COMMENT
LOW	etcmodel/tensor_utils.py	62	# are statically known. Otherwise, just use -1.	COMMENT
LOW	etcmodel/tensor_utils.py	702	# function, so we just return it.	COMMENT
LOW	etcmodel/feature_utils.py	288	# We just use `make_segmented_att_mask` to constrain attention within unmasked	COMMENT
LOW	bisimulation_aaai2020/grid_world/grid_world.py	685	# Otherwise we just use the last evaluation metric.	COMMENT
MEDIUM	covid_epidemiology/src/constants.py	224	# static features pertaining to county-level models	COMMENT
LOW	quantile_regression/qr_lib_gasthaus.py	106	# Can't just use exclusive=True since we need L+1 elements.	COMMENT
MEDIUM	uflow/uflow_utils.py	621	"""The so-called robust loss used by DDFlow."""	STRING
LOW	widget_caption/widget_caption_input.py	37	# If indices is empty (no valid tokens/annotations), just use the index 0,	COMMENT
LOW	…pretability/experiments/saving_litm_interpretations.py	401	if not found: # just pass all instances through	CODE
LOW	video_structure/dynamics.py	379	# If we have only 1 sample, we can just return that:	COMMENT
LOW	mobilebert/run_squad.py	542	# "Japanese", we just use "Japanese" as the annotation. This is fairly rare	COMMENT
LOW	mobilebert/run_squad.py	942	# just create a nonce prediction in this case to avoid failure.	COMMENT
LOW	mobilebert/run_squad.py	1021	# can fail in certain cases in which case we just return `orig_text`.	COMMENT
LOW	mobilebert/modeling.py	430	# function, so we just return it.	COMMENT
LOW	protseq/protseq_analysis.py	153	# Sometimes files are empty, just return empty Counter.	COMMENT
204 more matches not shown…

Excessive Try-Catch Wrapping435 hits · 576 pts

Severity	File	Line	Snippet	Context
MEDIUM	compositional_rl/compwob/fields.py	35	def extractor(utterance):	CODE
MEDIUM	compositional_rl/compwob/fields.py	48	def get_field_extractor(task_name):	CODE
LOW	compositional_rl/compwob/fields.py	39	except Exception as exc:	CODE
LOW	compositional_rl/compwob/fields.py	2569	except Exception as e: # pylint: disable=broad-except	CODE
LOW	…ward_learning/semantic_parsing/nsm/executor_factory.py	581	except Exception as e:	CODE
LOW	…ward_learning/semantic_parsing/nsm/computer_factory.py	238	except Exception as e:	CODE
MEDIUM	…ward_learning/semantic_parsing/nsm/computer_factory.py	239	print('Error: ', e)	CODE
LOW	…ward_learning/semantic_parsing/nsm/computer_factory.py	303	except Exception as e:	CODE
LOW	meta_reward_learning/textworld/lib/helpers.py	159	except Exception as e:	CODE
MEDIUM	f_divergence_tests/test_two_samples.py	227	print('Error: Invalid JSON string for divergence parameters.')	CODE
LOW	table_rag/utils/execute.py	108	except Exception:	CODE
LOW	table_rag/utils/execute.py	119	except Exception as e:	CODE
LOW	table_rag/agent/model.py	99	except Exception as e:	CODE
LOW	table_rag/agent/rag_agent.py	39	except Exception as e:	CODE
LOW	table_rag/agent/rag_agent.py	67	except Exception as e:	CODE
MEDIUM	table_rag/agent/agent.py	167	print('Error: table is too large.')	CODE
LOW	stacked_capsule_autoencoders/eval_mnist_model.py	133	except Exception as err: # pylint: disable=broad-except	CODE
LOW	stacked_capsule_autoencoders/train.py	222	except Exception as err: # pylint: disable=broad-except	CODE
MEDIUM	…ope/airdialogue_model_transformer/generate_ope_data.py	226	print('Error IDs: ', errorids)	CODE
LOW	dialogue_ope/airdialogue_ope/modeling/utils.py	143	except Exception:	CODE
MEDIUM	dialogue_ope/airdialogue_ope/data/convai2/eval.py	162	print('Error IDs: ', errorids)	CODE
LOW	…ssion/compression_lib/examples/cifar10/cifar10_eval.py	122	except Exception as e: # pylint: disable=broad-except	CODE
LOW	TimesX/dataset_agent/orchestrator.py	439	except Exception as e:	CODE
LOW	TimesX/dataset_agent/orchestrator.py	505	except Exception as e:	CODE
LOW	TimesX/dataset_agent/orchestrator.py	559	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	81	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	158	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	258	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	334	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	494	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	552	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	710	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	767	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	1077	except Exception as e:	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	1235	except Exception as e:	CODE
MEDIUM	TimesX/dataset_agent/modules/module_04_events.py	43	def _classify_customsearch_error(response):	CODE
LOW⚡	TimesX/dataset_agent/modules/module_04_events.py	46	except Exception:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	404	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	535	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	770	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1190	except Exception as crawl_error:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1212	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1391	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1612	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1774	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/module_04_events.py	1022	except Exception as e:	STRING
LOW	TimesX/dataset_agent/modules/task_runtime.py	101	except Exception:	CODE
LOW⚡	TimesX/dataset_agent/modules/module_01_trends.py	230	except Exception as e:	CODE
LOW⚡	TimesX/dataset_agent/modules/module_01_trends.py	293	except Exception as retry_error:	CODE
LOW	TimesX/dataset_agent/modules/module_01_trends.py	334	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/llm_retry_handler.py	121	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/llm_retry_handler.py	161	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/llm_retry_handler.py	219	except Exception as e:	CODE
LOW	TimesX/dataset_agent/modules/llm_retry_handler.py	259	except Exception as e:	CODE
LOW	…mesX/dataset_agent/modules/module_06_peak_discovery.py	160	except Exception as e:	CODE
LOW	…mesX/dataset_agent/modules/module_06_peak_discovery.py	254	except Exception as e:	CODE
LOW⚡	TimesX/dataset_agent/modules/evidence_cleaning.py	146	except Exception:	CODE
LOW⚡	TimesX/dataset_agent/modules/evidence_cleaning.py	156	except Exception as exc:	CODE
LOW	TimesX/dataset_agent/modules/llm_handler.py	134	except Exception as e:	STRING
LOW	TimesX/dataset_agent/modules/llm_handler.py	338	except Exception as e:	CODE
375 more matches not shown…

Cross-Language Confusion80 hits · 405 pts

Severity	File	Line	Snippet	Context
HIGH	jaxraytrace/vector.py	77	return self / self.length()	CODE
HIGH	ebp/ebp/common/cmd_args.py	54	help='type for gradient norm (lp1 \|\| norm2)')	CODE
HIGH	ebp/ebp/common/cmd_args.py	117	help='type for flows (planar \|\| ires)')	CODE
HIGH	ebp/ebp/common/cmd_args.py	122	help='form of flows (param \|\| hyper)')	CODE
HIGH	ebp/ebp/common/cmd_args.py	214	'-net_type', type=str, default='mlp', help='type for vae (cnn \|\| mlp)')	CODE
HIGH	TimesX/dataset_agent/modules/llm_handler.py	233	"content_date": null,	CODE
HIGH	TimesX/dataset_agent/modules/llm_handler.py	254	"content_date": null,	CODE
HIGH	study_recommend/utils/input_pipeline_utils.py	246	# If either value is undefined, put the student in their own classroom	COMMENT
HIGH	neutra/ebm/train_ebm.py	198	"""KL[P \|\| Q].	STRING
HIGH	neutra/ebm/train_ebm.py	220	"""KL[Q \|\| U].	STRING
HIGH	neutra/ebm/train_ebm.py	244	"""KL[Q \|\| U].	STRING
HIGH	neutra/ebm/train_ebm.py	268	"""alpha KL[Q \|\| U] + beta KL[data \|\| Q].	STRING
HIGH	neutra/ebm/train_ebm.py	320	"""KL[data \|\| Q].	STRING
HIGH	linear_dynamical_systems/experiments.py	78	'is comma separated. E.g. `0.9,0.1 0.5,0.1`. When null, generate random '	STRING
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	42	(dnf_lib.Clause(3, 2, False, False), '(x_2 \|\| x_3)'),	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	45	(dnf_lib.Clause(4, 5, True, False), '(!x_4 \|\| x_5)'),	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	189	self.assertIn('(x_0 \|\| x_2)', str(dnf))	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	271	('(x_32 \|\| x_0)', dnf_lib.Clause(0, 32, False, False)),	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	273	('(!x_11 \|\| x_12)', dnf_lib.Clause(11, 12, True, False)),	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	284	('x_0 \|\| x_1)'),	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	285	('x_0 \|\| x_1'),	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	286	('(!!x_3 \|\| x_5)'),	CODE
HIGH⚡	bangbang_qaoa/two_sat/dnf_lib_test.py	287	('(!x_3 \|\| x_4 \|\| x_5)')	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	306	'Number of Literals: 24, DNF: (!x_0 \|\| x_1)',	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	310	'Number of Literals: 5, DNF:(x_2 \|\| x_4) && (x_3 \|\| !x_1)',	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib_test.py	322	('Number of Literals: 5, DNF: (x_0 \|\| x_1) && ')	CODE
HIGH	bangbang_qaoa/two_sat/dnf_lib.py	102	An example would be: (!x_0 \|\| x_5)	STRING
HIGH	etcmodel/layers/recompute_grad.py	47	return _context_stack.push(self)	CODE
HIGH	etcmodel/models/wikihop/data_utils.py	118	max_heap.push((index, num_sentences))	CODE
HIGH	etcmodel/models/wikihop/data_utils.py	211	max_heap.push((index, num_sentences if num_sentences > 0 else 0))	CODE
HIGH	covid_epidemiology/src/feature_preprocessing.py	110	for each location will be set to this value if it is null.	STRING
HIGH	covid_epidemiology/src/feature_preprocessing.py	145	for each location will be set to this value if it is null.	STRING
HIGH	…iology/src/models/definitions/base_model_definition.py	863	value for each location will be set to this value if it is null.	STRING
HIGH	ipagnn/lib/setup.py	98	same_config = config_utils.equals(config.model, original_config.model)	CODE
HIGH	ipagnn/lib/setup.py	110	same_config = config_utils.equals(config.dataset, original_config.dataset)	CODE
HIGH⚡	ipagnn/lib/config_utils_test.py	44	self.assertTrue(config_utils.equals(config, restored_config))	CODE
HIGH⚡	ipagnn/lib/config_utils_test.py	47	self.assertFalse(config_utils.equals(config, restored_config))	CODE
HIGH⚡	ipagnn/lib/config_utils_test.py	56	self.assertTrue(config_utils.equals(config, restored_config))	CODE
HIGH⚡	graph_sampler/graph_sampler/graph_sampler.py	220	self._num_graphs_stats.push(importance * weight)	CODE
HIGH⚡	graph_sampler/graph_sampler/graph_sampler.py	221	self._importance_stats.push(importance)	CODE
HIGH⚡	graph_sampler/graph_sampler/graph_sampler.py	222	self._weight_stats.push(weight)	CODE
HIGH	symbolic_functionals/syfes/dataset/dataset.py	478	if not pd.DataFrame.equals(	CODE
HIGH	readtwice/layers/recompute_grad.py	47	return _context_stack.push(self)	CODE
HIGH	dpsgd_batch_sampler_accounting/balls_and_bins.py	351	The hockey stick divergence D_{e^eps}(P \|\| Q) is given by	STRING
HIGH	dpsgd_batch_sampler_accounting/monte_carlo_estimator.py	78	"""Returns the smallest p s.t. KL(q \|\| p) >= kl_bound or 1 if none exists."""	STRING
HIGH⚡	dpsgd_batch_sampler_accounting/monte_carlo_estimator.py	161	Then for `p` such that KL(q/C \|\| p/C) * n >= log(1 / error_prob), we have	STRING
HIGH⚡	dpsgd_batch_sampler_accounting/monte_carlo_estimator.py	167	Pr[(X_1 + ... + X_n) / n <= q] <= exp(-KL(q \|\| m) n).	STRING
HIGH⚡	dpsgd_batch_sampler_accounting/monte_carlo_estimator.py	169	such that KL(q \|\| m) > KL(q \|\| p) >= log(1 / error_prob) / n.	STRING
HIGH	correct_batch_effects_wdn/io_utils_test.py	47	self.assertTrue(actual.equals(df))	CODE
HIGH	…nnotate_protein_universe/hmm_blast_baselines/phmmer.py	74	# Here we discard the normal stdout of phmmer with -o /dev/null, as we don't	STRING
HIGH	camp_zipnerf/tests/render_test.py	113	basis = jnp.linalg.svd(null)[0][:, :2]	CODE
HIGH	camp_zipnerf/internal/math.py	66	"""Make plus_eps()'s gradient a no-op (nextafter's gradient is undefined)."""	STRING
HIGH	camp_zipnerf/internal/math.py	72	"""Make minus_eps()'s gradient a no-op (nextafter's gradient is undefined)."""	STRING
HIGH	aptamers_mlpd/util/selection.py	404	If template_sequence is undefined, generates a sane default.	STRING
HIGH	aptamers_mlpd/simulation/pool.py	370	return (self.aptamers.equals(other.aptamers)	CODE
HIGH	yobo/multiscope_renderer.py	445	self.spl.push(self.get_kf())	CODE
HIGH	yobo/internal/math.py	67	"""Make plus_eps()'s gradient a no-op (nextafter's gradient is undefined)."""	STRING
HIGH	yobo/internal/math.py	73	"""Make minus_eps()'s gradient a no-op (nextafter's gradient is undefined)."""	STRING
HIGH	…guided_symbolic_regression/utils/postprocessor_test.py	275	stack.push('x')	CODE
HIGH⚡	lighthouse/data_loader.py	106	self.timestamp, [0], [self.length()], strides=[stride]),	CODE
20 more matches not shown…

Redundant / Tautological Comments201 hits · 293 pts

Severity	File	Line	Snippet	Context
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	492	# Check if the utterance mentions any phrases that are semantically same as	COMMENT
LOW	compositional_rl/gwob/CoDE/web_environment.py	204	page) not in selected_designs: # Check if design is duplicate.	CODE
LOW	gfsa/schema_util.py	52	# Check if the list of edges with this type exists and is non-empty	COMMENT
LOW	gfsa/automaton_builder_test.py	425	# Set another to sum to less than 1.	COMMENT
LOW	psycholab/game.py	507	# Check if no wall or (unpassable + unpushable) object:	COMMENT
LOW	psycholab/game.py	558	# Check if it is an unpassable/unpushable player who stays:	COMMENT
LOW	imp/max/optimization/objectives.py	902	# Check if the objective modalities exist in the common space	COMMENT
LOW	imp/max/utils/sharding.py	153	# Check if this sequence has valid members	COMMENT
LOW	imp/max/utils/sharding.py	159	# Check if a member of the sequence is a valid sharding super-axis.	COMMENT
LOW	imp/max/modeling/garden/imp.py	1148	# Check if the dataflow exists in the inputdata	COMMENT
LOW	imp/max/modeling/garden/imp.py	2138	# Check if the dataflow exists in the inputdata	COMMENT
LOW	imp/max/execution/executors.py	252	# Check if the leaf-of-interest is scalar or non-scalar	COMMENT
LOW	imp/max/execution/checkpointing.py	563	# Check if the shapes of the array on disk match the expected shape based	COMMENT
LOW	imp/max/evaluation/evaluators.py	166	# Check if the leaf-of-interest is scalar or non-scalar	COMMENT
LOW	zebra_puzzle_generator/zebra_solver.py	344	# Check if any entity has only one possible value left	COMMENT
LOW	zebra_puzzle_generator/zebra_puzzle_generator.py	459	# Check if puzzle is solvable.	COMMENT
LOW	table_rag/utils/utils.py	130	# Check if the markdown string is empty or only contains the header and delimiter	COMMENT
LOW	table_rag/utils/utils.py	134	# Check if the markdown string contains the correct delimiter for a table	COMMENT
LOW	TimesX/dataset_agent/orchestrator.py	246	# Check if any time blocks for this keyword need processing	COMMENT
LOW⚡	TimesX/dataset_agent/modules/module_01_trends.py	236	# Check if this is a rate limit error and we haven't switched to robust mode yet	COMMENT
LOW⚡	TimesX/dataset_agent/modules/module_01_trends.py	303	# Check if we have any successful data	COMMENT
LOW	smu/parser/smu_writer_lib.py	2421	# Check if the modified lines match the original.	COMMENT
LOW	graphqa/graph_task.py	434	# Check if these are not integers, sort	COMMENT
LOW	kl_guided_sampling/decoding.py	509	# Check if the next token is padding (a target) or non-padding (an input).	COMMENT
LOW	data_selection/wmt/input_pipeline.py	742	# Iterate through dataset and write to memory	COMMENT
LOW	…mples/research_projects/summarization/ppo_summ_rlhf.py	179	# Check if the number is smaller than the smallest value in quantiles	COMMENT
LOW	…mples/research_projects/summarization/ppo_summ_rlhf.py	182	# Check if the number is greater than the largest value in quantiles	COMMENT
LOW	…c/llm-intrinsic-reward/trl/extras/summ_reward_model.py	91	# Check if there is any padding otherwise take length of sequence	COMMENT
LOW	polysketchformer/polynomial_attention.py	50	assert query.shape[-1] == key.shape[-1] # Check if it supports dot products	CODE
LOW	polysketchformer/polynomial_attention.py	51	assert key.shape[-2] == value.shape[-2] # Check if num_keys match num_values	CODE
LOW	experience_replay/run_experience_replay_experiment.py	120	# Check if checkpoint exists. Note that the existence of checkpoint 0 means	COMMENT
LOW⚡	summae/model_test.py	308	# Check if it's unique class ID for each permutation.	COMMENT
LOW	summae/text_encoder_test.py	144	max_subtoken_length = 10 # Set this to `None` to get problems.	CODE
LOW	felix/example_builder_for_felix_insert.py	68	# Check if the labels(_mask) is None or an empty list.	COMMENT
LOW	recs_ecosystem_creator_rl/environment/environment.py	211	# Check if reaches a terminal state and return.	COMMENT
LOW	eli5_retrieval_large_lm/check_flags.py	39	# Verify if all m_base_pat matches overlap partially with at least one	COMMENT
LOW	eli5_retrieval_large_lm/utils.py	208	# Check if the prefix path FLAGS.source_embeddings_prefix has at least one	COMMENT
LOW	sd_gym/env.py	147	# Set type to float if unit has '/' or 'per ' in it (inferring division),	COMMENT
LOW	sd_gym/util.py	83	# Check if it is observable	COMMENT
LOW	sd_gym/util.py	89	# Check if it is actionable	COMMENT
LOW	jaxsel/_src/train_utils.py	51	# Check if a datapoint in the batch matches the label	COMMENT
LOW	jaxsel/examples/utils/data.py	175	# Set thresh to .5 by leveraging the image discretization.	COMMENT
LOW	smerf/smerf/internal/grid_utils.py	541	# Assign sm_idxs to each query position.	COMMENT
LOW	smerf/smerf/internal/grid_utils.py	613	# Assign sm_idxs to each query position.	COMMENT
LOW	smerf/webviewer/launch_webserver_utils.sh	46	# Check if this command exists	COMMENT
LOW	smerf/webviewer/launch_webserver_utils.sh	66	# Check if this command exists	COMMENT
LOW	weak_disentangle/main.py	245	# Check if we're resuming training if not in debugging mode	COMMENT
LOW	…ext_aware_transliteration/transformer/data_pipeline.py	246	# Read files and interleave results. When training, the order of the examples	COMMENT
LOW	compositional_classification/scripts/cfq_parse_util.py	303	# Assign indices to the structure tokens of constituency parsing	COMMENT
LOW	pvn/state.py	263	# Check if the directory is empty, Orbax could have failed to save	COMMENT
LOW	betum_tool/models/diffusiondet/scripts/parse_output.py	152	# Check if it's already formatted as COCO format or needs conversion	COMMENT
LOW	betum_tool/models/owlv2/tests/losses_test.py	128	# Check if it computes without crash.	COMMENT
LOW	xirl/utils.py	160	# Check if the env is in x-magical.	COMMENT
LOW	xirl/base_configs/rl.py	38	# Set this to True to allow CUDA to find the best convolutional algorithm to	COMMENT
LOW	…object_detection/balanced_positive_negative_sampler.py	153	# Check if indicator and labels have a static size.	COMMENT
LOW	pse/jumping_task/evaluation_helpers.py	132	# Loop over data dimensions and create text annotations.	COMMENT
LOW	assessment_plan_modeling/ap_parsing/data_lib.py	542	# Check if labeled span is contained in section:	COMMENT
LOW	resolve_ref_exp_elements_ml/eval.py	99	# Check if the elements selected are part of the ground truth bounding box	COMMENT
LOW	ramsey_number_bounds/code/ramsey_4_19_213.py	482	# Check if this is a new global best or an improved S for this N	COMMENT
LOW	ramsey_number_bounds/code/ramsey_4_20_234.py	948	# Check if a better graph (in terms of the overall goal) was found in g2	COMMENT
141 more matches not shown…

Modern AI Meta-Vocabulary65 hits · 216 pts

Severity	File	Line	Snippet	Context
MEDIUM	imp/max/evaluation/evaluators.py	833	# Initialize the zero-shot classifier.	COMMENT
MEDIUM	imp/max/evaluation/evaluators.py	1088	# perform zero-shot probing	COMMENT
MEDIUM	imp/max/evaluation/evaluators.py	1157	# perform zero-shot probing	COMMENT
MEDIUM	graphqa/graph_task_generator.py	247	# Loading few-shot graphs.	COMMENT
MEDIUM	state_of_sparsity/sparse_rn50/imagenet_train_eval.py	490	# define a custom scaffold function to enable initializing the mask from an	COMMENT
MEDIUM	mol_dqn/experimental/multi_obj_opt.py	159	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/experimental/multi_obj_gen.py	65	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/experimental/multi_obj_gen.py	96	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/experimental/multi_obj.py	63	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/experimental/multi_obj.py	94	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/chemgraph/multi_obj_opt.py	107	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/chemgraph/dqn/run_dqn.py	160	# if the current molecule does not contain the scaffold of the target,	COMMENT
MEDIUM	mol_dqn/chemgraph/dqn/py/molecules_test.py	42	# Note that the carbonyl is included in the scaffold...	COMMENT
MEDIUM	resolve_ref_exp_elements_ml/elements_embeddings.py	605	# Text model refers to embedding model for sentences	COMMENT
MEDIUM	scaling_transformer_inference_efficiency/attention.py	315	# smaller batch size earlier in the sequence: for example, during few-shot	COMMENT
MEDIUM	scaling_transformer_inference_efficiency/attention.py	316	# prompting, the few-shot examples typically have batch size 1, whereas the	COMMENT
MEDIUM	social_rl/multiagent_tfagents/multiagent_ppo.py	45	# Specific to multi-agent case	COMMENT
MEDIUM	social_rl/multiagent_tfagents/multiagent_ppo_policy.py	103	# Make multi-agent policy_state spec	COMMENT
MEDIUM	social_rl/multiagent_tfagents/multiagent_ppo_policy.py	131	# Make multi-agent info spec	COMMENT
MEDIUM	social_rl/multiagent_tfagents/multiagent_ppo_policy.py	276	# Stack actions into multi-agent action	COMMENT
MEDIUM	social_rl/multiagent_tfagents/joint_attention/README.md	1	# Joint attention extension to multi-agent tf-agents	COMMENT
MEDIUM	…agent_tfagents/joint_attention/attention_ppo_policy.py	111	# Make multi-agent info spec	COMMENT
MEDIUM	distribution_embedding_networks/simulation.py	196	# We first create the embedding model	COMMENT
MEDIUM	polish/ppo/ppo_model_fn.py	551	# Setup fine tune scaffold	COMMENT
MEDIUM	polish/ppo/ppo_model_fn.py	552	# The scaffold here is used to restore the weights from _warmstart_file.	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_7.py	590	# Filter augmented_locations_df to only 'State' region_type for the base scaffold	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_7.py	608	# Create base scaffold for all (observation_date, location) combinations	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	191	# ii. Create a scaffold of all `(target_end_date, location)` combinations within this range, merging `population`	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	192	# iii. Merge `df_full_history`'s `target_end_date`, `location`, `TARGET_STR_LOG`, `unweighted_ili`, `national_ili	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	193	# iv. For any NaNs in `unweighted_ili`, `national_ili`, `hhs_ili` in the scaffold, impute them using the seasonal	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	194	# v. For any NaNs in `TARGET_STR_LOG` in the scaffold (e.g., dates before `df_full_history` or in the future test	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	195	# vi. Set `(target_end_date, location)` as the index for the scaffold and convert relevant columns (`TARGET_STR_L	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	980	# NEW: Add sin_week and cos_week to lookup scaffold for transformation	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	988	# Merge df_full_history onto the scaffold to get actual/synthetic values	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	1003	# Merge seasonal averages onto the scaffold for imputation	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_3.py	1057	# First, ensure transformation params are available on the scaffold	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_8.py	434	# Create an empty scaffold for all historical data	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_8.py	441	# Add population data to the full historical scaffold	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_8.py	826	# Initialize prediction_df_state with the full history and future scaffold	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Hybrid_3.py	1321	# Create a scaffold for test features, initially with NaN for dynamic features	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_10.py	521	# Create a scaffold for all location-date combinations for ILI history	COMMENT
MEDIUM⚡	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_10.py	527	# Merge state-level ILI onto the scaffold	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_10.py	842	# Now, extend the combined_tracker (DataFrame itself) with the test scaffold for recursive updates.	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_10.py	846	# Combine historical tracker data with future scaffold	COMMENT
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Novel_6.py	158	) # create features for test_x scaffold	CODE
MEDIUM	epi_forecasts/flu_hub/model_py/Google_SAI-Adapted_5.py	118	# 7. `fit_and_predict_fn` orchestration:	COMMENT
MEDIUM	epi_forecasts/covid_hub/model_py/Google_SAI-Hybrid_1.py	164	# Return necessary columns including the original 'population' for consistency in scaffold processing	COMMENT
MEDIUM	COSTAR/config/config.yaml	21	few_shot_sample_num: -1 # when > 0, resample generated training samples to make the dataset few-shot	CODE
MEDIUM	COSTAR/config/config.yaml	29	# few_shot_sample_num: -1 # when > 0, resample generated training samples to make the dataset few-shot	COMMENT
MEDIUM	COSTAR/scripts_release/baselines.sh	20	## zero-shot transfer	COMMENT
MEDIUM	COSTAR/scripts_release/baselines.sh	53	# semi-synthetic MIMIC-III (run zero-shot transfer experiments first)	COMMENT
MEDIUM	COSTAR/scripts_release/baselines.sh	54	## zero-shot transfer	COMMENT
MEDIUM	COSTAR/scripts_release/baselines.sh	103	# M5 (run zero-shot transfer experiments first)	COMMENT
MEDIUM	COSTAR/scripts_release/baselines.sh	104	## zero-shot transfer	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	2	## zero-shot transfer/data-efficient transfer/standard supervised learning	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	3	## zero-shot transfer metrics: dst-zero-shot-encoder_test_rmse_last, dst-zero-shot-decoder_test_rmse_[2-6]-step	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	8	# semi-synthetic MIMIC-III (run zero-shot transfer/data-efficient transfer experiments first)	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	9	## zero-shot transfer/data-efficient transfer	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	10	## zero-shot transfer metrics: dst-zero-shot-encoder_test_rmse_last, dst-zero-shot-decoder_test_rmse_[2-6]-step	COMMENT
MEDIUM⚡	COSTAR/scripts_release/costar.sh	17	# M5 (run zero-shot transfer/data-efficient transfer experiments first)	COMMENT
5 more matches not shown…

Structural Annotation Overuse89 hits · 160 pts

Severity	File	Line	Snippet	Context
LOW⚡	ledge/ledge.py	379	# Step 3: Run the net once for each pass to compute the commands and	COMMENT
LOW⚡	ledge/ledge.py	385	# Step 4: Apply the computed commands to the bases.	COMMENT
LOW⚡	ledge/ledge.py	389	# Step 5: Optimize the parameters to fit the bases to the target_func.	COMMENT
LOW	ara_optimization/synthetic_dataset.py	306	# Step 2: Generate conversions for each impression.	COMMENT
LOW	ara_optimization/synthetic_dataset.py	381	# Step 1: Generate impression side distribution.	COMMENT
LOW	ml_debiaser/reduce_to_binary.py	111	# Step 1: debias each label separately.	COMMENT
LOW	ml_debiaser/reduce_to_binary.py	124	# Step 2: update ADMM variables.	COMMENT
LOW⚡	hmc_swindles/utils.py	314	# Step 1: mask = [False, False, True, False]	COMMENT
LOW⚡	hmc_swindles/utils.py	316	# Step 2: mask = [0, 0, 1, 1]	COMMENT
LOW⚡	hmc_swindles/utils.py	318	# Step 3: mask = [0, 0, 1, 2]	COMMENT
LOW⚡	hmc_swindles/utils.py	320	# Step 4: mask = [1, 1, 0, 0]	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	65	# Step 1: Load the model	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	86	# Step 2: Load the dataset and pre-process it	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	139	# Step 3: Define the training arguments	COMMENT
LOW⚡	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	155	# Step 4: Define the LoraConfig	COMMENT
LOW⚡	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	161	# Step 5: Define the Trainer	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	75	# Step 1: Load the model	COMMENT
LOW⚡	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	99	# Step 2: Load the dataset	COMMENT
LOW⚡	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	102	# Step 3: Define the training arguments	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	118	# Step 4: Define the LoraConfig	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	129	# Step 5: Define the Trainer	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	141	# Step 6: Save the model	COMMENT
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	186	# Step 0: check positional arguments validity	STRING
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	197	# Step 1: Initialize Accelerator	STRING
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	272	# Step 3: Initialize optimizer and data collator	STRING
LOW⚡	neutra/utils.py	578	# Step 1: mask = [False, False, True, False]	COMMENT
LOW⚡	neutra/utils.py	580	# Step 2: mask = [0, 0, 1, 1]	COMMENT
LOW⚡	neutra/utils.py	582	# Step 3: mask = [0, 0, 1, 2]	COMMENT
LOW⚡	neutra/utils.py	584	# Step 4: mask = [1, 1, 0, 0]	COMMENT
LOW	drops/drops_test_time.py	525	# Step 2: Update softmaxed of logits get model prediction (post-shift)	COMMENT
LOW	drops/drops_test_time.py	536	# Step 3: Calculate L_y (per class loss), L is the 0-1 loss	COMMENT
LOW	drops/drops_test_time.py	561	# Step 4: Get the Lagrangian constraint term	COMMENT
LOW⚡	drops/drops_test_time.py	582	# Step 5: Get the Lagrangian (with L_y list of size K)	COMMENT
LOW⚡	drops/drops_test_time.py	587	# Step 6: EG update on g_y	COMMENT
LOW⚡	drops/drops_test_time.py	615	# Step 7: EG update on lambda	COMMENT
LOW⚡	drops/drops_test_time.py	618	# Step 8: Update alpha_y	COMMENT
LOW	drops/main_lt.py	526	# Step 1: Prepare w_y (optional--for ce loss)	COMMENT
LOW⚡	drops/main_lt.py	541	# Step 2: Update softmaxed of logits get model prediction (post-shift)	COMMENT
LOW⚡	drops/main_lt.py	551	# Step 3: Calculate L_y (per class loss), L is the 0-1 loss	COMMENT
LOW	drops/main_lt.py	576	# Step 4: Get the Lagrangian constraint term	COMMENT
LOW⚡	drops/main_lt.py	595	# Step 5: Get the Lagrangian (with L_y list of size K)	COMMENT
LOW⚡	drops/main_lt.py	600	# Step 6: EG update on g_y	COMMENT
LOW⚡	drops/main_lt.py	621	# Step 7: EG update on lambda	COMMENT
LOW⚡	drops/main_lt.py	624	# Step 8: Update alpha_y	COMMENT
LOW	…quantization/tf_cnn_benchmarks/all_reduce_benchmark.py	113	# Step 1: Do the aggregation.	COMMENT
LOW	OpenMSD/README.md	17	## Step 1: Download data	COMMENT
LOW	OpenMSD/README.md	35	## Step 2: Get papers	COMMENT
LOW	OpenMSD/README.md	51	## Step 3: Get Citation, Co-Citation and Bibliographic-Coupling pairs	COMMENT
LOW	speculative_kd/transformers/utils.py	3020	# IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memory	STRING
LOW	speculative_kd/transformers/utils.py	3339	# IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memory	STRING
LOW	speculative_kd/transformers/utils.py	3578	# IMPORTANT: Note that this should appear BEFORE the call to _reorder_cache() to save the maximum memory	STRING
LOW	tft/run.sh	28	# Step 1: Setup environment.	COMMENT
LOW⚡	tft/run.sh	41	# Step 2: Downloads data if not present.	COMMENT
LOW⚡	tft/run.sh	45	# Step 3: Train & Test	COMMENT
LOW	tft/README.md	30	### Step 1: Download data for default experiments	COMMENT
LOW	tft/README.md	37	### Step 2: Train and evaluate network	COMMENT
LOW	tft/README.md	53	### Step 1: Implement custom data formatter	COMMENT
LOW	tft/README.md	56	### Step 2: Update configs.py	COMMENT
LOW	tft/README.md	111	### Step 3: Run training script	COMMENT
LOW⚡	contrack/model.py	521	# Step 1: Concatenate input data into a single sequence	COMMENT
29 more matches not shown…

Fake / Example Data117 hits · 147 pts

Severity	File	Line	Snippet	Context
LOW	compositional_rl/integrate_miniwob.py	60	" self._placeholder = raw_dom.get('placeholder')\n"	CODE
LOW	compositional_rl/gwob/gminiwob/env-design.js	594	'Lorem ipsum dolor sit amet, consectetur adipisicing elit. Amet numquam aspernatur!'	CODE
LOW	compositional_rl/gwob/gminiwob/env-design.js	594	'Lorem ipsum dolor sit amet, consectetur adipisicing elit. Amet numquam aspernatur!'	CODE
LOW⚡	sparse_mixers/train_utils_test.py	120	dummy_data = jax.random.randint(	CODE
LOW⚡	sparse_mixers/train_utils_test.py	122	return {"a": dummy_data, "b": dummy_data}	CODE
LOW	smerf/smerf/internal/baked_render.py	305	# Therefore we want to eliminate case B and append M "placeholder" hits to	COMMENT
LOW⚡	betum_tool/tests/data_test.py	34	dummy_data = {"images": [{"id": 1, "file_name": "img1.jpg"}]}	CODE
LOW⚡	betum_tool/tests/data_test.py	36	json.dump(dummy_data, f)	CODE
LOW⚡	betum_tool/tests/data_test.py	39	self.assertEqual(result, dummy_data)	CODE
LOW⚡	…ediction/eq_mag_prediction/forecasting/metrics_test.py	753	fake_data = np.arange(0.5, 9.5, 1)	CODE
LOW⚡	…ediction/eq_mag_prediction/forecasting/metrics_test.py	762	data_pool=fake_data,	CODE
LOW⚡	…ediction/eq_mag_prediction/forecasting/metrics_test.py	770	data_pool=fake_data,	CODE
LOW⚡	…ediction/eq_mag_prediction/forecasting/metrics_test.py	778	data_pool=fake_data,	CODE
LOW⚡	…ediction/eq_mag_prediction/forecasting/metrics_test.py	786	data_pool=fake_data,	CODE
LOW⚡	semantic_routing/benchmark/datasets/touring_dataset.py	275	fake_data = datapoint["query_data"].copy()	CODE
LOW⚡	semantic_routing/benchmark/datasets/touring_dataset.py	276	if "time_budget" not in fake_data:	CODE
LOW⚡	semantic_routing/benchmark/datasets/touring_dataset.py	277	fake_data["time_budget"] = 10000000	CODE
LOW⚡	semantic_routing/benchmark/datasets/touring_dataset.py	279	fake_data, datapoint["end"], edgelist	CODE
LOW	d3pm/text/diffusion.py	2490	fake_key = jrandom.PRNGKey(0)	CODE
LOW	d3pm/text/diffusion.py	2492	key=fake_key,	CODE
LOW	…d/data_processing/xmile_parser/bindings/xmile_style.py	169	"name": "placeholder",	CODE
LOW	…_processing/xmile_parser/bindings/xmile_placeholder.py	27	name = "placeholder"	CODE
LOW	…benchmark/eval_embedding/sklearn/sklearn_utils_test.py	47	fake_data = [	CODE
LOW⚡	…benchmark/eval_embedding/sklearn/sklearn_utils_test.py	67	for emb, label_index in fake_data:	CODE
LOW⚡	…benchmark/eval_embedding/sklearn/sklearn_utils_test.py	77	expected_embs = np.array([d[0] for d in fake_data], np.float32)	CODE
LOW⚡	Uboreshaji_Modeli/tests/data_test.py	36	dummy_data = {"images": [{"id": 1, "file_name": "img1.jpg"}]}	CODE
LOW⚡	Uboreshaji_Modeli/tests/data_test.py	38	json.dump(dummy_data, f)	CODE
LOW⚡	Uboreshaji_Modeli/tests/data_test.py	41	self.assertEqual(result, dummy_data)	CODE
LOW	uq_benchmark_2019/mnist/data_lib.py	107	def build_dataset(opts, fake_data=False):	CODE
LOW	uq_benchmark_2019/mnist/data_lib.py	112	if fake_data:	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment_test.py	32	flags.DEFINE_bool('fake_data', True, 'Whether to use fake dataset data.')	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment_test.py	46	if not flags.FLAGS.fake_data:	CODE
LOW	uq_benchmark_2019/mnist/experiment.py	41	fake_data=test_level > 1,	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment.py	58	fake_data = test_level > 1	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment.py	65	dataset_train = data_lib.build_dataset(data_opts_list[0], fake_data=fake_data)	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment.py	66	dataset_eval = data_lib.build_dataset(data_opts_list[1], fake_data=fake_data)	CODE
LOW⚡	uq_benchmark_2019/mnist/experiment.py	73	dataset = data_lib.build_dataset(data_opts, fake_data=fake_data)	CODE
LOW⚡	uq_benchmark_2019/mnist/hparams_lib.py	50	fake_data=False, fake_training=False):	CODE
LOW⚡	uq_benchmark_2019/mnist/hparams_lib.py	53	fake_data=fake_data,	CODE
LOW⚡	uq_benchmark_2019/mnist/hparams_lib.py	58	fake_data=False, fake_training=False):	CODE
LOW⚡	uq_benchmark_2019/mnist/hparams_lib.py	60	num_train_examples = (data_lib.DUMMY_DATA_SIZE if fake_data else	CODE
LOW	uq_benchmark_2019/imagenet/end_to_end_test.py	43	flags.DEFINE_bool('fake_data', True, 'Use dummy random data.')	CODE
LOW⚡	uq_benchmark_2019/imagenet/end_to_end_test.py	57	if flags.FLAGS.fake_data and (data_name != 'test'):	CODE
LOW⚡	uq_benchmark_2019/imagenet/end_to_end_test.py	63	metrics=metrics, fake_data=flags.FLAGS.fake_data,	CODE
LOW⚡	uq_benchmark_2019/imagenet/end_to_end_test.py	69	fake_data=flags.FLAGS.fake_data)	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib.py	57	config, batch_size, is_training=False, fake_data=False, use_bfloat16=False):	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib.py	65	fake_data: If True, use randomly generated data.	STRING
LOW⚡	uq_benchmark_2019/imagenet/data_lib.py	70	if fake_data:	CODE
LOW	uq_benchmark_2019/imagenet/run_predict.py	55	max_examples, output_dir, fake_data=False):	CODE
LOW	uq_benchmark_2019/imagenet/run_predict.py	59	dataset = data_lib.build_dataset(data_config, batch_size, fake_data=fake_data)	CODE
LOW⚡	uq_benchmark_2019/imagenet/imagenet_input.py	58	use_bfloat16=False, fake_data=False):	CODE
LOW⚡	uq_benchmark_2019/imagenet/imagenet_input.py	67	fake_data: If True, use synthetic random data.	STRING
LOW⚡	uq_benchmark_2019/imagenet/imagenet_input.py	74	self.fake_data = fake_data	CODE
LOW	uq_benchmark_2019/imagenet/imagenet_input.py	122	if self.fake_data:	CODE
LOW	uq_benchmark_2019/imagenet/data_lib_test.py	30	flags.DEFINE_bool('fake_data', True, 'Bypass tests that rely on real data and '	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib_test.py	45	dataset = data_lib.build_dataset(config, BATCH_SIZE, fake_data=True)	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib_test.py	54	if not flags.FLAGS.fake_data:	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib_test.py	64	if not flags.FLAGS.fake_data:	CODE
LOW⚡	uq_benchmark_2019/imagenet/data_lib_test.py	73	if not flags.FLAGS.fake_data:	CODE
LOW	uq_benchmark_2019/imagenet/data_lib_test.py	89	if not flags.FLAGS.fake_data:	CODE
57 more matches not shown…

Verbosity Indicators72 hits · 129 pts

Severity	File	Line	Snippet	Context
LOW⚡	ledge/ledge.py	379	# Step 3: Run the net once for each pass to compute the commands and	COMMENT
LOW⚡	ledge/ledge.py	385	# Step 4: Apply the computed commands to the bases.	COMMENT
LOW⚡	ledge/ledge.py	389	# Step 5: Optimize the parameters to fit the bases to the target_func.	COMMENT
LOW	scrna_benchmark/dca_process.py	170	# We need to check if the file exists before creating it.	COMMENT
LOW	scrna_benchmark/scvi_process.py	204	# We need to check if the file exists before creating it.	COMMENT
LOW	schema_guided_dst/multiwoz/create_data_from_multiwoz.py	69	# we need to check if it is a correct match.	COMMENT
LOW	ara_optimization/synthetic_dataset.py	306	# Step 2: Generate conversions for each impression.	COMMENT
LOW	ara_optimization/synthetic_dataset.py	381	# Step 1: Generate impression side distribution.	COMMENT
LOW	ml_debiaser/reduce_to_binary.py	111	# Step 1: debias each label separately.	COMMENT
LOW	ml_debiaser/reduce_to_binary.py	124	# Step 2: update ADMM variables.	COMMENT
LOW⚡	hmc_swindles/utils.py	314	# Step 1: mask = [False, False, True, False]	COMMENT
LOW⚡	hmc_swindles/utils.py	316	# Step 2: mask = [0, 0, 1, 1]	COMMENT
LOW⚡	hmc_swindles/utils.py	318	# Step 3: mask = [0, 0, 1, 2]	COMMENT
LOW⚡	hmc_swindles/utils.py	320	# Step 4: mask = [1, 1, 0, 0]	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	65	# Step 1: Load the model	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	86	# Step 2: Load the dataset and pre-process it	COMMENT
LOW	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	139	# Step 3: Define the training arguments	COMMENT
LOW⚡	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	155	# Step 4: Define the LoraConfig	COMMENT
LOW⚡	…lm-intrinsic-reward/examples/scripts/reward_trainer.py	161	# Step 5: Define the Trainer	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	75	# Step 1: Load the model	COMMENT
LOW⚡	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	99	# Step 2: Load the dataset	COMMENT
LOW⚡	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	102	# Step 3: Define the training arguments	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	118	# Step 4: Define the LoraConfig	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	129	# Step 5: Define the Trainer	COMMENT
LOW	…c/llm-intrinsic-reward/examples/scripts/sft_trainer.py	141	# Step 6: Save the model	COMMENT
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	186	# Step 0: check positional arguments validity	STRING
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	197	# Step 1: Initialize Accelerator	STRING
LOW	relc/llm-intrinsic-reward/trl/trainer/ppo_trainer.py	272	# Step 3: Initialize optimizer and data collator	STRING
LOW⚡	neutra/utils.py	578	# Step 1: mask = [False, False, True, False]	COMMENT
LOW⚡	neutra/utils.py	580	# Step 2: mask = [0, 0, 1, 1]	COMMENT
LOW⚡	neutra/utils.py	582	# Step 3: mask = [0, 0, 1, 2]	COMMENT
LOW⚡	neutra/utils.py	584	# Step 4: mask = [1, 1, 0, 0]	COMMENT
LOW	vdvae_flax/optimizers.py	37	The purpose of this function is to prevent any optimisation to happen if the	STRING
LOW	drops/drops_test_time.py	525	# Step 2: Update softmaxed of logits get model prediction (post-shift)	COMMENT
LOW	drops/drops_test_time.py	536	# Step 3: Calculate L_y (per class loss), L is the 0-1 loss	COMMENT
LOW	drops/drops_test_time.py	561	# Step 4: Get the Lagrangian constraint term	COMMENT
LOW⚡	drops/drops_test_time.py	582	# Step 5: Get the Lagrangian (with L_y list of size K)	COMMENT
LOW⚡	drops/drops_test_time.py	587	# Step 6: EG update on g_y	COMMENT
LOW⚡	drops/drops_test_time.py	615	# Step 7: EG update on lambda	COMMENT
LOW⚡	drops/drops_test_time.py	618	# Step 8: Update alpha_y	COMMENT
LOW	drops/main_lt.py	526	# Step 1: Prepare w_y (optional--for ce loss)	COMMENT
LOW⚡	drops/main_lt.py	541	# Step 2: Update softmaxed of logits get model prediction (post-shift)	COMMENT
LOW⚡	drops/main_lt.py	551	# Step 3: Calculate L_y (per class loss), L is the 0-1 loss	COMMENT
LOW	drops/main_lt.py	576	# Step 4: Get the Lagrangian constraint term	COMMENT
LOW⚡	drops/main_lt.py	595	# Step 5: Get the Lagrangian (with L_y list of size K)	COMMENT
LOW⚡	drops/main_lt.py	600	# Step 6: EG update on g_y	COMMENT
LOW⚡	drops/main_lt.py	621	# Step 7: EG update on lambda	COMMENT
LOW⚡	drops/main_lt.py	624	# Step 8: Update alpha_y	COMMENT
LOW	…quantization/tf_cnn_benchmarks/all_reduce_benchmark.py	113	# Step 1: Do the aggregation.	COMMENT
LOW	etcmodel/models/hotpotqa/data_utils.py	176	the exact answer, 1895. The purpose of this function is to find such "better	STRING
LOW	correct_batch_effects_wdn/evaluate.py	292	The purpose of this function is to check whether batch effects have been	STRING
LOW	tft/run.sh	28	# Step 1: Setup environment.	COMMENT
LOW⚡	tft/run.sh	41	# Step 2: Downloads data if not present.	COMMENT
LOW⚡	tft/run.sh	45	# Step 3: Train & Test	COMMENT
LOW⚡	contrack/model.py	521	# Step 1: Concatenate input data into a single sequence	COMMENT
LOW⚡	contrack/model.py	524	# Step 2: Identify new entities.	COMMENT
LOW⚡	contrack/model.py	535	# Step 3: Compute enref ids for new entities	COMMENT
LOW⚡	contrack/model.py	539	# Step 4: Determine enref predictions	COMMENT
LOW⚡	contrack/model.py	542	# Step 5: Merge ids from new and existing enrefs	COMMENT
LOW	graph_temporal_ai/src/mpnn_cell.py	151	# Step 4: Normalize node features.	COMMENT
12 more matches not shown…

Modern Structural Boilerplate92 hits · 92 pts

Severity	File	Line	Snippet	Context
LOW	dialogue_ope/airdialogue_ope/airope_processors.py	38	logger = logging.getLogger(__name__)	CODE
LOW	dialogue_ope/airdialogue_ope/utils.py	42	logger = logging.getLogger(__name__)	CODE
LOW	dialogue_ope/airdialogue_ope/main.py	40	logger = logging.getLogger(__name__)	CODE
LOW	TimesX/dataset_agent/event_pipeline.py	36	logger = logging.getLogger(__name__)	CODE
LOW⚡	TimesX/dataset_agent/modules/module_04_events.py	40	logger = logging.getLogger(__name__)	CODE
LOW	…sX/dataset_agent/modules/module_07_cross_validation.py	22	logger = logging.getLogger(__name__)	CODE
LOW	TimesX/dataset_agent/modules/module_01_trends.py	28	logger = logging.getLogger(__name__)	CODE
LOW	TimesX/dataset_agent/modules/llm_retry_handler.py	25	logger = logging.getLogger(__name__)	CODE
LOW	…mesX/dataset_agent/modules/module_06_peak_discovery.py	30	logger = logging.getLogger(__name__)	CODE
LOW	TimesX/dataset_agent/modules/utils.py	19	logger = logging.getLogger(__name__)	CODE
LOW	TimesX/dataset_agent/modules/llm_handler.py	36	logger = logging.getLogger(__name__)	CODE
LOW	…mesX/dataset_agent/modules/module_05_initial_events.py	41	logger = logging.getLogger(__name__)	CODE
LOW	hmc_swindles/targets/probit_regression.py	36	__all__ = [	CODE
LOW	hmc_swindles/targets/target_spec.py	33	__all__ = [	CODE
LOW	hmc_swindles/targets/joint_distribution_posterior.py	29	__all__ = [	CODE
LOW	hmc_swindles/targets/__init__.py	37	__all__ = [	CODE
LOW	hmc_swindles/targets/item_response_theory.py	37	__all__ = [	CODE
LOW	hmc_swindles/targets/sparse_logistic_regression.py	36	__all__ = [	CODE
LOW	hmc_swindles/targets/neals_funnel.py	29	__all__ = [	CODE
LOW	hmc_swindles/targets/banana.py	29	__all__ = [	CODE
LOW	hmc_swindles/targets/logistic_regression.py	35	__all__ = [	CODE
LOW	hmc_swindles/targets/ill_conditioned_gaussian.py	33	__all__ = [	CODE
LOW	hmc_swindles/targets/data.py	37	__all__ = [	CODE
LOW	xirl/xirl/trainers/__init__.py	25	__all__ = [	CODE
LOW	xirl/xirl/evaluators/__init__.py	27	__all__ = [	CODE
LOW	…ects/mmdet3d_plugin/occformer/decode_heads/__init__.py	20	__all__ = [	CODE
LOW	…_ref_exp_elements_ml/deeplab/mobilenet/mobilenet_v2.py	184	__all__ = ['training_scope', 'mobilenet_base', 'mobilenet', 'V2_DEF']	CODE
LOW	etcmodel/models/hotpotqa/generate_tf_examples_lib.py	317	def set_paragraph_breakpoint(self, is_actual_paragraph: bool = False) -> None:	CODE
LOW	learning_to_clarify/act/src/act/utils/artifact_utils.py	26	logger = logging.getLogger(__name__)	CODE
LOW	…ning_to_clarify/act/src/act/models/generative_model.py	34	logger = logging.getLogger(__name__)	CODE
LOW	learning_to_clarify/act/src/act/scripts/run_act.py	53	logger = logging.getLogger(__name__)	CODE
LOW	learning_to_clarify/act/src/act/scripts/run_sft.py	46	logger = logging.getLogger(__name__)	CODE
LOW	…ng_to_clarify/act/src/act/data/preference_generator.py	26	logger = logging.getLogger(__name__)	CODE
LOW	jaxstronomy/psf_models.py	28	__all__ = ['Gaussian', 'Pixel']	CODE
LOW	jaxstronomy/lens_models.py	26	__all__ = ['EPL', 'NFW', 'Shear', 'TNFW']	CODE
LOW	jaxstronomy/source_models.py	25	__all__ = ['Interpol', 'SersicElliptic']	CODE
LOW	STraTA/selftraining.py	37	logger = logging.getLogger(__name__)	CODE
LOW	STraTA/finetuning.py	53	logger = logging.getLogger(__name__)	CODE
LOW	speculative_kd/train/train_sft.py	42	logger = logging.getLogger(__name__)	CODE
LOW	aptamers_mlpd/learning/train_feedforward.py	247	logger = logging.getLogger(__name__)	CODE
LOW	aptamers_mlpd/learning/dataset_stats.py	32	logger = logging.getLogger(__name__)	CODE
LOW	aptamers_mlpd/learning/eval_feedforward.py	49	logger = logging.getLogger(__name__)	CODE
LOW	cold_posterior_flax/cifar10/sample/__init__.py	22	__all__ = ["SymEulerSGMCMC"]	CODE
LOW	nerflets/models/rendering.py	32	__all__ = ['render_rays']	CODE
LOW	COSTAR/utils/ckpt.py	33	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_rep_est.py	43	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_msm.py	33	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_rmsn.py	43	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_enc_dec.py	46	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_multi.py	49	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/runnables/train_gnet.py	41	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/rmsn.py	40	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/time_varying_model.py	59	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/ct.py	40	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/msm.py	41	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/crn.py	35	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/edct.py	42	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/gnet.py	39	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/rep_est/rep_est.py	34	logger = logging.getLogger(__name__)	CODE
LOW	COSTAR/src/models/rep_est/cotrans.py	33	logger = logging.getLogger(__name__)	CODE
32 more matches not shown…

Dead Code34 hits · 68 pts

Severity	File	Line	Context
MEDIUM	jrl/agents/msg/networks.py	547	CODE
MEDIUM	jrl/agents/msg/networks.py	555	CODE
MEDIUM	jrl/agents/msg/networks.py	556	CODE
MEDIUM	jrl/agents/msg/networks.py	557	CODE
MEDIUM	jrl/utils/network_utils.py	85	CODE
MEDIUM	jrl/utils/network_utils.py	86	CODE
MEDIUM	jrl/utils/network_utils.py	87	CODE
MEDIUM	jrl/utils/network_utils.py	89	CODE
MEDIUM	jrl/utils/network_utils.py	112	CODE
MEDIUM	smerf/smerf/internal/train_utils.py	757	CODE
MEDIUM	smerf/smerf/internal/train_utils.py	760	CODE
MEDIUM	smerf/smerf/internal/train_utils.py	764	CODE
MEDIUM	…ion/diffusion_distillation/config/church128_distill.py	100	CODE
MEDIUM	…ion/diffusion_distillation/config/church128_distill.py	106	CODE
MEDIUM	…on/diffusion_distillation/config/imagenet64_distill.py	100	CODE
MEDIUM	…on/diffusion_distillation/config/imagenet64_distill.py	106	CODE
MEDIUM	…on/diffusion_distillation/config/bedroom128_distill.py	100	CODE
MEDIUM	…on/diffusion_distillation/config/bedroom128_distill.py	106	CODE
MEDIUM	bnn_hmc/utils/train_utils.py	215	CODE
MEDIUM	local_forward_gradient/train_mixer_supervised.py	1484	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	313	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	314	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	316	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	317	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	319	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	321	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	322	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	323	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	325	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	326	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	327	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	328	CODE
MEDIUM	strategic_exploration/hrl/env_wrapper.py	330	CODE
MEDIUM	strategic_exploration/hrl/graph_update.py	142	CODE

Slop Phrases37 hits · 62 pts

Severity	File	Line	Snippet	Context
MEDIUM	schema_guided_dst/baseline/data_utils.py	587	# the value was mentioned earlier in the dialogue. Since this model	COMMENT
MEDIUM	jrl/utils/saved_model_lib.py	107	# names, you can use `tree.map_structure_with_path` from the `dm-tree` package	COMMENT
LOW	multimodalchat/photochat/test/test_01.json	31017	"message": "You should! Don't forget to grab some coffee while you're out.",	CODE
MEDIUM	multimodalchat/photochat/test/test_01.json	38183	"message": "Haha yeah, I'm unable to share the photo right now. But I will soon. I wish you could see it now tho	CODE
MEDIUM	multimodalchat/photochat/train/train_01.json	9999	"message": "I'm unable to share the photo for some reason",	CODE
MEDIUM	multimodalchat/photochat/train/train_16.json	9493	"message": "Let me know if you need any extra help!",	CODE
LOW	multimodalchat/photochat/train/train_07.json	32842	"message": "the game is over at the high school fields, 7pm sharp, don't forget to cheer on my Mom, her jersey h	CODE
LOW	multimodalchat/photochat/train/train_10.json	2164	"message": "Better late than never. Don't forget to invite me.",	CODE
LOW	multimodalchat/photochat/train/train_05.json	7432	"message": "Oh thats beautiful. next time don't forget to invite me.",	CODE
LOW	multimodalchat/photochat/train/train_13.json	2321	"message": "don't forget to bring your mobile device in case we need to call for a ride home",	CODE
LOW	multimodalchat/photochat/train/train_08.json	14788	"message": "That sounds great! I'm sure you'll love it. Don't forget to pack your apple laptop to bring with you	CODE
MEDIUM	multimodalchat/photochat/train/train_03.json	2971	"message": "I'm unable to sleep for the past few days.",	CODE
LOW	multimodalchat/photochat/train/train_15.json	1611	"message": "I'll buy us each a beer, don't forget to bring your mobile device in case we need to call for a ride	CODE
LOW	multimodalchat/photochat/dev/dev_00.json	7022	"message": "don't forget to join us",	CODE
LOW	imp/max/execution/executors.py	543	# we make sure to cache the transformed obj_fns to avoid re-compiling	COMMENT
MEDIUM	data_selection/wmt/input_pipeline.py	810	# Optionally you can add a seed for better reproducibility	COMMENT
LOW	…ples/research_projects/summarization/ppo_summ_rouge.py	265	# We make sure to use `Adam` optimizer on the model parameters	COMMENT
LOW	…mples/research_projects/summarization/ppo_summ_rlhf.py	369	# make sure to use `Adam` optimizer on parameters that require gradients.	COMMENT
LOW	…ch_projects/toxicity/ppo-intrinsic-rewards-toxicity.py	170	# We make sure to use `Adam` optimizer on the model parameters	COMMENT
LOW	…_projects/sentiment/ppo-intrinsic-rewards-sentiment.py	326	# the sentiment analysis pipeline arguments. Let's also make sure to set	COMMENT
LOW	…/examples/research_projects/sentiment/ppo-sentiment.py	131	# the sentiment analysis pipeline arguments. Let's also make sure to set the	COMMENT
MEDIUM	fvlm/utils/saved_model_lib.py	127	# names, you can use `tree.map_structure_with_path` from the `dm-tree` package	COMMENT
LOW	covid_epidemiology/src/constants.py	645	# If you are changing any of the parameters below, please make sure to update	COMMENT
LOW	…ogy/src/models/generic_seir_state_model_constructor.py	1018	# If you are changing any of the parameters below, please make sure to	COMMENT
LOW	…els/generic_seir_japan_prefecture_model_constructor.py	960	# If you are changing any of the parameters below, please make sure to	COMMENT
LOW	…gy/src/models/generic_seir_county_model_constructor.py	1297	# If you are changing any of the parameters below, please make sure to	COMMENT
LOW	gigamol/run_test.sh	1	# To run this script, please make sure you have virtualenv and bazel installed.	COMMENT
MEDIUM	…resample_with_dp_histogram/resample_with_embeddings.py	185	ratio = noisy_p_bins / q_bins # you can also use full_q_bins instead of q_bins.	CODE
LOW	ncsnv3/utils.py	197	# logic will make sure to only commit checkpoints if they complete	COMMENT
LOW	…ined_language_typology/build_feature_matrix_example.py	85	# Obviously if you use this make sure you do the same thing to both training	COMMENT
LOW	invariant_explanations/utils.py	146	# make sure to filter to the right stratum here before further analysis.	COMMENT
LOW	invariant_explanations/utils.py	435	# the same hparams, but make sure you get the correct rows for tr/te acc!!!	COMMENT
MEDIUM	anthea/template-mqm-source-media.js	686	As mentioned earlier, the context of the document is sometimes the	CODE
MEDIUM	anthea/template-mqm-speech-to-speech.js	596	As mentioned earlier, the context of the document is sometimes the	CODE
MEDIUM	anthea/template-base.js	432	As mentioned earlier, the context of the document is sometimes the	CODE
LOW	snerg/snerg/eval_and_refine.py	209	# Then, make sure to populate the output array in the same order	COMMENT
LOW	abstract_nas/synthesis/enum_sequential.py	211	# may have changed, so make sure to randomize from the most up-to-date	COMMENT

AI Response Leakage5 hits · 41 pts

Severity	File	Line	Snippet	Context
HIGH⚡	…positional_rl/gwob/examples/web_environment_example.py	47	# are used to shape them. In this example, they don't have that effect.	COMMENT
HIGH	dvrl/main_corrupted_sample_discovery.py	88	# In this example, we consider a classification problem and we use Logistic	COMMENT
HIGH	m_theory/m_theory_lib/ode/ode_hessian_test.py	45	# In this example, we are going for 'recovered = 0.80' at-end.	COMMENT
HIGH	correct_batch_effects_wdn/transform_test.py	140	# In this example, the eigenvalues are discrete, so the eigenvectors are	COMMENT
HIGH	…e_representations_for_entity_retrieval/mel/mewsli-x.md	210	# In this example, just locate the gold entity by its ID to look at some of	COMMENT

Synthetic Comment Markers2 hits · 15 pts

Severity	File	Line	Snippet	Context
HIGH	…ory/dim4/so8_supergravity_extrema/code/distillation.py	151	# Diagonalizes either the 35s or 35c, as requested.	COMMENT
HIGH	…n_semantic_speech_benchmark/data_prep/splitter_test.py	80	# Check number of groups in train/dev/test are as requested.	COMMENT

Overly Generic Function Names13 hits · 12 pts

Severity	File	Line	Snippet	Context
LOW	fm4tlp/utils/dataset_pyg_transfer.py	148	def process_data(self):	STRING
LOW	fm4tlp/utils/dataset_pyg.py	177	def process_data(self):	STRING
LOW	nf_diffusion/models/ldm_reluf_dual_v2.py	496	def helper(zt, xt, gt):	CODE
LOW	nf_diffusion/models/ldm_reluf_dual_v3.py	467	def helper(zt, xt, gt):	CODE
LOW	jaxstronomy/source_models_test.py	104	def test_function(self):	CODE
LOW	jaxstronomy/source_models_test.py	154	def test_function(self):	CODE
LOW	speculative_kd/train/train_sft.py	114	def process_data(args, data, tokenizer, remove_columns):	CODE
LOW	vct/src/tf_memoize.py	25	def my_function(x, y, z):	STRING
LOW	constrained_language_typology/build_feature_matrix.py	315	def process_data(self, target_feature, force_recompute=False,	CODE
LOW	hipi/envs/dm_env.py	251	def run_task(time_limit=quadruped._DEFAULT_TIME_LIMIT, # pylint: disable=protected-access	CODE
LOW	COSTAR/src/data/mimic_iii/semi_synthetic_dataset.py	1368	def process_data(self, scaling_params):	CODE
LOW	COSTAR/src/data/cancer_sim/dataset.py	183	def process_data(self, scaling_params):	CODE
LOW	merf/internal/coord.py	88	def helper(x, d):	CODE

Example Usage Blocks7 hits · 10 pts

Severity	File	Line	Snippet	Context
LOW	hmc_swindles/scripts/fetch_datasets.sh	20	# Usage:	COMMENT
LOW	automl_zero/run_integration_tests.sh	21	# Usage:	COMMENT
LOW	automl_zero/run_demo.sh	18	# Usage:	COMMENT
LOW	agile_deliberation/setup.sh	19	# Usage:	COMMENT
LOW	informally_romanized_lang_id/train_pair_lm.sh	20	# Example usage:	COMMENT
LOW	…lly_romanized_lang_id/create_supplementary_lexicons.sh	21	# Example usage:	COMMENT
LOW	simulation_research/traffic/fcd_file_cutter.sh	22	# Example usage:	COMMENT

Magic Placeholder Names2 hits · 8 pts

Severity	File	Line	Snippet	Context
HIGH	relc/llm-intrinsic-reward/README.md	151	export PERSPECTIVE_API_KEY="YOUR_API_KEY"	CODE
HIGH	behavioral_dispositions/src/gemini_runner.py	39	client = genai.Client(api_key="YOUR_API_KEY")	STRING

TODO Padding1 hit · 2 pts

Severity	File	Line	Snippet	Context
LOW	tide_nlp/identity_annotator.py	139	# TODO: implement confidence measure and don't filter out low confidence.	COMMENT

Analysis Overview

What These Metrics Mean

Score History

Severity Breakdown

Directory Score Breakdown

Pattern Findings