AI Slop Code RIsk Monitor

microsoft/unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

26.6 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for microsoft/unilm, a Python project with 22,230 GitHub stars. SynthScan examined 1,384,201 lines of code across 5680 source files, recording 15485 pattern matches distributed across 24 syntactic categories. The legacy adjusted pattern signal is 26.6 (Elevated pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

26.6
Adjusted Signal
26.6
Raw Pattern Score
100%
Time Factor
2026-09-21
Last Push
22.2K
Stars
Python
Language
1.4M
Lines of Code
5.7K
Files
15.5K
Pattern Hits
2026-10-12
Scan Date
0.90
HC Hit Rate

Risk Review · v3

Use each vector to guide manual verification of the underlying findings.

Cognitive Ownership Risk 18.2/100 · LOW

Can maintainers explain intent, assumptions, and trade-offs? 5382 finding(s).

Hallucinated Dependency & Supply Chain Risk 12.9/100 · LOW

Are imports declared and package/API names verified? 3748 finding(s).

Agent Over-Engineering Ratio 66.4/100 · HIGH

Are wrappers, guards, and repeated structures necessary? 9074 finding(s).

PR Review Velocity Impact 78.3/100 · CRITICAL

Which changes need focused human review? 15485 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

Run additional scans to build a history of the legacy pattern signal. Score changes are not a measure of AI adoption or code quality.

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

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 29HIGH 5093MEDIUM 531LOW 9832

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 15485 distinct pattern matches across 24 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. 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 configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Cross-File Repetition4895 hits · 24475 pts
SeverityFileLineSnippetContext
HIGHDiff-Transformer/kernel/rotary.py0arguments: x: (batch, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim). cos: (seqlen_STRING
HIGHYOCO/yoco/models/decoder/kernel/rotary.py0arguments: x: (batch, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim). cos: (seqlen_STRING
HIGHLatentLM/models/kernel/rotary.py0arguments: x: (batch, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim). cos: (seqlen_STRING
HIGHReSA/llm/kernel/rotary.py0arguments: x: (batch, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim). cos: (seqlen_STRING
HIGHDiff-Transformer/kernel/rotary.py0arguments: x: (batch_size, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim) cos, sin:STRING
HIGHYOCO/yoco/models/decoder/kernel/rotary.py0arguments: x: (batch_size, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim) cos, sin:STRING
HIGHLatentLM/models/kernel/rotary.py0arguments: x: (batch_size, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim) cos, sin:STRING
HIGHReSA/llm/kernel/rotary.py0arguments: x: (batch_size, seqlen, nheads, headdim) if cu_seqlens is none else (total_seqlen, nheads, headdim) cos, sin:STRING
HIGHwavlm/modules.py0returns the activation function corresponding to `activation`STRING
HIGHinfoxlm/fairseq/fairseq/utils.py0returns the activation function corresponding to `activation`STRING
HIGHedgelm/fairseq/utils.py0returns the activation function corresponding to `activation`STRING
HIGHbeats/modules.py0returns the activation function corresponding to `activation`STRING
HIGHdecoding/GAD/fairseq/utils.py0returns the activation function corresponding to `activation`STRING
HIGHdecoding/IAD/fairseq/fairseq/utils.py0returns the activation function corresponding to `activation`STRING
HIGHspeechlm/modules.py0returns the activation function corresponding to `activation`STRING
HIGHkosmos-2/fairseq/fairseq/utils.py0returns the activation function corresponding to `activation`STRING
HIGHwavlm/modules.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGH…airseq/fairseq/modules/transformer_sentence_encoder.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGHedgelm/fairseq/modules/transformer_sentence_encoder.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGHbeats/backbone.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGH…ng/GAD/fairseq/modules/transformer_sentence_encoder.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGH…airseq/fairseq/modules/transformer_sentence_encoder.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGHspeechlm/modules.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGH…airseq/fairseq/modules/transformer_sentence_encoder.py0initialize the weights specific to the bert model. this overrides the default initializations depending on the specifiedSTRING
HIGHwavlm/modules.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHedgelm/fairseq/modules/quant_noise.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHbeats/modules.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHdecoding/GAD/fairseq/modules/quant_noise.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHdecoding/IAD/fairseq/fairseq/modules/quant_noise.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHspeechlm/modules.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHkosmos-2/fairseq/fairseq/modules/quant_noise.py0wraps modules and applies quantization noise to the weights for subsequent quantization with iterative product quantizatSTRING
HIGHwavlm/modules.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHinfoxlm/fairseq/fairseq/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHedgelm/fairseq/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHbeats/backbone.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHdecoding/GAD/fairseq/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGH…ing/IAD/fairseq/fairseq/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHspeecht5/speecht5/models/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHspeechlm/modules.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHspeechlm/speechlm/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHkosmos-2/fairseq/fairseq/modules/multihead_attention.py0multi-headed attention. see "attention is all you need" for more details.STRING
HIGHwavlm/modules.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHinfoxlm/fairseq/fairseq/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHedgelm/fairseq/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGH…er/linformer_src/modules/multihead_linear_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHbeats/backbone.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHdecoding/GAD/fairseq/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGH…ing/IAD/fairseq/fairseq/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGH…er/linformer_src/modules/multihead_linear_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHspeecht5/speecht5/models/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHspeechlm/modules.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHspeechlm/speechlm/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHkosmos-2/fairseq/fairseq/modules/multihead_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGH…er/linformer_src/modules/multihead_linear_attention.py0input shape: time x batch x channel args: key_padding_mask (bytetensor, optional): mask to exclude keys that are pads, oSTRING
HIGHwavlm/WavLM.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
HIGHedgelm/fairseq/data/data_utils.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
HIGHdecoding/GAD/fairseq/data/data_utils.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
HIGHdecoding/IAD/fairseq/fairseq/data/data_utils.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
HIGHkosmos-2/fairseq/fairseq/data/data_utils.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
HIGHspeechlm/modules.py0computes random mask spans for a given shape args: shape: the the shape for which to compute masks. should be of size 2 STRING
4835 more matches not shown…
Unused Imports3664 hits · 3324 pts
SeverityFileLineSnippetContext
LOWvlmo/vlmo/datasets/wikibk_dataset.py1CODE
LOWvlmo/vlmo/datasets/__init__.py1CODE
LOWvlmo/vlmo/datasets/__init__.py2CODE
LOWvlmo/vlmo/datasets/__init__.py3CODE
LOWvlmo/vlmo/datasets/__init__.py4CODE
LOWvlmo/vlmo/datasets/__init__.py5CODE
LOWvlmo/vlmo/datasets/__init__.py6CODE
LOWvlmo/vlmo/datasets/__init__.py7CODE
LOWvlmo/vlmo/datasets/__init__.py8CODE
LOWvlmo/vlmo/datasets/sbu_caption_dataset.py1CODE
LOWvlmo/vlmo/datasets/conceptual_caption_dataset.py1CODE
LOWvlmo/vlmo/utils/write_wikibk.py1CODE
LOWvlmo/vlmo/utils/write_wikibk.py5CODE
LOWvlmo/vlmo/utils/write_wikibk.py9CODE
LOWvlmo/vlmo/modules/__init__.py1CODE
LOWvlmo/vlmo/modules/vlmo_module.py1CODE
LOWvlmo/vlmo/modules/vlmo_module.py7CODE
LOWvlmo/vlmo/modules/vlmo_utils.py2CODE
LOWvlmo/vlmo/modules/vlmo_utils.py3CODE
LOWvlmo/vlmo/modules/vlmo_utils.py10CODE
LOWvlmo/vlmo/modules/vlmo_utils.py11CODE
LOWvlmo/vlmo/modules/objectives.py11CODE
LOWvlmo/vlmo/modules/objectives.py12CODE
LOWvlmo/vlmo/modules/heads.py3CODE
LOWDiff-Transformer/multihead_diffattn.py7CODE
LOWDiff-Transformer/multihead_attention.py1CODE
LOWDiff-Transformer/multihead_attention.py7CODE
LOWDiff-Transformer/multihead_attention.py9CODE
LOWDiff-Transformer/multihead_attention.py12CODE
LOWDiff-Transformer/multihead_flashdiff_2.py3CODE
LOWDiff-Transformer/multihead_flashdiff_1.py3CODE
LOWinfoxlm/tools/para2bin.py5CODE
LOWinfoxlm/tools/para2bin.py5CODE
LOWinfoxlm/tools/para2bin.py5CODE
LOWinfoxlm/tools/para2bin4xlco.py5CODE
LOWinfoxlm/tools/para2bin4xlco.py5CODE
LOWinfoxlm/tools/para2bin4xlco.py5CODE
LOWinfoxlm/tools/para2bin4xlco.py11CODE
LOWinfoxlm/tools/txt2bin.py5CODE
LOWinfoxlm/fairseq/setup.py109CODE
LOWinfoxlm/fairseq/hubconf.py8CODE
LOWinfoxlm/fairseq/hubconf.py9CODE
LOWinfoxlm/fairseq/hubconf.py24CODE
LOWinfoxlm/fairseq/hubconf.py27CODE
LOWinfoxlm/fairseq/fairseq/__init__.py9CODE
LOWinfoxlm/fairseq/fairseq/__init__.py10CODE
LOWinfoxlm/fairseq/fairseq/__init__.py11CODE
LOWinfoxlm/fairseq/fairseq/__init__.py12CODE
LOWinfoxlm/fairseq/fairseq/__init__.py13CODE
LOWinfoxlm/fairseq/fairseq/__init__.py14CODE
LOWinfoxlm/fairseq/fairseq/__init__.py15CODE
LOWinfoxlm/fairseq/fairseq/progress_bar.py41CODE
LOWinfoxlm/fairseq/fairseq/tasks/fairseq_task.py6CODE
LOWinfoxlm/fairseq/fairseq/optim/__init__.py11CODE
LOWinfoxlm/fairseq/fairseq/optim/__init__.py11CODE
LOWinfoxlm/fairseq/fairseq/optim/__init__.py12CODE
LOWinfoxlm/fairseq/fairseq/optim/adam.py29CODE
LOWinfoxlm/fairseq/fairseq/models/__init__.py10CODE
LOWinfoxlm/fairseq/fairseq/models/__init__.py11CODE
LOWinfoxlm/fairseq/fairseq/models/__init__.py12CODE
3604 more matches not shown…
Hyper-Verbose Identifiers1986 hits · 2011 pts
SeverityFileLineSnippetContext
LOWvlmo/run.py25 def creates_processes_externally(self):CODE
LOWvlmo/vlmo/config.py134def task_mlm_itm_itc_base_plus():CODE
LOWvlmo/vlmo/transforms/pixelbert.py20def pixelbert_transform_randaug(size=800):CODE
LOWvlmo/vlmo/modules/vlmo_module.py350 def build_relative_position_embed(self, config):CODE
LOWvlmo/vlmo/modules/objectives.py609def compute_irtr_recall_with_rerank(pl_module, split="test"):CODE
LOWwavlm/modules.py417 def _relative_positions_bucket(self, relative_positions, bidirectional=True):CODE
LOWwavlm/modules.py766 def _append_prev_key_padding_mask(CODE
LOWinfoxlm/fairseq/preprocess.py160 def make_binary_alignment_dataset(input_prefix, output_prefix, num_workers):CODE
LOWinfoxlm/fairseq/tests/test_bmuf.py27def setup_model_loss_criterion(args, rank, is_cuda):CODE
LOWinfoxlm/fairseq/tests/test_bmuf.py140 def test_warmup_sync_bmuf_sync(self):CODE
LOWinfoxlm/fairseq/tests/test_utils.py15 def test_convert_padding_direction(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py22 def _get_test_data_with_bpe_cont_marker(self, append_eos=True):CODE
LOWinfoxlm/fairseq/tests/test_noising.py57 def _get_test_data_with_bpe_end_marker(self, append_eos=True):CODE
LOWinfoxlm/fairseq/tests/test_noising.py93 def _get_test_data_with_word_vocab(self, append_eos=True):CODE
LOWinfoxlm/fairseq/tests/test_noising.py122 def _convert_src_tokens_to_tensor(CODE
LOWinfoxlm/fairseq/tests/test_noising.py152 def assert_word_dropout_correct(self, x, x_noised, x_len, l_noised):CODE
LOWinfoxlm/fairseq/tests/test_noising.py159 def test_word_dropout_with_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py170 def assert_word_blanking_correct(self, x, x_noised, x_len, l_noised, unk):CODE
LOWinfoxlm/fairseq/tests/test_noising.py191 def generate_unchanged_shuffle_map(self, length):CODE
LOWinfoxlm/fairseq/tests/test_noising.py194 def assert_word_shuffle_matches_expected(CODE
LOWinfoxlm/fairseq/tests/test_noising.py246 def test_word_shuffle_with_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py277 def test_word_shuffle_with_eos_nonbpe(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py309 def test_word_shuffle_without_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py341 def test_word_shuffle_without_eos_with_bpe_end_marker(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py386 def test_word_dropout_without_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py398 def test_word_blank_without_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py410 def _get_noising_dataset_batch(CODE
LOWinfoxlm/fairseq/tests/test_noising.py448 def test_noising_dataset_with_eos(self):CODE
LOWinfoxlm/fairseq/tests/test_noising.py480 def test_noising_dataset_without_eos(self):CODE
LOW…foxlm/fairseq/tests/test_sparse_multihead_attention.py12 def test_sparse_multihead_attention(self):CODE
LOWinfoxlm/fairseq/tests/test_train.py37def get_trainer_and_epoch_itr(epoch, epoch_size, num_updates, iterations_in_epoch):CODE
LOWinfoxlm/fairseq/tests/test_train.py69 def test_load_partial_checkpoint(self):CODE
LOWinfoxlm/fairseq/tests/test_train.py99 def test_load_full_checkpoint(self):CODE
LOWinfoxlm/fairseq/tests/test_multihead_attention.py12 def test_append_prev_key_padding_mask(self):CODE
LOWinfoxlm/fairseq/tests/test_resampling_dataset.py66 def test_resampling_dataset_batch_by_size_false(self):CODE
LOWinfoxlm/fairseq/tests/test_resampling_dataset.py84 def test_resampling_dataset_batch_by_size_true(self):CODE
LOWinfoxlm/fairseq/tests/test_backtranslation_dataset.py32 def _backtranslation_dataset_helper(CODE
LOW⚡infoxlm/fairseq/tests/test_backtranslation_dataset.py95 def test_backtranslation_dataset_no_eos_in_output_src(self):CODE
LOW⚡infoxlm/fairseq/tests/test_backtranslation_dataset.py100 def test_backtranslation_dataset_with_eos_in_output_src(self):CODE
LOW⚡infoxlm/fairseq/tests/test_backtranslation_dataset.py105 def test_backtranslation_dataset_no_eos_in_input_src(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py157 def test_transformer_cross_self_attention(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py219 def test_levenshtein_transformer(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py235 def test_nonautoregressive_transformer(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py252 def test_iterative_nonautoregressive_transformer(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py269 def test_insertion_transformer(self):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py418 def _test_pretrained_masked_lm_for_translation(self, learned_pos_emb, encoder_only):CODE
LOW⚡infoxlm/fairseq/tests/test_binaries.py471 def test_pretrained_masked_lm_for_translation_learned_pos_emb(self):CODE
LOW⚡infoxlm/fairseq/tests/test_binaries.py474 def test_pretrained_masked_lm_for_translation_sinusoidal_pos_emb(self):CODE
LOW⚡infoxlm/fairseq/tests/test_binaries.py477 def test_pretrained_masked_lm_for_translation_encoder_only(self):CODE
LOW⚡infoxlm/fairseq/tests/test_binaries.py481def train_legacy_masked_language_model(data_dir, arch, extra_args=()):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py580 def _create_dummy_alignment_data(filename_src, filename_tgt, filename):CODE
LOWinfoxlm/fairseq/tests/test_binaries.py606def preprocess_translation_data(data_dir, extra_flags=None):CODE
LOWinfoxlm/fairseq/tests/test_sequence_generator.py68 def test_without_normalization(self):CODE
LOWinfoxlm/fairseq/tests/test_sequence_generator.py87 def test_with_lenpen_favoring_short_hypos(self):CODE
LOWinfoxlm/fairseq/tests/test_sequence_generator.py105 def test_with_lenpen_favoring_long_hypos(self):CODE
LOWinfoxlm/fairseq/tests/test_sequence_generator.py281 def test_topp_sampling_search_low_prob(self):CODE
LOWinfoxlm/fairseq/tests/test_sequence_generator.py310 def test_topp_sampling_search_high_prob(self):CODE
LOWinfoxlm/fairseq/tests/test_concat_dataset.py42 def test_concat_dataset_basics(self):CODE
LOWinfoxlm/fairseq/tests/test_character_token_embedder.py14 def test_character_token_embedder(self):CODE
LOWinfoxlm/fairseq/tests/test_average_checkpoints.py87 def test_average_checkpoints_with_shared_parameters(self):CODE
1926 more matches not shown…
Deep Nesting1527 hits · 1497 pts
SeverityFileLineSnippetContext
LOWvlmo/run.py69CODE
LOWvlmo/vlmo/utils/write_conceptual_caption.py30CODE
LOWvlmo/vlmo/utils/write_vqa.py13CODE
LOWvlmo/vlmo/utils/write_vqa.py52CODE
LOWvlmo/vlmo/modules/vlmo_module.py229CODE
LOWvlmo/vlmo/modules/vlmo_utils.py16CODE
LOWvlmo/vlmo/modules/vlmo_utils.py55CODE
LOWminilm/examples/run_xnli.py81CODE
LOWminilm/examples/run_xnli.py258CODE
LOWwavlm/modules.py144CODE
LOWwavlm/modules.py100CODE
LOWwavlm/modules.py766CODE
LOWwavlm/WavLM.py35CODE
LOWwavlm/WavLM.py379CODE
LOWinfoxlm/fairseq/preprocess.py22CODE
LOWinfoxlm/fairseq/generate.py16CODE
LOWinfoxlm/fairseq/interactive.py57CODE
LOWinfoxlm/fairseq/train.py226CODE
LOWinfoxlm/fairseq/train.py286CODE
LOWinfoxlm/fairseq/eval_lm.py46CODE
LOWinfoxlm/fairseq/score.py35CODE
LOWinfoxlm/fairseq/tests/test_binaries.py546CODE
LOW…oxlm/fairseq/fairseq/iterative_refinement_generator.py102CODE
LOWinfoxlm/fairseq/fairseq/registry.py65CODE
LOWinfoxlm/fairseq/fairseq/sequence_generator.py116CODE
LOWinfoxlm/fairseq/fairseq/pdb.py32CODE
LOWinfoxlm/fairseq/fairseq/hub_utils.py18CODE
LOWinfoxlm/fairseq/fairseq/sequence_scorer.py22CODE
LOWinfoxlm/fairseq/fairseq/utils.py92CODE
LOWinfoxlm/fairseq/fairseq/utils.py239CODE
LOWinfoxlm/fairseq/fairseq/utils.py319CODE
LOWinfoxlm/fairseq/fairseq/distributed_utils.py22CODE
LOWinfoxlm/fairseq/fairseq/progress_bar.py20CODE
LOWinfoxlm/fairseq/fairseq/progress_bar.py50CODE
LOWinfoxlm/fairseq/fairseq/trainer.py171CODE
LOWinfoxlm/fairseq/fairseq/trainer.py287CODE
LOWinfoxlm/fairseq/fairseq/trainer.py500CODE
LOWinfoxlm/fairseq/fairseq/tasks/translation_lev.py54CODE
LOWinfoxlm/fairseq/fairseq/tasks/translation.py24CODE
LOW…lm/fairseq/fairseq/tasks/semisupervised_translation.py134CODE
LOWinfoxlm/fairseq/fairseq/tasks/translation_moe.py57CODE
LOWinfoxlm/fairseq/fairseq/tasks/translation_moe.py83CODE
LOWinfoxlm/fairseq/fairseq/optim/adafactor.py128CODE
LOWinfoxlm/fairseq/fairseq/optim/adam.py112CODE
LOW…q/fairseq/optim/lr_scheduler/tri_stage_lr_scheduler.py144CODE
LOWinfoxlm/fairseq/fairseq/models/fconv_self_att.py397CODE
LOWinfoxlm/fairseq/fairseq/models/transformer.py738CODE
LOWinfoxlm/fairseq/fairseq/models/fconv.py423CODE
LOWinfoxlm/fairseq/fairseq/models/bart/model.py129CODE
LOW…oxlm/fairseq/fairseq/models/roberta/alignment_utils.py12CODE
LOWinfoxlm/fairseq/fairseq/models/roberta/model.py148CODE
LOWinfoxlm/fairseq/fairseq/modules/multihead_attention.py281CODE
LOW…q/fairseq/modules/lightconv_layer/cuda_function_gen.py7CODE
LOW…q/fairseq/modules/lightconv_layer/cuda_function_gen.py116CODE
LOW…fairseq/modules/dynamicconv_layer/cuda_function_gen.py7CODE
LOW…fairseq/modules/dynamicconv_layer/cuda_function_gen.py96CODE
LOWinfoxlm/fairseq/fairseq/data/monolingual_dataset.py99CODE
LOWinfoxlm/fairseq/fairseq/data/mask_tokens_dataset.py98CODE
LOWinfoxlm/fairseq/fairseq/data/indexed_dataset.py28CODE
LOWinfoxlm/fairseq/fairseq/data/indexed_dataset.py51CODE
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Decorative Section Separators389 hits · 1204 pts
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MEDIUMwavlm/modules.py1# --------------------------------------------------------COMMENT
MEDIUMwavlm/modules.py8# --------------------------------------------------------COMMENT
MEDIUMwavlm/WavLM.py1# --------------------------------------------------------COMMENT
MEDIUMwavlm/WavLM.py8# --------------------------------------------------------COMMENT
MEDIUM⚡…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py4 # -----------------------------------------------------------------------------COMMENT
MEDIUM⚡…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py6 # -----------------------------------------------------------------------------COMMENT
MEDIUMunilm-v1/src/qg/eval_on_unilm_tokenized_ref.py134 # =================================================COMMENT
MEDIUMunilm-v1/src/qg/eval_on_unilm_tokenized_ref.py136 # =================================================COMMENT
MEDIUMunilm-v1/src/qg/eval.py134 # =================================================COMMENT
MEDIUMunilm-v1/src/qg/eval.py136 # =================================================COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py45# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py47# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py102# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py104# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py210# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py212# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py338# ------------------------------------------------------------------------------COMMENT
MEDIUM⚡edgelm/fairseq/models/speech_to_text/utils.py340# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py18# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py20# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py67# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py69# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py86# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py88# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py128# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py130# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py146# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py148# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py163# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py165# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py180# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py182# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py194# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py196# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py291# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py293# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py357# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py359# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py402# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py404# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py455# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py457# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py519# ------------------------------------------------------------------------------COMMENT
MEDIUMedgelm/fairseq/models/speech_to_text/utils.py521# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py88# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py90# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py149# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py151# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py225# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py227# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py1780# ------------------------------------------------------------------------------COMMENT
MEDIUM…gelm/fairseq/models/speech_to_text/modules/emformer.py1783# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py23# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py25# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py119# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py121# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py187# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py189# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py358# ------------------------------------------------------------------------------COMMENT
MEDIUM…s/speech_to_text/modules/augmented_memory_attention.py360# ------------------------------------------------------------------------------COMMENT
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Over-Commented Block927 hits · 834 pts
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LOWvlmo/vlmo/transforms/randaug.py161def augment_list(): # 16 oeprations and their rangesCOMMENT
LOWminilm/examples/run_xnli.py1# coding=utf-8COMMENT
LOW…lm/fairseq/fairseq/modules/lightconv_layer/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOW…/fairseq/fairseq/modules/dynamicconv_layer/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWinfoxlm/fairseq/docs/conf.py1#!/usr/bin/env python3COMMENT
LOWinfoxlm/fairseq/docs/conf.py61#COMMENT
LOWinfoxlm/fairseq/docs/conf.py81highlight_language = 'python'COMMENT
LOWinfoxlm/fairseq/docs/conf.py101# relative to this directory. They are copied after the builtin static files,COMMENT
LOWinfoxlm/fairseq/examples/noisychannel/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOW…q/examples/speech_recognition/models/vggtransformer.py961 # - transformer_layers (x12) --> 37.74MCOMMENT
LOW…lm/fairseq/examples/roberta/commonsense_qa/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWmarkuplm/examples/fine_tuning/run_swde/prepare_data.py1# coding=utf-8COMMENT
LOWmarkuplm/examples/fine_tuning/run_swde/prepare_data.py421 # now for each page_dataCOMMENT
LOWmarkuplm/examples/fine_tuning/run_swde/pack_data.py1# coding=utf-8COMMENT
LOWmarkuplm/examples/fine_tuning/run_swde/constants.py1# coding=utf-8COMMENT
LOW…rkuplm/markuplmft/models/markuplm/modeling_markuplm.py1# coding=utf-8COMMENT
LOW…lm/markuplmft/models/markuplm/tokenization_markuplm.py1# coding=utf-8COMMENT
LOWmarkuplm/markuplmft/models/markuplm/__init__.py1# flake8: noqaCOMMENT
LOW…m/markuplmft/models/markuplm/configuration_markuplm.py1# coding=utf-8COMMENT
LOW…rkuplmft/models/markuplm/tokenization_markuplm_fast.py1# coding=utf-8COMMENT
LOW…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py1# -*- coding: utf-8 -*-COMMENT
LOW…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py21 # ---------------------------------------------------------------------------- #COMMENT
LOW…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py41 # e.g., ["p2", "p3", "p4", "p5", "p6"] for FPNCOMMENT
LOW…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py61 _C.MODEL.ROI_HEADS.NUM_CLASSES = 5COMMENT
LOWYOCO/yoco/__init__.py1# Copyright (c) 2022 MicrosoftCOMMENT
LOWYOCO/yoco/validate.py141 )COMMENT
LOWunilm-v1/src/pytorch_pretrained_bert/optimization.py1# coding=utf-8COMMENT
LOWunilm-v1/src/pytorch_pretrained_bert/tokenization.py1# coding=utf-8COMMENT
LOW…lm-v1/src/pytorch_pretrained_bert/optimization_fp16.py61 self.last_overflow_iter = state_dict['last_overflow_iter']COMMENT
LOWedgelm/tests/test_binaries.py781 # with contextlib.redirect_stdout(StringIO()):COMMENT
LOWedgelm/fairseq/search.py481 # truncate. Now that the candidates are sorted by (bank,COMMENT
LOWedgelm/fairseq/benchmark/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/config/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/clib/libnat/edit_dist.cpp1/**COMMENT
LOWedgelm/fairseq/models/speech_to_text/utils.py261 )COMMENT
LOW…gelm/fairseq/models/speech_to_text/modules/emformer.py1141 # the attention matrix is formed by 9 parts:COMMENT
LOWedgelm/fairseq/model_parallel/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOW…allel/models/pipeline_parallel_transformer/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOW…gelm/fairseq/model_parallel/models/roberta/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/modules/quantization/pq/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/modules/quantization/scalar/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/modules/lightconv_layer/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/modules/dynamicconv_layer/__init__.py1# Copyright (c) Facebook, Inc. and its affiliates.COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp1/* Generated by Cython 0.29.28 */COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp21 #define __stdcallCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp41#endifCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp61 #endifCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp81 #define CYTHON_PEP489_MULTI_PHASE_INIT 0COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp101 #ifndef CYTHON_USE_UNICODE_INTERNALSCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp121 #undef CYTHON_PEP489_MULTI_PHASE_INITCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp141 #endifCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp161 #undef CYTHON_USE_UNICODE_WRITERCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp181 #ifndef CYTHON_FAST_PYCALLCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp201#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1)COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp221 #if defined(__GNUC__)COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp241# define CYTHON_UNUSEDCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp261 #if _MSC_VER < 1300COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp281 #endifCOMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp321 private:COMMENT
LOWedgelm/fairseq/data/data_utils_fast.cpp401 PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)COMMENT
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Empty Error Handlers160 hits · 800 pts
SeverityFileLineSnippetContext
HIGHinfoxlm/fairseq/setup.py82except ImportError:CODE
HIGHinfoxlm/fairseq/fairseq/distributed_utils.py66except FileNotFoundError: # Slurm is not installedCODE
HIGHinfoxlm/fairseq/fairseq/modules/layer_norm.py14except ImportError:CODE
HIGHinfoxlm/fairseq/fairseq_cli/setup.py82except ImportError:CODE
HIGHedgelm/setup.py159except ImportError:CODE
HIGHedgelm/setup.py33except Exception:CODE
HIGHedgelm/fairseq/checkpoint_utils.py315except FileNotFoundError:CODE
HIGHedgelm/fairseq/tasks/multilingual_translation.py86except ArgumentError:CODE
HIGHedgelm/fairseq/tasks/online_backtranslation.py119except ArgumentError:CODE
HIGHedgelm/fairseq/distributed/utils.py136except FileNotFoundError: # Slurm is not installedCODE
HIGHedgelm/fairseq/optim/fused_adam.py383except ImportError:CODE
HIGHedgelm/fairseq/optim/fused_adam.py35except ImportError:CODE
HIGHedgelm/fairseq/dataclass/utils.py192except ArgumentError:CODE
HIGHedgelm/fairseq/dataclass/utils.py270except:CODE
HIGHedgelm/fairseq/data/plasma_utils.py129except plasma.PlasmaObjectExists:CODE
HIGH…fairseq/data/multilingual/multilingual_data_manager.py160except ArgumentError:CODE
HIGHedgelm/examples/__init__.py8except ImportError:CODE
HIGHedgelm/examples/speech_to_text/prep_covost_data.py164except RuntimeError:CODE
HIGH…_nlp/gslm/speech2unit/pretrained/cpc_feature_reader.py161except RuntimeError:CODE
HIGHedgelm/examples/textless_nlp/gslm/ulm/sample.py53except:CODE
HIGHedgelm/examples/speech_recognition/infer.py50except:CODE
HIGHedgelm/examples/laser/laser_src/laser_task.py78except ArgumentError:CODE
HIGHedgelm/examples/MMPT/mmpt/__init__.py11except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/losses/__init__.py10except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/losses/__init__.py15except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/tasks/__init__.py11except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/tasks/__init__.py16except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/tasks/__init__.py21except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/datasets/__init__.py9except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/models/transformermodel.py29except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/models/__init__.py11except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/models/__init__.py16except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/models/mmfusionnlg.py35except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/models/mmfusion.py25except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/evaluators/__init__.py12except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/processors/__init__.py22except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/modules/retri.py12except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/modules/__init__.py9except ImportError:CODE
HIGHedgelm/examples/MMPT/mmpt/modules/mm.py28except ImportError:CODE
HIGHedgelm/examples/truncated_bptt/transformer_xl_model.py98except Exception:CODE
HIGHPFPO/scripts/apps/utils_execute.py1034except SystemExit as e:CODE
HIGHPFPO/scripts/apps/utils_execute.py711except:CODE
HIGHPFPO/scripts/apps/utils_execute.py494except Exception as e:CODE
HIGHPFPO/scripts/apps/utils_execute.py501except Exception as e:CODE
HIGHPFPO/scripts/apps/utils_execute.py748except:CODE
HIGH…pps/pp_test_case_gen_public_outputs_few_shot_verify.py97except:CODE
HIGHPFPO/scripts/apps/pp_test_case.py115except:CODE
HIGHPFPO/data/math.py23except ValueError:CODE
HIGHPFPO/data/math.py29except (TypeError, ValueError):CODE
HIGHPFPO/data/deepseek_math_utils/eval_script.py39except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py144except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py217except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py302except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py308except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py171except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py292except:CODE
HIGHPFPO/data/deepseek_math_utils/eval_utils.py129except:CODE
HIGHPFPO/data/qwen25math/grader.py116except:CODE
HIGHPFPO/data/qwen25math/grader.py295except:CODE
HIGHPFPO/data/qwen25math/grader.py302except:CODE
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AI Structural Patterns733 hits · 728 pts
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LOWvlmo/vlmo/transforms/randaugment.py40CODE
LOWvlmo/vlmo/transforms/randaugment.py63CODE
LOWvlmo/vlmo/transforms/randaugment.py74CODE
LOWvlmo/vlmo/transforms/randaugment.py84CODE
LOWvlmo/vlmo/transforms/randaugment.py106CODE
LOWvlmo/vlmo/transforms/randaugment.py119CODE
LOWvlmo/vlmo/transforms/randaugment.py128CODE
LOWvlmo/vlmo/transforms/randaugment.py156CODE
LOWvlmo/vlmo/transforms/randaugment.py166CODE
LOWvlmo/vlmo/transforms/randaugment.py176CODE
LOWvlmo/vlmo/transforms/randaugment.py184CODE
LOWvlmo/vlmo/transforms/randaugment.py191CODE
LOWvlmo/vlmo/modules/vlmo_module.py471CODE
LOWvlmo/vlmo/modules/vlmo_module.py527CODE
LOWvlmo/vlmo/modules/vlmo_module.py575CODE
LOWvlmo/vlmo/modules/vlmo_module.py620CODE
LOWvlmo/vlmo/modules/vlmo_module.py685CODE
LOWvlmo/vlmo/modules/vlmo_module.py742CODE
LOWvlmo/vlmo/modules/multiway_transformer.py122CODE
LOWvlmo/vlmo/modules/multiway_transformer.py248CODE
LOW…ansformer/Diff-Transformer-V2/multihead_flashdiffv2.py76CODE
LOWwavlm/modules.py65CODE
LOWwavlm/modules.py309CODE
LOWwavlm/modules.py457CODE
LOWwavlm/WavLM.py621CODE
LOWinfoxlm/fairseq/tests/test_bmuf.py24CODE
LOW…oxlm/fairseq/fairseq/iterative_refinement_generator.py24CODE
LOWinfoxlm/fairseq/fairseq/sequence_generator.py16CODE
LOWinfoxlm/fairseq/fairseq/tasks/fairseq_task.py97CODE
LOWinfoxlm/fairseq/fairseq/tasks/multilingual_masked_lm.py282CODE
LOWinfoxlm/fairseq/fairseq/optim/adafactor.py93CODE
LOWinfoxlm/fairseq/fairseq/optim/adam.py216CODE
LOWinfoxlm/fairseq/fairseq/models/fconv_self_att.py292CODE
LOWinfoxlm/fairseq/fairseq/models/fconv_self_att.py482CODE
LOWinfoxlm/fairseq/fairseq/models/fconv.py349CODE
LOWinfoxlm/fairseq/fairseq/models/lstm.py175CODE
LOWinfoxlm/fairseq/fairseq/models/lstm.py310CODE
LOWinfoxlm/fairseq/fairseq/modules/multihead_attention.py21CODE
LOWinfoxlm/fairseq/fairseq/modules/grad_multiply.py14CODE
LOW…q/modules/sparse_transformer_sentence_encoder_layer.py15CODE
LOW…airseq/fairseq/modules/transformer_sentence_encoder.py72CODE
LOW…fairseq/modules/sparse_transformer_sentence_encoder.py17CODE
LOWinfoxlm/fairseq/fairseq/modules/transformer_layer.py188CODE
LOW…/fairseq/modules/transformer_sentence_encoder_layer.py23CODE
LOWinfoxlm/fairseq/fairseq/modules/dynamic_convolution.py14CODE
LOWinfoxlm/fairseq/fairseq/modules/dynamic_convolution.py65CODE
LOWinfoxlm/fairseq/fairseq/modules/dynamic_convolution.py171CODE
LOWinfoxlm/fairseq/fairseq/modules/dynamic_convolution.py217CODE
LOW…xlm/fairseq/fairseq/modules/lightweight_convolution.py202CODE
LOW…xlm/fairseq/fairseq/modules/lightweight_convolution.py233CODE
LOW…/fairseq/fairseq/modules/sparse_multihead_attention.py22CODE
LOW…fairseq/modules/dynamicconv_layer/dynamicconv_layer.py37CODE
LOW…fairseq/modules/dynamicconv_layer/dynamicconv_layer.py171CODE
LOW…fairseq/modules/dynamicconv_layer/dynamicconv_layer.py212CODE
LOWinfoxlm/fairseq/fairseq/data/language_pair_dataset.py149CODE
LOWinfoxlm/fairseq/examples/noisychannel/rerank_utils.py257CODE
LOW…fairseq/examples/speech_recognition/data/data_utils.py24CODE
LOWinfoxlm/src-infoxlm/infoxlm/utils.py24CODE
LOWinfoxlm/src-infoxlm/infoxlm/data/dict_dataset.py55CODE
LOWdeltalm/deltalm/models/deltalm.py220CODE
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Modern Structural Boilerplate684 hits · 685 pts
SeverityFileLineSnippetContext
LOWminilm/examples/run_xnli.py59logger = logging.getLogger(__name__)CODE
LOWwavlm/WavLM.py32logger = logging.getLogger(__name__)CODE
LOWinfoxlm/fairseq/fairseq/__init__.py6__all__ = ['pdb']CODE
LOWinfoxlm/fairseq/fairseq/pdb.py12__all__ = ['set_trace']CODE
LOWinfoxlm/fairseq/fairseq/file_utils.py49logger = logging.getLogger(__name__) # pylint: disable=invalid-nameCODE
LOWinfoxlm/fairseq/fairseq/optim/__init__.py15__all__ = [CODE
LOWinfoxlm/fairseq/fairseq/models/__init__.py32__all__ = [CODE
LOWinfoxlm/fairseq/fairseq/modules/__init__.py32__all__ = [CODE
LOWinfoxlm/fairseq/fairseq/data/__init__.py56__all__ = [CODE
LOWinfoxlm/fairseq/fairseq/data/legacy/__init__.py10__all__ = [CODE
LOWinfoxlm/fairseq/examples/speech_recognition/infer.py22logger = logging.getLogger(__name__)CODE
LOW…m/fairseq/examples/speech_recognition/data/__init__.py8__all__ = [CODE
LOW…seq/examples/speech_recognition/criterions/CTC_loss.py20logger = logging.getLogger(__name__)CODE
LOWinfoxlm/src-infoxlm/infoxlm/criterions/xlco.py14logger = logging.getLogger(__name__)CODE
LOWdeltalm/deltalm/models/deltalm.py35logger = logging.getLogger(__name__)CODE
LOWmarkuplm/examples/fine_tuning/run_websrc/run.py28logger = logging.getLogger(__name__)CODE
LOWmarkuplm/examples/fine_tuning/run_websrc/utils.py17logger = logging.getLogger(__name__)CODE
LOWmarkuplm/examples/fine_tuning/run_websrc/draft.py28logger = logging.getLogger(__name__)CODE
LOWmarkuplm/examples/fine_tuning/run_swde/run.py29logger = logging.getLogger(__name__)CODE
LOWlayoutlmft/layoutlmft/data/datasets/xfun.py15logger = logging.getLogger(__name__)CODE
LOWlayoutlmft/examples/run_xfun_ser.py35logger = logging.getLogger(__name__)CODE
LOWlayoutlmft/examples/run_funsd.py35logger = logging.getLogger(__name__)CODE
LOWlayoutlmft/examples/run_xfun_re.py30logger = logging.getLogger(__name__)CODE
LOWYOCO/yoco/tasks/harness_eval.py26logger = logging.getLogger(__name__)CODE
LOWYOCO/yoco/models/yoco.py26logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/pytorch_pretrained_bert/tokenization.py28logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/pytorch_pretrained_bert/file_utils.py24logger = logging.getLogger(__name__) # pylint: disable=invalid-nameCODE
LOWunilm-v1/src/pytorch_pretrained_bert/modeling.py27logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/gigaword/eval.py32logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/cnndm/eval.py32logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/biunilm/decode_seq2seq.py31logger = logging.getLogger(__name__)CODE
LOWunilm-v1/src/biunilm/run_seq2seq.py33logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/nan_detector.py11logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/__init__.py17__all__ = ["pdb"]CODE
LOWedgelm/fairseq/pdb.py12__all__ = ["set_trace"]CODE
LOWedgelm/fairseq/hub_utils.py20logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/utils.py38logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/checkpoint_utils.py32logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/quantization_utils.py12logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/file_utils.py51logger = logging.getLogger(__name__) # pylint: disable=invalid-nameCODE
LOWedgelm/fairseq/trainer.py30logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/benchmark/dummy_masked_lm.py18logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/benchmark/dummy_lm.py18logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/benchmark/dummy_mt.py14logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/fairseq_task.py21logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/hubert_pretraining.py22logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/multilingual_denoising.py27logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/denoising.py29logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/multilingual_translation.py26logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/language_modeling.py38logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/speech_to_text.py20logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/legacy_masked_lm.py19logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/online_backtranslation.py38logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/simultaneous_translation.py20logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/text_to_speech.py26logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/audio_pretraining.py24logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/translation.py36logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/semisupervised_translation.py29logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/frm_text_to_speech.py17logger = logging.getLogger(__name__)CODE
LOWedgelm/fairseq/tasks/sentence_prediction.py36logger = logging.getLogger(__name__)CODE
624 more matches not shown…
Hallucination Indicators29 hits · 400 pts
SeverityFileLineSnippetContext
CRITICAL⚡unilm-v1/src/pytorch_pretrained_bert/modeling.py1002 layer.attention.output.dense.weight.data.div_(CODE
CRITICAL⚡unilm-v1/src/pytorch_pretrained_bert/modeling.py1004 layer.output.dense.weight.data.div_(math.sqrt(2.0*(layer_id + 1)))CODE
CRITICALedgelm/examples/truncated_bptt/transformer_xl_model.py94 if all(p is None for p in self.model.crit.out_projs._parameters.values()):CODE
CRITICAL⚡beit3/modeling_finetune.py76 self.head.dense1.weight.data.mul_(init_scale)CODE
CRITICAL⚡beit3/modeling_finetune.py77 self.head.dense1.bias.data.mul_(init_scale)CODE
CRITICAL⚡beit3/modeling_finetune.py80 self.head.dense2.weight.data.mul_(init_scale)CODE
CRITICAL⚡beit3/modeling_finetune.py81 self.head.dense2.bias.data.mul_(init_scale)CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py45 init_ws.append(layer.attention.self.query.weight.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py46 init_bs.append(layer.attention.self.query.bias.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py47 init_ws.append(layer.attention.self.key.weight.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py48 init_bs.append(layer.attention.self.key.bias.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py49 init_ws.append(layer.attention.self.value.weight.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py50 init_bs.append(layer.attention.self.value.bias.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py51 init_ws.append(layer.attention.output.dense.weight.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py52 init_bs.append(layer.attention.output.dense.bias.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py53 init_ws.append(layer.attention.output.LayerNorm.weight.detach().clone())CODE
CRITICAL⚡PFPO/general_util/lightseq_utils.py54 init_bs.append(layer.attention.output.LayerNorm.bias.detach().clone())CODE
CRITICAL…lmv3/examples/object_detection/ditod/mycheckpointer.py25 N2, C2, H, W = model.backbone.bottom_up.backbone.absolute_pos_embed.size()CODE
CRITICAL…airseq/examples/truncated_bptt/transformer_xl_model.py92 if all(p is None for p in self.model.crit.out_projs._parameters.values()):CODE
CRITICAL⚡layoutreader/s2s_ft/modeling_decoding.py941 layer.attention.output.dense.weight.data.div_(CODE
CRITICAL⚡layoutreader/s2s_ft/modeling_decoding.py943 layer.output.dense.weight.data.div_(math.sqrt(2.0 * (layer_id + 1)))CODE
CRITICAL⚡layoutreader/s2s_ft/modeling_decoding.py1029 layer.attention.output.dense.weight.data.div_(CODE
CRITICAL⚡layoutreader/s2s_ft/modeling_decoding.py1031 layer.output.dense.weight.data.div_(math.sqrt(2.0 * (layer_id + 1)))CODE
CRITICAL⚡s2s-ft/s2s_ft/modeling_decoding.py881 layer.attention.output.dense.weight.data.div_(CODE
CRITICAL⚡s2s-ft/s2s_ft/modeling_decoding.py883 layer.output.dense.weight.data.div_(math.sqrt(2.0 * (layer_id + 1)))CODE
CRITICALtrocr/trocr_models.py367 decoder.embed_tokens.load_state_dict(roberta.model.encoder.sentence_encoder.embed_tokens.state_dict())CODE
CRITICALdit/text_detection/ditod/mycheckpointer.py26 N2, C2, H, W = model.backbone.bottom_up.backbone.absolute_pos_embed.size()CODE
CRITICALdit/object_detection/ditod/mycheckpointer.py24 N2, C2, H, W = model.backbone.bottom_up.backbone.absolute_pos_embed.size()CODE
CRITICAL…airseq/examples/truncated_bptt/transformer_xl_model.py94 if all(p is None for p in self.model.crit.out_projs._parameters.values()):CODE
Excessive Try-Catch Wrapping207 hits · 244 pts
SeverityFileLineSnippetContext
LOWvlmo/vlmo/datasets/base_dataset.py157 except Exception as e:CODE
MEDIUMvlmo/vlmo/datasets/base_dataset.py158 print(f"Error while read file idx {index} in {self.names[0]} -> {e}")CODE
LOWvlmo/vlmo/datasets/base_dataset.py172 except Exception as e:CODE
MEDIUMvlmo/vlmo/datasets/base_dataset.py173 print(f"Error while read file idx {index} in {self.names[0]} -> {e}")CODE
LOWinfoxlm/fairseq/fairseq/pdb.py19except Exception:CODE
LOWinfoxlm/fairseq/fairseq/checkpoint_utils.py226 except Exception:CODE
LOWinfoxlm/fairseq/fairseq/trainer.py201 except Exception:CODE
LOW…/examples/speech_recognition/datasets/asr_prep_json.py88 except Exception as exc:CODE
LOWYOCO/yoco/tasks/data/lm_loader.py284 except Exception as e:CODE
LOWedgelm/setup.py33 except Exception:CODE
LOWedgelm/fairseq/pdb.py19except Exception:CODE
LOWedgelm/fairseq/checkpoint_utils.py547 except Exception:CODE
LOWedgelm/fairseq/file_utils.py151 except Exception:CODE
LOWedgelm/fairseq/file_io.py173 except Exception:CODE
LOWedgelm/fairseq/trainer.py513 except Exception:CODE
LOWedgelm/fairseq/tasks/online_backtranslation.py81 except Exception:CODE
LOWedgelm/fairseq/tasks/sentence_prediction.py147 except Exception as e:CODE
LOWedgelm/fairseq/data/multi_corpus_dataset.py168 except Exception as e:CODE
LOWedgelm/fairseq/data/multi_corpus_dataset.py184 except Exception:CODE
LOWedgelm/fairseq/data/data_utils.py96 except Exception as e:CODE
LOWedgelm/fairseq/data/iterators.py577 except Exception as e:CODE
LOWedgelm/fairseq/data/audio/data_cfg.py23 except Exception as e:CODE
LOW…/examples/speech_recognition/datasets/asr_prep_json.py117 except Exception as exc:CODE
LOW…es/MMPT/scripts/video_feature_extractor/videoreader.py72 except Exception:CODE
LOW…es/MMPT/scripts/video_feature_extractor/videoreader.py94 except Exception:CODE
LOW…es/MMPT/scripts/video_feature_extractor/videoreader.py118 except Exception:CODE
LOW…es/MMPT/scripts/video_feature_extractor/videoreader.py211 except Exception:CODE
LOW…es/MMPT/scripts/video_feature_extractor/videoreader.py237 except Exception:CODE
LOWedgelm/examples/truncated_bptt/transformer_xl_model.py98 except Exception:CODE
MEDIUMedgelm/examples/truncated_bptt/transformer_xl_model.py52def __init__(self, cfg, task):CODE
LOW…xamples/speech_synthesis/preprocessing/vad/__init__.py150 except Exception:CODE
LOWPFPO/trainer_base_ds_mul_fs_tp.py401 except Exception as e:CODE
LOWPFPO/trainer_ds_megatron_mul.py392 except Exception as e:CODE
LOWPFPO/scripts/execute_mbpp_intermediate_res.py82 except Exception as e:STRING
LOWPFPO/scripts/verify_mbpp_test_cases.py24 except Exception as e:CODE
LOW…math_scale/rerank_w_prm_math_scale_save_pair_margin.py31 except Exception as e:CODE
MEDIUM…math_scale/rerank_w_prm_math_scale_save_pair_margin.py32 print(f"Error in {file}: {e}")CODE
MEDIUMPFPO/scripts/math_scale/construct_prefer_pair_sc.py114 print(f"Error in file {file}")CODE
MEDIUMPFPO/scripts/math_scale/construct_prefer_pair_sc.py121 print(f"Error in line: {line}")CODE
LOWPFPO/scripts/math_scale/rerank_w_prm_math_scale_save.py31 except Exception as e:CODE
MEDIUMPFPO/scripts/math_scale/rerank_w_prm_math_scale_save.py32 print(f"Error in {file}: {e}")CODE
LOWPFPO/scripts/math_scale/qwen25math_style_eval.py162 except Exception as error:CODE
MEDIUMPFPO/scripts/math_scale/construct_prefer_pair.py63 print(f"Error in file {file}")CODE
MEDIUMPFPO/scripts/math_scale/construct_prefer_pair.py70 print(f"Error in line: {line}")CODE
LOW…cripts/math_scale/rerank_w_prm_math_scale_save_pair.py31 except Exception as e:CODE
MEDIUM…cripts/math_scale/rerank_w_prm_math_scale_save_pair.py32 print(f"Error in {file}: {e}")CODE
LOWPFPO/scripts/math_scale/qwen25math_style_eval_math.py142 except Exception as error:CODE
LOWPFPO/scripts/math_scale/qwen25math_style_eval_v2.0.py180 except Exception as error:CODE
MEDIUMPFPO/scripts/math/merge_dp_predictions.py91 # print(f"Error in {item['id']} during evaluation: {e}")COMMENT
LOWPFPO/scripts/apps/solution_run_pseudo_outputs_local.py34 except Exception as e:CODE
LOWPFPO/scripts/apps/solution_run_pseudo_outputs_local.py57 except Exception as e:CODE
MEDIUMPFPO/scripts/apps/utils_execute.py93def _temp_run(problem, generation, debug, result, return_output):CODE
MEDIUMPFPO/scripts/apps/utils_execute.py141def _temp_run(problem, generation, debug, result, return_output):CODE
LOW⚡PFPO/scripts/apps/utils_execute.py486 except Exception as e:CODE
LOW⚡PFPO/scripts/apps/utils_execute.py494 except Exception as e:CODE
LOW⚡PFPO/scripts/apps/utils_execute.py501 except Exception as e:CODE
LOWPFPO/scripts/apps/utils_execute.py102 except Exception as e:CODE
LOWPFPO/scripts/apps/utils_execute.py150 except Exception as e:CODE
LOWPFPO/scripts/apps/utils_execute.py229 except Exception as e:CODE
LOWPFPO/scripts/apps/utils_execute.py275 except Exception as e:CODE
147 more matches not shown…
Self-Referential Comments52 hits · 153 pts
SeverityFileLineSnippetContext
MEDIUMinfoxlm/fairseq/fairseq/modules/beamable_mm.py11 """This module provides an optimized MM for beam decoding with attention.STRING
MEDIUMinfoxlm/fairseq/docs/conf.py7# This file is execfile()d with the current directory set to itsCOMMENT
MEDIUMmarkuplm/examples/fine_tuning/run_swde/prepare_data.py439 # Define the fixed-text nodes and variable nodes.COMMENT
MEDIUM…rkuplm/markuplmft/models/markuplm/modeling_markuplm.py169 # Create the position ids from the input token ids. Any padded tokens remain padded.COMMENT
MEDIUMedgelm/tests/gpu/transformer_quantization_config.yaml6# This file defines example configuration arguments for quantizingCOMMENT
MEDIUMedgelm/fairseq/sequence_generator.py661 # Create a set of "{sent}{unfin_idx}", whereCOMMENT
MEDIUMedgelm/fairseq/modules/beamable_mm.py11 """This module provides an optimized MM for beam decoding with attention.STRING
MEDIUMedgelm/docs/conf.py7# This file is execfile()d with the current directory set to itsCOMMENT
MEDIUM…mples/quant_noise/transformer_quantization_config.yaml6# This file defines example configuration arguments for quantizingCOMMENT
MEDIUMPFPO/scripts/execute_mbpp_intermediate_res.py69 # Create a StringIO stream to capture outputSTRING
MEDIUMPFPO/scripts/verify_mbpp_test_cases.py10 # Create a StringIO stream to capture outputCOMMENT
MEDIUMPFPO/scripts/execute_mbpp_intermediate_res_mp.py62 # Create a StringIO stream to capture outputCOMMENT
MEDIUMPFPO/scripts/math_scale/analyze/draw_sc.py16 # Create the line plotCOMMENT
MEDIUMPFPO/scripts/math_scale/analyze/freq2image.py11 # Create the bar chartCOMMENT
MEDIUMPFPO/scripts/math_scale/analyze/freq2image.py45 # Create the line plotCOMMENT
MEDIUMPFPO/scripts/mbpp/run_test_case_v1.0.py28 # Create a StringIO stream to capture outputCOMMENT
MEDIUMPFPO/scripts/apps/analyze/freq2image.py29 # Create a bar chart for the three metricsCOMMENT
MEDIUMPFPO/scripts/apps/analyze/freq2image.py61 # Create the line plotCOMMENT
MEDIUMPFPO/data/qwen25math/python_executor.py208 # Define the matrixSTRING
MEDIUMPFPO/data/qwen25math/math_utils.py265 pred = "To find the minimum value of $f(x)$, we need to find the critical points where the derivative of $f(x)$ is eCODE
MEDIUM…v3/layoutlmft/models/layoutlmv3/modeling_layoutlmv3.py158 # Create the position ids from the input token ids. Any padded tokens remain padded.COMMENT
MEDIUMdecoding/GAD/fairseq/modules/beamable_mm.py11 """This module provides an optimized MM for beam decoding with attention.STRING
MEDIUM…fairseq/tests/gpu/transformer_quantization_config.yaml6# This file defines example configuration arguments for quantizingCOMMENT
MEDIUMdecoding/IAD/fairseq/fairseq/modules/beamable_mm.py11 """This module provides an optimized MM for beam decoding with attention.STRING
MEDIUMdecoding/IAD/fairseq/docs/conf.py7# This file is execfile()d with the current directory set to itsCOMMENT
MEDIUM…mples/quant_noise/transformer_quantization_config.yaml6# This file defines example configuration arguments for quantizingCOMMENT
MEDIUMxtune/src/transformers/modeling_tf_roberta.py76 # Create the position ids from the input token ids. Any padded tokens remain padded.COMMENT
MEDIUMxtune/src/transformers/tokenization_openai.py284 # Create the normalizer structureCOMMENT
MEDIUMxtune/src/transformers/tokenization_transfo_xl.py373 # Create the correct normalization pathCOMMENT
MEDIUMxtune/src/transformers/modeling_roberta.py57 # Create the position ids from the input token ids. Any padded tokens remain padded.COMMENT
MEDIUMspeecht5/speecht5/sequence_generator.py753 # Create a set of "{sent}{unfin_idx}", whereCOMMENT
MEDIUMtextdiffuser-2/train_textdiffuser2_t2i_full.py1099 # Create the pipeline using the trained modules and save it.COMMENT
MEDIUMtextdiffuser-2/train_textdiffuser2_inpainting_full.py1127 # Create the pipeline using the trained modules and save it.COMMENT
MEDIUM…ser-2/extensions/train_textdiffuser2_t2i_full_angle.py1120 # Create the pipeline using the trained modules and save it.COMMENT
MEDIUM…tensions/train_textdiffuser2_t2i_full_quadrilateral.py1090 # Create the pipeline using the trained modules and save it.COMMENT
MEDIUM⚡textdiffuser/util.py6# This file defines a set of commonly used utility functions.COMMENT
MEDIUM⚡textdiffuser/gradio_app.py6# This file provides the inference script.COMMENT
MEDIUM⚡textdiffuser/train.py6# This file provides the inference script.COMMENT
MEDIUMtextdiffuser/train.py1075 # Create the pipeline using the trained modules and save it.COMMENT
MEDIUM⚡textdiffuser/inference.py6# This file provides the inference script.COMMENT
MEDIUM⚡textdiffuser/evaluate.py6# This file provides the inference script.COMMENT
MEDIUM⚡textdiffuser/eval/MARIOEval_generate.py6# This file provides the inference script.COMMENT
MEDIUM⚡textdiffuser/eval/ocr_eval.py6# This file provides the inference script.COMMENT
MEDIUM⚡textdiffuser/eval/MARIOEval_evaluate.py6# This file provides the inference script.COMMENT
MEDIUM…smos-2/torchscale/torchscale/component/xmoe/routing.py64 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUM…smos-2/torchscale/torchscale/component/xmoe/routing.py284 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUM…smos-2/torchscale/torchscale/component/xmoe/routing.py288 # Create a mask for 2nd's expert per token using Gumbel-max trickCOMMENT
MEDIUMkosmos-2/unilm/models/vl/vlm_generator.py648 # Create a set of "{sent}{unfin_idx}", whereCOMMENT
MEDIUMkosmos-2/fairseq/fairseq/sequence_generator.py745 # Create a set of "{sent}{unfin_idx}", whereCOMMENT
MEDIUMkosmos-2/fairseq/fairseq/modules/beamable_mm.py11 """This module provides an optimized MM for beam decoding with attention.STRING
MEDIUMkosmos-2/fairseq/docs/conf.py7# This file is execfile()d with the current directory set to itsCOMMENT
MEDIUM…mples/quant_noise/transformer_quantization_config.yaml6# This file defines example configuration arguments for quantizingCOMMENT
Docstring Block Structure27 hits · 135 pts
SeverityFileLineSnippetContext
HIGHedgelm/examples/MMPT/mmpt/models/mmfusionnlg.py245 Generates sequences for models with a language modeling head. The method currently supports greedy decoding, STRING
HIGHPFPO/eval/mbpp_eval/utils.py60 Calculates how good are predictions given some references, using certain scores Args: predictions: list of candidatSTRING
HIGHxtune/src/transformers/configuration_utils.py122 Instantiate a :class:`~transformers.PretrainedConfig` (or a derived class) from a pre-trained model configuratSTRING
HIGHxtune/src/transformers/modeling_tf_bert.py133Get token embeddings of inputs. Args: inputs: list of three int64 tensors with shape [batch_size, leSTRING
HIGHxtune/src/transformers/tokenization_utils.py624 Add a list of new tokens to the tokenizer class. If the new tokens are not in the vocabulary, they are STRING
HIGHxtune/src/transformers/tokenization_utils.py691 Add a dictionary of special tokens (eos, pad, cls...) to the encoder and link them to class attributes.STRING
HIGHxtune/src/transformers/modeling_bart.py995 Generates sequences for models with a LM head. The method currently supports greedy or penalized greedy decoding, samplSTRING
HIGHxtune/src/transformers/configuration_auto.py116 Instantiates one of the configuration classes of the library from a pre-trained model configuration. TSTRING
HIGHxtune/src/transformers/modelcard.py89 Instantiate a :class:`~transformers.ModelCard` from a pre-trained model model card. Parameters: prSTRING
HIGHxtune/src/transformers/modeling_tf_distilbert.py98Get token embeddings of inputs. Args: inputs: list of three int64 tensors with shape [batch_size, leSTRING
HIGHxtune/src/transformers/modeling_utils.py302Instantiate a pretrained pytorch model from a pre-trained model configuration. The model is set in evaluation mSTRING
HIGHxtune/src/transformers/modeling_tf_albert.py82Get token embeddings of inputs. Args: inputs: list of three int64 tensors with shape [batch_size, leSTRING
HIGHxtune/src/transformers/pipelines.py1247 Utility factory method to build a pipeline. Pipeline are made of: - A Tokenizer instance in charge ofSTRING
HIGHxtune/src/transformers/modeling_tf_utils.py193Instantiate a pretrained TF 2.0 model from a pre-trained model configuration. The warning ``Weights from XXX noSTRING
HIGHxtune/src/transformers/modeling_tf_utils.py1154Get token embeddings of inputs. Args: inputs: list of three int64 tensors with shape [batch_size, leSTRING
HIGHxtune/src/transformers/data/processors/xtreme.py44 Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.dSTRING
HIGHxtune/src/transformers/data/processors/squad.py284 Converts a list of examples into a list of features that can be directly given as input to a model. It is modelSTRING
HIGHxtune/src/transformers/data/processors/squad.py469 Creates a list of :class:`~transformers.data.processors.squad.SquadExample` using a TFDS dataset. ArgsSTRING
HIGHxtune/src/transformers/data/processors/glue.py43 Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.dSTRING
HIGHxtune/src/transformers/data/processors/xglue.py45 Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.dSTRING
HIGHxtune/src/transformers/data/processors/xglue.py187 Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.dSTRING
HIGH…echt5/speecht5/models/modules/speech_decoder_prenet.py92Make masks for self-attention. Args: ilens (LongTensor or List): Batch of lengths (B,). RetuSTRING
HIGH…/fairseq/fairseq/modules/espnet_multihead_attention.py220Compute rotary position attention. Args: query: Query tensor T X B X C key: Key tensor TSTRING
HIGH…mos-2/fairseq/examples/MMPT/mmpt/models/mmfusionnlg.py245 Generates sequences for models with a language modeling head. The method currently supports greedy decoding, STRING
HIGHadalm/finetune/utils_for_glue.py142 Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.dSTRING
HIGHadalm/incr_bpe/text_encoder.py180Escape away underscores and OOV characters and append '_'. This allows the token to be expressed as the concatenationSTRING
HIGHadalm/incr_bpe/text_encoder.py472Builds a SubwordTextEncoder that has `vocab_size` near `target_size`. Uses simple recursive binary search to findSTRING
Fake / Example Data44 hits · 52 pts
SeverityFileLineSnippetContext
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py345 def calc_gradient_penalty(self, real_data, fake_data):CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py347 b_size = min(real_data.size(0), fake_data.size(0))CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py348 t_size = min(real_data.size(1), fake_data.size(1))CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py364 fake_data = get_slice(fake_data, 0, b_size)CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py365 fake_data = get_slice(fake_data, 1, t_size)CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py369 fake_data = fake_data[:b_size, :t_size]CODE
LOW⚡…gelm/examples/wav2vec/unsupervised/models/wav2vec_u.py375 interpolates = alpha * real_data + ((1 - alpha) * fake_data)CODE
LOW⚡PFPO/data/deepseek_math_utils/answer_extraction.py291 ans = ['placeholder']CODE
LOW⚡PFPO/data/deepseek_math_utils/answer_extraction.py302 ans = 'placeholder'CODE
LOW⚡PFPO/data/deepseek_math_utils/answer_extraction.py312 return 'placeholder'CODE
LOWPFPO/data/qwen25math/parser.py361 return "placeholder"CODE
LOW⚡xtune/src/transformers/modeling_xlnet.py942 dummy_token = torch.zeros((effective_batch_size, 1), dtype=torch.long, device=input_ids.device)CODE
LOW⚡xtune/src/transformers/modeling_xlnet.py943 input_ids = torch.cat([input_ids, dummy_token], dim=1)CODE
LOW⚡xtune/src/transformers/modeling_tf_xlnet.py844 dummy_token = tf.zeros((effective_batch_size, 1), dtype=tf.int32)CODE
LOW⚡xtune/src/transformers/modeling_tf_xlnet.py845 inputs = tf.concat([inputs, dummy_token], axis=1)CODE
LOWkosmos-2/infinibatch/README.md80'Lorem ipsum dolor sit amet,CODE
LOWkosmos-2/infinibatch/README.md80'Lorem ipsum dolor sit amet,CODE
LOW⚡kosmos-2/infinibatch/README.md126Lorem ipsum dolor sit amet,CODE
LOW⚡kosmos-2/infinibatch/README.md126Lorem ipsum dolor sit amet,CODE
LOW⚡kosmos-2/infinibatch/README.md133Lorem ipsum dolor sit amet,CODE
LOW⚡kosmos-2/infinibatch/README.md133Lorem ipsum dolor sit amet,CODE
LOWkosmos-2/infinibatch/README.md189['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']CODE
LOWkosmos-2/infinibatch/README.md189['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']CODE
LOWkosmos-2/infinibatch/README.md215['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']CODE
LOWkosmos-2/infinibatch/README.md215['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']CODE
LOWkosmos-2/infinibatch/infinibatch/__init__.py69'Lorem ipsum dolor sit amet,STRING
LOWkosmos-2/infinibatch/infinibatch/__init__.py69'Lorem ipsum dolor sit amet,STRING
LOW⚡kosmos-2/infinibatch/infinibatch/__init__.py115Lorem ipsum dolor sit amet,STRING
LOW⚡kosmos-2/infinibatch/infinibatch/__init__.py115Lorem ipsum dolor sit amet,STRING
LOW⚡kosmos-2/infinibatch/infinibatch/__init__.py122Lorem ipsum dolor sit amet,STRING
LOW⚡kosmos-2/infinibatch/infinibatch/__init__.py122Lorem ipsum dolor sit amet,STRING
LOWkosmos-2/infinibatch/infinibatch/__init__.py178['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']STRING
LOWkosmos-2/infinibatch/infinibatch/__init__.py178['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']STRING
LOWkosmos-2/infinibatch/infinibatch/__init__.py204['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']STRING
LOWkosmos-2/infinibatch/infinibatch/__init__.py204['consectetur adipiscing elit,', 'Lorem ipsum dolor sit amet,']STRING
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py345 def calc_gradient_penalty(self, real_data, fake_data):CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py347 b_size = min(real_data.size(0), fake_data.size(0))CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py348 t_size = min(real_data.size(1), fake_data.size(1))CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py364 fake_data = get_slice(fake_data, 0, b_size)CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py365 fake_data = get_slice(fake_data, 1, t_size)CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py369 fake_data = fake_data[:b_size, :t_size]CODE
LOW⚡…rseq/examples/wav2vec/unsupervised/models/wav2vec_u.py375 interpolates = alpha * real_data + ((1 - alpha) * fake_data)CODE
LOWReSA/llm/utils/math_utils.py886 return "placeholder"CODE
LOWReSA/scripts/math_utils.py501 return "placeholder"CODE
AI Slop Vocabulary36 hits · 50 pts
SeverityFileLineSnippetContext
LOWmarkuplm/examples/fine_tuning/run_websrc/utils.py65 # the difference between T-PLM and H-PLM is just add <xx> and </xx> into theSTRING
LOWmarkuplm/examples/fine_tuning/run_websrc/utils.py853 # just create a nonce prediction in this case to avoid failure.STRING
LOWedgelm/fairseq/checkpoint_utils.py232 # else just use usual logic to load checkpoint, e.g. restart from last checkpoint and etc.COMMENT
LOWedgelm/fairseq/data/squad/squad_extractor.py211 # "Japanese", we just use "Japanese" as the annotation. This is fairly rareCOMMENT
LOWedgelm/fairseq/data/squad/squad_metrics.py296 # can fail in certain cases in which case we just return `orig_text`.COMMENT
LOWedgelm/fairseq/data/squad/squad_metrics.py547 # So we just create a nonce prediction in this case to avoid failure.COMMENT
LOWedgelm/fairseq/data/squad/squad_metrics.py552 # just create a nonce prediction in this case to avoid failure.COMMENT
MEDIUM…latent_depth/latent_depth_src/modules/latent_layers.py27 """To leverage the efficiency of distributed training, samples for allSTRING
MEDIUMedgelm/examples/MMPT/mmpt/tasks/retritask.py242 # we moved the center to make cluster robust.COMMENT
MEDIUMPFPO/scripts/execute_mbpp_intermediate_res.py19_running_code_judge_template_0 = """I will show you a programming problem. You will first be given the instruction aboutSTRING
MEDIUMPFPO/scripts/execute_mbpp_intermediate_res.py43_running_code_judge_template_1 = """I will show you a programming problem. You will first be given the instruction aboutSTRING
LOWdecoding/GAD/fairseq/checkpoint_utils.py170 # else just use usual logic to load checkpoint, e.g. restart from last checkpoint and etc.COMMENT
LOWdecoding/IAD/fairseq/fairseq/checkpoint_utils.py170 # else just use usual logic to load checkpoint, e.g. restart from last checkpoint and etc.COMMENT
MEDIUM…latent_depth/latent_depth_src/modules/latent_layers.py27 """To leverage the efficiency of distributed training, samples for allSTRING
MEDIUMbeit2/run_class_finetuning.py47 # robust evaluationCOMMENT
LOWxdoc/fine_tuning/websrc/websrc.py329 # the difference between T-PLM and H-PLM is just add <xx> and </xx> into theSTRING
LOWxdoc/fine_tuning/websrc/trainer.py499 # just create a nonce prediction in this case to avoid failure.STRING
LOWxtune/src/transformers/modeling_utils.py1507 # We can probably just use the multi-head attention module of PyTorch >=1.1.0STRING
LOWxtune/src/transformers/modeling_tf_utils.py1217 # We can probably just use the multi-head attention module of PyTorch >=1.1.0STRING
LOWxtune/src/transformers/data/metrics/squad_metrics.py268 # can fail in certain cases in which case we just return `orig_text`.COMMENT
LOWxtune/src/transformers/data/metrics/squad_metrics.py516 # So we just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/transformers/data/metrics/squad_metrics.py521 # just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/transformers/data/metrics/squad_metrics.py717 # just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/pequod/data/utils_squad.py424 # "Japanese", we just use "Japanese" as the annotation. This is fairly rareCOMMENT
LOWxtune/src/pequod/data/utils_squad.py611 # So we just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/pequod/data/utils_squad.py617 # just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/pequod/data/utils_squad.py809 # just create a nonce prediction in this case to avoid failure.COMMENT
LOWxtune/src/pequod/data/utils_squad.py894 # can fail in certain cases in which case we just return `orig_text`.COMMENT
MEDIUMtextdiffuser-2/train_textdiffuser2_t2i_lora.py776 random.shuffle(ocrs_temp) #### augment the ocr sequence for robust trainingSTRING
MEDIUMtextdiffuser-2/train_textdiffuser2_t2i_full.py739 random.shuffle(ocrs_temp) #### augment the ocr sequence for robust trainingCODE
MEDIUM…ser-2/extensions/train_textdiffuser2_t2i_full_angle.py760 random.shuffle(ocrs_temp) #### augment the ocr sequence for robust trainingCODE
MEDIUM…tensions/train_textdiffuser2_t2i_full_quadrilateral.py743 random.shuffle(ocrs_temp) #### augment the ocr sequence for robust trainingCODE
LOWtextdiffuser-2/assets/attention_processor.py520 # here we simply pass along all tensors to the selected processor classSTRING
LOWkosmos-2/fairseq/fairseq/checkpoint_utils.py244 # else just use usual logic to load checkpoint, e.g. restart from last checkpoint and etc.COMMENT
MEDIUM…latent_depth/latent_depth_src/modules/latent_layers.py27 """To leverage the efficiency of distributed training, samples for allSTRING
MEDIUMkosmos-2/fairseq/examples/MMPT/mmpt/tasks/retritask.py242 # we moved the center to make cluster robust.COMMENT
Cross-Language Confusion11 hits · 50 pts
SeverityFileLineSnippetContext
HIGHPFPO/data/qwen25math/math_utils.py130 return ans_p.equals(ans_l)CODE
HIGHPFPO/data/qwen25math/grader.py300 if a.equals(b) or simplify(a - b) == 0:CODE
HIGHPFPO/data/qwen25math/grader.py324 if _a.equals(_b):CODE
HIGHxtune/src/transformers/tokenization_xlm.py693 logger.error("1. git clone git@github.com:neubig/kytea.git && cd kytea")CODE
HIGHxtune/src/transformers/tokenization_xlm.py696 logger.error("4. make && make install")CODE
HIGHxtune/src/transformers/tokenization_xlm.py764 git clone git@github.com:neubig/kytea.git && cd kyteaSTRING
HIGHxtune/src/transformers/tokenization_xlm.py767 make && make installSTRING
HIGHReSA/llm/utils/math_utils.py1677 if a.equals(b) or simplify(a - b) == 0:CODE
HIGHReSA/llm/utils/math_utils.py1701 if _a.equals(_b):CODE
HIGHReSA/scripts/math_utils.py1292 if a.equals(b) or simplify(a - b) == 0:CODE
HIGHReSA/scripts/math_utils.py1316 if _a.equals(_b):CODE
Slop Phrases30 hits · 50 pts
SeverityFileLineSnippetContext
LOWinfoxlm/fairseq/fairseq/tasks/translation_lev.py98 target_length = target_length + 1 # make sure to mask at least one token.CODE
MEDIUM⚡…lmft/layoutlmft/models/layoutlmv2/detectron2_config.py11 # Otherwise, you can use [57.375, 57.120, 58.395] (ImageNet std)COMMENT
LOWYOCO/yoco/tasks/data/tiktoken_tokenizer.py19 # If you're changing the set of special tokens, make sure to use a different nameCOMMENT
LOWedgelm/fairseq/tasks/translation_lev.py118 target_length = target_length + 1 # make sure to mask at least one token.CODE
MEDIUM…amples/wav2vec/unsupervised/kaldi_self_train/st/cmd.sh1# you can change cmd.sh depending on what type of queue you are using.COMMENT
MEDIUM…nsupervised/kaldi_self_train/st/steps_gan/train_sat.sh15exit_stage=-100 # you can use this to require it to exit at theCODE
MEDIUMlayoutlmv3/layoutlmft/data/cord.py56 # Or you can use the following links. Please follow the original LICENSE of CORD for usage.STRING
LOW…ng/GAD/block_plugins/tasks/translation_lev_modified.py138 target_length = target_length + 1 # make sure to mask at least one token.CODE
LOW…ng/GAD/block_plugins/tasks/translation_lev_modified.py165 cutoff_length = cutoff_length.int() + 1 # make sure to mask at least one token.CODE
LOWdecoding/GAD/fairseq/tasks/translation_lev.py118 target_length = target_length + 1 # make sure to mask at least one token.CODE
LOWdecoding/IAD/fairseq/fairseq/tasks/translation_lev.py116 target_length = target_length + 1 # make sure to mask at least one token.CODE
MEDIUM⚡…unsd/layoutlmft/models/layoutlmv2/detectron2_config.py11 # Otherwise, you can use [57.375, 57.120, 58.395] (ImageNet std)COMMENT
LOWxtune/src/transformers/modeling_tf_xlm.py477 # Sometimes XLM has language embeddings so don't forget to build them as well if neededCOMMENT
LOWxtune/src/transformers/modeling_tf_xlm.py477 # Sometimes XLM has language embeddings so don't forget to build them as well if neededCOMMENT
MEDIUMxtune/src/transformers/configuration_openai.py71 Whether special tokens should be predicted when the model is has a language modeling head.STRING
LOWtextdiffuser-2/train_textdiffuser2_t2i_full.py589 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser-2/train_textdiffuser2_inpainting_full.py595 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser-2/inference_textdiffuser2_t2i_full.py382 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOW…ser-2/extensions/train_textdiffuser2_t2i_full_angle.py595 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOW…tensions/train_textdiffuser2_t2i_full_quadrilateral.py589 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOW…2/extensions/inference_textdiffuser2_t2i_full_angle.py387 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOW…ions/inference_textdiffuser2_t2i_full_quadrilateral.py383 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser-2/assets/attention_processor.py389 # Don't forget to remove ALL `_remove_lora` from the codebaseSTRING
LOWtextdiffuser/gradio_app.py393 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser/train.py537 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser/inference.py389 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWtextdiffuser/evaluate.py396 # make sure to pop weight so that corresponding model is not saved againCOMMENT
LOWkosmos-2/fairseq/fairseq/tasks/translation_lev.py122 target_length = target_length + 1 # make sure to mask at least one token.CODE
MEDIUM…amples/wav2vec/unsupervised/kaldi_self_train/st/cmd.sh1# you can change cmd.sh depending on what type of queue you are using.COMMENT
MEDIUM…nsupervised/kaldi_self_train/st/steps_gan/train_sat.sh15exit_stage=-100 # you can use this to require it to exit at theCODE
Modern AI Meta-Vocabulary16 hits · 45 pts
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MEDIUMinfoxlm/fairseq/eval_lm.py72 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMinfoxlm/fairseq/fairseq_cli/eval_lm.py72 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMedgelm/fairseq_cli/eval_lm.py245 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMedgelm/examples/MMPT/README.md86python locallaunch.py projects/retri/videoclip/test_youcook_zs.yaml --jobtype local_predict # zero-shot evaluation.CODE
MEDIUMedgelm/examples/MMPT/mmpt/evaluators/predictor.py484 # logic of zero-shot for sequence labeling.COMMENT
MEDIUMPFPO/data/qwen25math/parser.py535 # Handle Chinese few-shot multiple choice problem answer extractionCOMMENT
MEDIUMdecoding/GAD/fairseq_cli/eval_lm.py245 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMdecoding/IAD/fairseq/fairseq_cli/eval_lm.py245 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMkosmos-2/fairseq/fairseq/sequence_generator.py347 if len(img_token_size) == 5: # few-shot setting, [B, K-shot, D(3, 244, 244)]CODE
MEDIUMkosmos-2/fairseq/fairseq/sequence_generator.py888 # elif False: #TODO: skip this for text zero-shotCOMMENT
MEDIUMkosmos-2/fairseq/fairseq_cli/eval_lm.py245 # reduce tokens per sample by the required context window sizeCOMMENT
MEDIUMkosmos-2/fairseq/examples/MMPT/README.md86python locallaunch.py projects/retri/videoclip/test_youcook_zs.yaml --jobtype local_predict # zero-shot evaluation.CODE
MEDIUM…s-2/fairseq/examples/MMPT/mmpt/evaluators/predictor.py484 # logic of zero-shot for sequence labeling.COMMENT
MEDIUMkosmos-2/open_clip/README.md275### Evaluating hosted pretrained checkpoint on ImageNet zero-shot prediction:COMMENT
MEDIUMReSA/llm/utils/math_utils.py1060 # Handle Chinese few-shot multiple choice problem answer extractionCOMMENT
MEDIUMReSA/scripts/math_utils.py675 # Handle Chinese few-shot multiple choice problem answer extractionCOMMENT
Dead Code20 hits · 40 pts
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MEDIUMinfoxlm/fairseq/fairseq/data/data_utils.py283CODE
MEDIUMinfoxlm/fairseq/fairseq/data/data_utils.py311CODE
MEDIUMinfoxlm/fairseq/fairseq/data/data_utils.py313CODE
MEDIUMinfoxlm/fairseq/fairseq/data/data_utils.py314CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py509CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py529CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py530CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py533CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py534CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py535CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py536CODE
MEDIUMedgelm/examples/MMPT/mmpt/processors/dsprocessor.py543CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py509CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py529CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py530CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py533CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py534CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py535CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py536CODE
MEDIUM…2/fairseq/examples/MMPT/mmpt/processors/dsprocessor.py543CODE
Structural Annotation Overuse16 hits · 32 pts
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LOWvlmo/README.md43### Step 1: Vision Pre-TrainingCOMMENT
LOWvlmo/README.md47### Step 2: Language Pre-Training (VLMo-Base)COMMENT
LOWvlmo/README.md60### Step 3: Vision-Language Pre-Training (VLMo-Base)COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt65### Step 1: Substitute \( t = -2 \) into \( p(t) \):COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt70### Step 2: Simplify the exponent:COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt79### Step 3: Simplify \( 4^{-3} \):COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt84### Step 4: Substitute \( 4^{-3} \) into \( p(-2) \):COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt89### Step 5: Simplify the multiplication:COMMENT
LOW⚡PFPO/prompts/math/college_math_4shot.txt94### Step 6: Add \( -\frac{1}{32} \) and \( 1 \):COMMENT
LOWPFPO/prompts/math/college_math_4shot.txt116### Step 1: Factorize where possibleCOMMENT
LOWPFPO/prompts/math/college_math_4shot.txt127### Step 2: Simplify common termsCOMMENT
LOW⚡dit/object_detection/inference.py43 # Step 1: instantiate configCOMMENT
LOW⚡dit/object_detection/inference.py48 # Step 2: add model weights URL to configCOMMENT
LOW⚡dit/object_detection/inference.py51 # Step 3: set deviceCOMMENT
LOW⚡dit/object_detection/inference.py55 # Step 4: define modelCOMMENT
LOW⚡dit/object_detection/inference.py58 # Step 5: run inferenceCOMMENT
Redundant / Tautological Comments22 hits · 30 pts
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LOWminilm/examples/run_xnli.py110 # Check if saved optimizer or scheduler states existCOMMENT
LOWminilm/examples/run_xnli.py152 # Check if continuing training from a checkpointCOMMENT
LOW…oxlm/fairseq/fairseq/tasks/multilingual_translation.py263 # Check if task args are consistant with model argsCOMMENT
LOWedgelm/fairseq/tasks/multilingual_translation.py314 # Check if task args are consistant with model argsCOMMENT
LOWedgelm/examples/MMPT/mmpt/models/mmfusionnlg.py807 # Check if we are done so that we can save a pad step if all(done)COMMENT
LOWPFPO/post_processors/pattern/tags.py11 # Check if there's exactly one pair of tagsCOMMENT
LOWPFPO/post_processors/pattern/tags.py24 # Check if there's exactly one pair of tagsCOMMENT
LOWPFPO/post_processors/pattern/tags.py37 # Check if there's exactly one pair of tagsCOMMENT
LOWdecoding/GAD/fairseq/tasks/multilingual_translation.py309 # Check if task args are consistant with model argsCOMMENT
LOW…/IAD/fairseq/fairseq/tasks/multilingual_translation.py309 # Check if task args are consistant with model argsCOMMENT
LOWxtune/src/run_qa.py797 # Check if saved optimizer or scheduler states existCOMMENT
LOWxtune/src/run_qa.py840 # Check if continuing training from a checkpointCOMMENT
LOWxtune/src/run_cls.py607 # Check if saved optimizer or scheduler states existCOMMENT
LOWxtune/src/run_cls.py649 # Check if continuing training from a checkpointCOMMENT
LOWxtune/src/transformers/modeling_bart.py1171 # Check if were done so that we can save a pad step if all(done)STRING
LOWxtune/src/transformers/modeling_tf_utils.py359 # Check if the models are the same to output loading informationsSTRING
LOWtextdiffuser/assets/files/modeling_utils.py457 # Check if we can handle device_map and dispatching the weightsSTRING
LOW…os-2/fairseq/fairseq/tasks/multilingual_translation.py314 # Check if task args are consistant with model argsCOMMENT
LOW…mos-2/fairseq/examples/MMPT/mmpt/models/mmfusionnlg.py807 # Check if we are done so that we can save a pad step if all(done)COMMENT
LOWadalm/finetune/run_ner.py127 # Check if saved optimizer or scheduler states existCOMMENT
LOWadalm/finetune/run_pico.py147 # Check if saved optimizer or scheduler states existCOMMENT
LOWReSA/llm/kernel/tilelang_sparse_decoding.py466 cache_seqlens[random_index] = max_cache_seqlen # Assign cache_seqlen to ensure at least one occurrenceCODE
Verbosity Indicators5 hits · 11 pts
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LOW⚡dit/object_detection/inference.py43 # Step 1: instantiate configCOMMENT
LOW⚡dit/object_detection/inference.py48 # Step 2: add model weights URL to configCOMMENT
LOW⚡dit/object_detection/inference.py51 # Step 3: set deviceCOMMENT
LOW⚡dit/object_detection/inference.py55 # Step 4: define modelCOMMENT
LOW⚡dit/object_detection/inference.py58 # Step 5: run inferenceCOMMENT
TODO Padding2 hits · 3 pts
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LOWPFPO/data/vllm.py85 # TODO: Add error processing here (need to remove `get_response` method)COMMENT
LOWkosmos-2/infinibatch/test/test_iterators.py581 # TODO: Add test cases for behavior when source iterators end but item is retrievedCOMMENT
Overly Generic Function Names3 hits · 2 pts
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LOWmarkuplm/examples/fine_tuning/run_swde/run.py407def do_something(train_websites, test_websites, args, config, tokenizer):STRING
LOWedgelm/tests/test_roberta.py104 def helper(self):CODE
LOWedgelm/tests/test_roberta.py113 def helper(self):CODE