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PaddlePaddle/PaddleFormers

PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.

27.7 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for PaddlePaddle/PaddleFormers, a Python project with 12,976 GitHub stars. SynthScan examined 404,617 lines of code across 1410 source files, recording 7917 pattern matches distributed across 24 syntactic categories. The legacy adjusted pattern signal is 27.7 (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.

27.7
Adjusted Signal
27.7
Raw Pattern Score
100%
Time Factor
2026-10-10
Last Push
13.0K
Stars
Python
Language
404.6K
Lines of Code
1.4K
Files
7.9K
Pattern Hits
2026-10-12
Scan Date
0.41
HC Hit Rate

Risk Review · v3

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

Cognitive Ownership Risk 56.1/100 · HIGH

Can maintainers explain intent, assumptions, and trade-offs? 6046 finding(s).

Hallucinated Dependency & Supply Chain Risk 16.5/100 · LOW

Are imports declared and package/API names verified? 836 finding(s).

Agent Over-Engineering Ratio 59.2/100 · HIGH

Are wrappers, guards, and repeated structures necessary? 4957 finding(s).

PR Review Velocity Impact 75.9/100 · CRITICAL

Which changes need focused human review? 7917 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

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

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 62HIGH 522MEDIUM 219LOW 7114

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 7917 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.

Hyper-Verbose Identifiers3500 hits · 3760 pts
SeverityFileLineSnippetContext
LOWtests/testing_utils.py82def softmax_with_cross_entropy(logits, label, soft_label=False, axis=-1, ignore_index=-1):CODE
LOWtests/testing_utils.py467def require_paddle_non_multi_gpu(test_case):CODE
LOWtests/mergekit/test_merge_model.py128 def test_fuse_qkv_lora_merge_torch(self):CODE
LOWtests/nn/test_mlp.py39 def test_initialization_default(self):CODE
LOWtests/nn/test_mlp.py52 def test_initialization_fuse_ffn(self):CODE
LOWtests/nn/test_mlp.py63 def test_initialization_non_fuse_ffn(self):CODE
LOW⚡tests/nn/test_criterion.py38 def test_forward_non_fuse_subbatch_sft(self):CODE
LOW⚡tests/nn/test_criterion.py45 def test_forward_with_loss_mask(self):CODE
LOW⚡tests/nn/test_criterion.py50 def test_forward_with_recompute(self):CODE
LOW⚡tests/nn/test_norm.py30 def test_layer_norm_initialization(self):CODE
LOW⚡tests/nn/test_norm.py40 def test_layer_norm_sequence_parallel(self):CODE
LOW⚡tests/nn/test_norm.py50 def test_rms_norm_initialization(self):CODE
LOW⚡tests/nn/test_norm.py59 def test_rms_norm_sequence_parallel(self):CODE
LOWtests/nn/test_lm_head.py24 def test_initialization_default(self):CODE
LOWtests/nn/test_lm_head.py35 def test_initialization_with_tie_word_embeddings(self):CODE
LOWtests/nn/test_lm_head.py50 def test_forward_fused_head_loss(self):CODE
LOW⚡tests/nn/test_attention.py203 def test_forward_calls_correct_function(self):CODE
LOWtests/dataset/test_file_reader.py48 def test_file_samplenum_undersample(self):CODE
LOWtests/dataset/test_file_reader.py56 def test_file_samplenum_oversample(self):CODE
LOWtests/dataset/test_file_reader.py67 def test_unsupported_file_type_raises(self):CODE
LOWtests/dataset/test_file_reader.py76 def test_unsupported_extension_raises(self):CODE
LOWtests/dataset/test_file_reader.py91 def test_filelist_reader_invalid_dir_raises(self):CODE
LOWtests/dataset/test_convertor.py192 def test_erniekit_convertor_dpo(self):CODE
LOWtests/dataset/test_convertor.py207 def test_erniekit_convertor_txt(self):CODE
LOWtests/dataset/test_convertor.py221 def test_erniekit_convertor_mm(self):CODE
LOWtests/dataset/test_convertor.py235 def test_erniekit_convertor_pretrain(self):CODE
LOW⚡tests/dataset/test_collate.py61 def test_pads_to_explicit_max_seq_len(self):CODE
LOW⚡tests/dataset/test_collate.py71 def test_no_cross_segment_attention(self):CODE
LOW⚡tests/dataset/test_collate.py75 def test_global_causal_is_lower_triangular(self):CODE
LOW⚡tests/dataset/test_collate.py81 def test_output_shape_and_dtype(self):CODE
LOW⚡tests/dataset/test_collate.py86 def test_each_token_points_to_segment_end(self):CODE
LOW⚡tests/dataset/test_collate.py92 def test_padding_area_is_ascending(self):CODE
LOWtests/dataset/test_collate.py41 def test_no_parallelism_no_padding(self):CODE
LOWtests/dataset/test_collate.py50 def test_sequence_parallel_uses_tp_size(self):CODE
LOWtests/dataset/test_collate.py123 def test_global_causal_is_lower_triangular(self):CODE
LOWtests/dataset/test_collate.py143 def test_padding_area_is_zero(self):CODE
LOWtests/dataset/test_collate.py153 def test_output_shape_and_dtype(self):CODE
LOWtests/dataset/test_collate.py170 def test_padding_area_is_ascending(self):CODE
LOWtests/dataset/test_collate.py217 def test_output_shape_and_dtype(self):CODE
LOWtests/dataset/test_collate.py243 def test_single_sequence_no_boundary(self):CODE
LOWtests/dataset/test_map_datasets.py82 def test_isinstance_paddle_dataset(self):CODE
LOWtests/dataset/test_map_datasets.py101 def test_len_concat_two_sources(self):CODE
LOW⚡tests/dataset/test_map_datasets.py119 def test_packed_idx_is_none_without_packing(self):CODE
LOW⚡tests/dataset/test_map_datasets.py124 def test_getitem_returns_list(self):CODE
LOW⚡tests/dataset/test_map_datasets.py131 def test_getitem_sequence_fields(self):CODE
LOW⚡tests/dataset/test_map_datasets.py140 def test_getitem_token_ids_within_max_seq_len(self):CODE
LOW⚡tests/dataset/test_map_datasets.py148 def test_getitem_labels_same_length_as_token_ids(self):CODE
LOW⚡tests/dataset/test_map_datasets.py156 def test_getitem_position_ids_same_length_as_token_ids(self):CODE
LOW⚡tests/dataset/test_map_datasets.py164 def test_getitem_single_returns_one_sequence(self):CODE
LOW⚡tests/dataset/test_map_datasets.py200 def test_packed_idx_is_list_of_lists(self):CODE
LOW⚡tests/dataset/test_map_datasets.py209 def test_len_equals_packed_groups(self):CODE
LOW⚡tests/dataset/test_map_datasets.py214 def test_len_packed_le_raw_data(self):CODE
LOW⚡tests/dataset/test_map_datasets.py219 def test_getitem_packed_returns_list(self):CODE
LOW⚡tests/dataset/test_map_datasets.py226 def test_getitem_packed_sequences_within_max_seq_len(self):CODE
LOW⚡tests/dataset/test_map_datasets.py234 def test_packing_only_true_raises(self):CODE
LOWtests/dataset/test_map_datasets.py245 def test_all_packed_indices_valid(self):CODE
LOWtests/dataset/test_map_datasets.py280 def test_cache_loaded_on_second_init(self):CODE
LOWtests/dataset/test_map_datasets.py299 def test_eval_cache_file_name(self):CODE
LOWtests/dataset/test_map_datasets.py312 def test_corrupt_cache_falls_back_to_recompute(self):CODE
LOWtests/dataset/test_mix_datasets.py88 def test_interleave_under_dataset_len(self):CODE
3440 more matches not shown…
Cross-File Repetition387 hits · 1935 pts
SeverityFileLineSnippetContext
HIGH…sts/coverage_test/cli/test_coverage_deepseek_v3_fp8.py0load a module directly from file path without going through __init__.py.STRING
HIGH…/coverage_test/cli/test_coverage_deepseek_v3_kernel.py0load a module directly from file path without going through __init__.py.STRING
HIGH…/coverage_test/cli/test_coverage_deepseek_v3_config.py0load a module directly from file path without going through __init__.py.STRING
HIGH…ts/coverage_test/cli/test_coverage_convert_ckpt_sft.py0load a module directly from file path without going through __init__.py.STRING
HIGH…erage_test/cli/test_coverage_deepseek_v3_token_disp.py0load a module directly from file path without going through __init__.py.STRING
HIGHtests/coverage_test/cli/test_coverage_load_hf_ckpt.py0load a module directly from file path without going through __init__.py.STRING
HIGH…overage_test/cli/test_coverage_deepseek_v3_moe_gate.py0load a module directly from file path without going through __init__.py.STRING
HIGH…overage_test/cli/test_coverage_deepseek_v3_workflow.py0load a module directly from file path without going through __init__.py.STRING
HIGH…verage_test/cli/test_coverage_deepseek_v3_moe_utils.py0load a module directly from file path without going through __init__.py.STRING
HIGH…verage_test/cli/test_coverage_deepseek_v3_moe_layer.py0load a module directly from file path without going through __init__.py.STRING
HIGHtests/transformers/kimi_k25/test_processor.py0tests that special vision tokens do not get truncated when `truncation=true` is set.STRING
HIGHtests/transformers/qwen2_5_vl/test_processor.py0tests that special vision tokens do not get truncated when `truncation=true` is set.STRING
HIGHtests/transformers/qwen2_vl/test_processor.py0tests that special vision tokens do not get truncated when `truncation=true` is set.STRING
HIGHtests/transformers/qwen3_vl/test_processor.py0tests that special vision tokens do not get truncated when `truncation=true` is set.STRING
HIGHtests/transformers/qwen2_5_vl/test_modeling.py0tests that vlms through an error with explicit message saying what is wrong when number of images don't match number of STRING
HIGHtests/transformers/qwen3_vl_moe/test_modeling.py0tests that vlms through an error with explicit message saying what is wrong when number of images don't match number of STRING
HIGHtests/transformers/qwen3_vl/test_modeling.py0tests that vlms through an error with explicit message saying what is wrong when number of images don't match number of STRING
HIGHtests/transformers/paddleocr_vl/test_modeling.py0tests that vlms through an error with explicit message saying what is wrong when number of images don't match number of STRING
HIGHexamples/experiments/paddlefleet/run_pretrain.py0arguments pertaining to what data we are going to input our model for training and evaluating. using `pdargumentparser` STRING
HIGH…mples/experiments/deepseek_v3_pretrain/run_pretrain.py0arguments pertaining to what data we are going to input our model for training and evaluating. using `pdargumentparser` STRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/workflow.py0arguments pertaining to what data we are going to input our model for training and evaluating. using `pdargumentparser` STRING
HIGHexamples/experiments/paddlefleet/run_pretrain.py0arguments pertaining to which model/config/tokenizer we are going to pre-train from.STRING
HIGH…mples/experiments/deepseek_v3_pretrain/run_pretrain.py0arguments pertaining to which model/config/tokenizer we are going to pre-train from.STRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/workflow.py0arguments pertaining to which model/config/tokenizer we are going to pre-train from.STRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_utils.py0restore the original order of tokens after permutation. if probs are provided, it will also apply them to the tokens befSTRING
HIGH…dleformers/cli/train/deepseek_v3_pretrain/moe_utils.py0restore the original order of tokens after permutation. if probs are provided, it will also apply them to the tokens befSTRING
HIGHpaddleformers/transformers/moe_utils.py0restore the original order of tokens after permutation. if probs are provided, it will also apply them to the tokens befSTRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_layer.py0moe layer forward function 1. gate forward. 2. dispatch export. 3. experts forward. args: hidden_state: moe layer input STRING
HIGH…dleformers/cli/train/deepseek_v3_pretrain/moe_layer.py0moe layer forward function 1. gate forward. 2. dispatch export. 3. experts forward. args: hidden_state: moe layer input STRING
HIGHpaddleformers/transformers/moe_layer.py0moe layer forward function 1. gate forward. 2. dispatch export. 3. experts forward. args: hidden_state: moe layer input STRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_layer.py0moe expert dispatch from: https://huggingface.co/deepseek-ai/deepseek-v3/blob/main/modeling_deepseek.pySTRING
HIGH…dleformers/cli/train/deepseek_v3_pretrain/moe_layer.py0moe expert dispatch from: https://huggingface.co/deepseek-ai/deepseek-v3/blob/main/modeling_deepseek.pySTRING
HIGHpaddleformers/transformers/moe_layer.py0moe expert dispatch from: https://huggingface.co/deepseek-ai/deepseek-v3/blob/main/modeling_deepseek.pySTRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_gate.py0_summary_ the priority is the cumulative sum of the expert indices. this method is used in hunyuan model args: topk_idx STRING
HIGHpaddleformers/nn/moe_deepep/moe_gate.py0_summary_ the priority is the cumulative sum of the expert indices. this method is used in hunyuan model args: topk_idx STRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py0_summary_ the priority is the cumulative sum of the expert indices. this method is used in hunyuan model args: topk_idx STRING
HIGHpaddleformers/transformers/moe_gate.py0_summary_ the priority is the cumulative sum of the expert indices. this method is used in hunyuan model args: topk_idx STRING
HIGHpaddleformers/transformers/moe_gate_auto.py0_summary_ the priority is the cumulative sum of the expert indices. this method is used in hunyuan model args: topk_idx STRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts returns: tuple[paddleSTRING
HIGHpaddleformers/nn/moe_deepep/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts returns: tuple[paddleSTRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts returns: tuple[paddleSTRING
HIGHpaddleformers/transformers/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts returns: tuple[paddleSTRING
HIGHpaddleformers/transformers/moe_gate_auto.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts returns: tuple[paddleSTRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts in each group n_groupSTRING
HIGHpaddleformers/nn/moe_deepep/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts in each group n_groupSTRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts in each group n_groupSTRING
HIGHpaddleformers/transformers/moe_gate.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts in each group n_groupSTRING
HIGHpaddleformers/transformers/moe_gate_auto.py0_summary_ args: scores (paddle.tensor): [bsz*seq_len, n_experts] k (int): select the top k experts in each group n_groupSTRING
HIGHexamples/experiments/deepseek_v3_pretrain/moe_gate.py0calculate sequence auxiliary loss. args: logits (paddle.tensor): model output. returns: paddle.tensor: the value of sequSTRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py0calculate sequence auxiliary loss. args: logits (paddle.tensor): model output. returns: paddle.tensor: the value of sequSTRING
HIGHpaddleformers/transformers/moe_gate_auto.py0calculate sequence auxiliary loss. args: logits (paddle.tensor): model output. returns: paddle.tensor: the value of sequSTRING
HIGH…mples/experiments/deepseek_v3_pretrain/load_hf_ckpt.py0convert paddle model parameter names to hugging face format name lists args: paddle_name: parameter name in paddle formaSTRING
HIGH…xperiments/deepseek_v3_pretrain/convert_ckpt_to_sft.py0convert paddle model parameter names to hugging face format name lists args: paddle_name: parameter name in paddle formaSTRING
HIGH…s/cli/train/deepseek_v3_pretrain/utils/load_hf_ckpt.py0convert paddle model parameter names to hugging face format name lists args: paddle_name: parameter name in paddle formaSTRING
HIGH…rain/deepseek_v3_pretrain/utils/convert_ckpt_to_sft.py0convert paddle model parameter names to hugging face format name lists args: paddle_name: parameter name in paddle formaSTRING
HIGHexamples/experiments/deepseek_v3_pretrain/modeling.py0get the value of the 'use_casual_mask' environment variable.STRING
HIGHpaddleformers/utils/masking_utils.py0get the value of the 'use_casual_mask' environment variable.STRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/modeling.py0get the value of the 'use_casual_mask' environment variable.STRING
HIGHexamples/experiments/deepseek_v3_pretrain/modeling.py0args: hidden_states (_type_): [batch_size * seq_len, hidden_size]STRING
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/modeling.py0args: hidden_states (_type_): [batch_size * seq_len, hidden_size]STRING
327 more matches not shown…
Over-Commented Block1194 hits · 1160 pts
SeverityFileLineSnippetContext
LOWsetup.py1# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/conftest.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/parallel_launch.py1# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/testing_utils.py1# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/common_test.py1# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/__init__.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/check_log_for_exitcode.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_pt_fp8.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen3vl_sft.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_a100.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_dpo_lora.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/run_fleet_cice.sh1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/update_precision.sh1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/check_pr_approval.py1# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen3_single_card.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen3vl_sft_single_card.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/internlm3_sft.sh1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_pt_ep4.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen3vl_lora.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_dpo.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/qwen3_a100.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_pt_single_card.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_sft_cp.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_pt.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/preprocess.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_sft.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/check_precision_approval.sh1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/check_loss.py1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_lora.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/integration_test/glm45_pt_grouped_gemm.sh1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/mergekit/test_merge_model.py1# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/mergekit/test_sparsify_method.py1# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/mergekit/__init__.py1# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/mergekit/test_merge_config.py1# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/mergekit/test_merge_method.py1# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_mlp.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_activation.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_criterion.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_norm.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/__init__.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_lm_head.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/nn/test_attention.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/config/benchmark/config/pt/MinimaxV2.5_hzz1.yaml121# fp8: e4m3COMMENT
LOWtests/dataset/test_file_reader.py1# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_convertor.py1# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_collate.py1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_collate.py181 end = int(result[0, k, pos, 0])COMMENT
LOWtests/dataset/test_collate.py261# position_ids = [[0,1,2], [0,1], [0,1,2]] -> concat = [0,1,2,0,1,0,1,2]COMMENT
LOWtests/dataset/test_map_datasets.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_iter_datasets.py1# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_mix_datasets.py1# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_usetemplate.py1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/__init__.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_io.py1# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/dataset/test_packing.py1# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/triton/test_rope_triton.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOW…s/coverage_test/nn/test_coverage_moe_alltoall_layer.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOWtests/coverage_test/nn/test_coverage_moe_block.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
LOW…sts/coverage_test/nn/test_coverage_generation_utils.py1# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.COMMENT
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Unused Imports732 hits · 684 pts
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LOWtests/transformers/intern_lm3/test_modeling.py14CODE
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LOWtests/transformers/minimax/test_modeling.py14CODE
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LOW…ts/transformers/ernie4_5_moe_vl/test_vision_process.py14CODE
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LOWtests/transformers/glm_ocr/test_modeling.py15CODE
LOWtests/transformers/glm_ocr/test_processor.py14CODE
LOWtests/transformers/paligemma2/test_modeling.py16CODE
LOWtests/transformers/deepseek_v3/test_modeling.py15CODE
LOWtests/transformers/glm_moe_dsa/test_modeling.py15CODE
LOWtests/transformers/seed_oss/test_modeling.py14CODE
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LOWtests/transformers/intern_lm2_5/test_modeling.py14CODE
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LOWtests/transformers/llama/test_modeling.py15CODE
LOW…ers/diff_transformer/test_diff_transformer_modeling.py16CODE
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LOWtests/transformers/qwen3_vl/test_modeling_fleet.py14CODE
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LOWexamples/tools/compare_gemma3_multimodal_precision.py36CODE
LOWexamples/tools/compare_gemma3_ms_swift_loss.py39CODE
LOWexamples/experiments/deepseek_v3_pretrain/moe_layer.py17CODE
LOWexamples/experiments/deepseek_v3_pretrain/moe_gate.py17CODE
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Hallucination Indicators62 hits · 652 pts
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CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py157 _, _, x_t_fp8, x_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py165 x_fp8, x_scale, x_t_fp8, x_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py172 _, _, w1_fp8, w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py182 o2_fp8, o2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py186 _, _, w2_t_fp8, w2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py227 do3_fp8, do3_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py234 _, _, do3_t_fp8, do3_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py241 do3_fp8, do3_scale, do3_t_fp8, do3_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py247 w2_fp8, w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py257 _, _, o2_t_fp8, o2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py277 do1_fp8, do1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py284 _, _, do1_t_fp8, do1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py291 do1_fp8, do1_scale, do1_t_fp8, do1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py297 w1_fp8, w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py354 x_fp8, x_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py358 _, _, w1_fp8, w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py368 o2_fp8, o2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py372 _, _, w2_t_fp8, w2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py412 _, _, x_t_fp8, x_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py422 do3_fp8, do3_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py429 _, _, do3_t_fp8, do3_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py436 do3_fp8, do3_scale, do3_t_fp8, do3_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py442 w2_fp8, w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py452 _, _, o2_t_fp8, o2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py472 do1_fp8, do1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py479 _, _, do1_t_fp8, do1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py486 do1_fp8, do1_scale, do1_t_fp8, do1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL⚡…amples/experiments/ernie_pretrain/models/fp8_linear.py492 w1_fp8, w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…amples/experiments/ernie_pretrain/models/fp8_linear.py400 _, _, w1_fp8, w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…xperiments/ernie_pretrain/models/ernie/modeling_moe.py2003 layer.self_attn.o_proj.dense_experts.down_proj.weight.scale_(factor)CODE
CRITICAL…xperiments/ernie_pretrain/models/ernie/modeling_moe.py2015 layer.mlp.dense_experts.down_proj.weight.scale_(factor)CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py191 w1_t_quant, w1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py201 x_fp8, x_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py267 w2_quant, w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py279 o2_quant, o2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py325 w2_quant, w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py336 o2_quant, o2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py384 bw_w2_quant, bw_w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py393 unzipped_grad_fp8, unzipped_grad_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py438 bw_w2_quant, bw_w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py447 unzipped_grad_fp8, unzipped_grad_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py508 bw_w1_quant, bw_w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py518 do1_fp8, do1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py568 o2_t_fp8, o2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py587 out_grad_fp8, out_grad_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py651 input_x_fp8, input_x_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py667 do1_fp8, do1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py891 w1_t_quant, w1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py909 x_fp8, x_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py966 w2_quant, w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py986 o2_fp8, o2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1031 bw_w2_quant, bw_w2_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1040 unzipped_grad_fp8, unzipped_grad_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1106 bw_w1_quant, bw_w1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1115 do1_fp8, do1_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1187 o2_t_fp8, o2_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1203 do3_t_fp8, do3_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1250 input_x_t_fp8, input_x_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
CRITICAL…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py1266 do1_t_fp8, do1_t_scale = paddle.incubate.nn.functional.fp8.fp8_quant_blockwise(CODE
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Deep Nesting657 hits · 596 pts
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AI Structural Patterns422 hits · 406 pts
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LOW…ments/ernie_pretrain/models/sequence_parallel_utils.py459CODE
LOW…ments/ernie_pretrain/models/sequence_parallel_utils.py467CODE
LOW…amples/experiments/ernie_pretrain/models/comm_utils.py128CODE
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Empty Error Handlers72 hits · 360 pts
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HIGHtests/coverage_test/nn/test_coverage_loss_utils.py131except Exception:CODE
HIGHtests/coverage_test/datasets/test_coverage_template.py374except Exception:CODE
HIGH…sts/coverage_test/cli/test_coverage_ernie_moe_utils.py72except Exception:CODE
HIGH…overage_test/cli/test_coverage_deepseek_v3_moe_gate.py423except (ValueError, RuntimeError):CODE
HIGH…verage_test/cli/test_coverage_deepseek_v3_moe_layer.py199except (AttributeError, AssertionError):CODE
HIGH…verage_test/cli/test_coverage_deepseek_v3_moe_layer.py218except (AttributeError, AssertionError):CODE
HIGH…verage_test/cli/test_coverage_deepseek_v3_moe_layer.py235except (AttributeError, AssertionError):CODE
HIGH…overage_test/cli/test_coverage_tensorboard_callback.py115except Exception:CODE
HIGH…verage_test/quantization/test_coverage_quant_linear.py103except RuntimeError:CODE
HIGH…e_test/transformers/test_coverage_kimi_k2_tokenizer.py168except Exception:CODE
HIGH…e_test/transformers/test_coverage_kimi_k2_tokenizer.py176except Exception:CODE
HIGHtests/transformers/test_configuration_common.py128except NotImplementedError:CODE
HIGHtests/transformers/test_configuration_common.py140except NotImplementedError:CODE
HIGHtests/transformers/phi4/test_phi4_modeling.py149except Exception:CODE
HIGHtests/transformers/phi4/test_phi4_modeling.py210except Exception:CODE
HIGHtests/transformers/phi4/test_phi4_modeling.py426except Exception:CODE
HIGHexamples/experiments/paddlefleet/run_pretrain.py584except ImportError:CODE
HIGHexamples/experiments/deepseek_v3_pretrain/fp8_linear.py38except:CODE
HIGH…mples/experiments/deepseek_v3_pretrain/run_pretrain.py516except ImportError:CODE
HIGHexamples/experiments/deepseek_v3_pretrain/modeling.py53except:CODE
HIGHexamples/experiments/ernie_pretrain/models/utils.py36except (ImportError, ModuleNotFoundError):CODE
HIGHexamples/experiments/ernie_pretrain/models/utils.py42except (ImportError, ModuleNotFoundError):CODE
HIGHpaddleformers/__init__.py51except:CODE
HIGHpaddleformers/nn/pp_model.py651except Exception:CODE
HIGHpaddleformers/datasets/dataset.py540except OSError:CODE
HIGHpaddleformers/datasets/dataset.py535except OSError:CODE
HIGHpaddleformers/datasets/SFTDataset.py252except Exception:CODE
HIGHpaddleformers/datasets/template/mm_plugin.py665except Exception:CODE
HIGHpaddleformers/utils/hf_bitexact_hybrid_clip.py79except ImportError:CODE
HIGHpaddleformers/utils/serialization.py145except KeyError:CODE
HIGHpaddleformers/utils/download/common.py416except OSError:CODE
HIGHpaddleformers/utils/download/common.py516except Exception:CODE
HIGHpaddleformers/utils/download/common.py112except OSError: # raise on anything: file does not exist or space disk cannot be checkedCODE
HIGHpaddleformers/utils/download/common.py460except PermissionError:CODE
HIGHpaddleformers/utils/download/common.py509except Exception:CODE
HIGHpaddleformers/cli/utils/process.py57except psutil.NoSuchProcess:CODE
HIGHpaddleformers/cli/utils/process.py45except psutil.NoSuchProcess:CODE
HIGHpaddleformers/cli/utils/process.py52except psutil.NoSuchProcess:CODE
HIGH…leformers/cli/train/deepseek_v3_pretrain/fp8_linear.py38except:CODE
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/workflow.py446except ImportError:CODE
HIGH…ddleformers/cli/train/deepseek_v3_pretrain/modeling.py53except:CODE
HIGHpaddleformers/cli/train/auto_parallel/workflow.py260except ImportError:CODE
HIGHpaddleformers/cli/train/ernie_pretrain/models/utils.py38except (ImportError, ModuleNotFoundError):CODE
HIGHpaddleformers/cli/train/ernie_pretrain/models/utils.py44except (ImportError, ModuleNotFoundError):CODE
HIGHpaddleformers/peft/lora/lora_model.py397except FileNotFoundError:CODE
HIGHpaddleformers/transformers/model_utils.py1167except FileNotFoundError:CODE
HIGHpaddleformers/transformers/model_utils.py2917except FileNotFoundError:CODE
HIGHpaddleformers/transformers/video_utils.py167except (IndexError, TypeError):CODE
HIGHpaddleformers/transformers/mc2_parallel_linear.py21except ImportError:CODE
HIGHpaddleformers/transformers/fp8_utils.py39except:CODE
HIGHpaddleformers/transformers/tokenizer_utils.py339except (FileNotFoundError, EnvironmentError):CODE
HIGHpaddleformers/transformers/linear_utils.py81except ImportError:CODE
HIGHpaddleformers/transformers/tensor_parallel_utils.py66except ImportError:CODE
HIGHpaddleformers/transformers/gpt_provider.py239except:CODE
HIGHpaddleformers/transformers/gemma4_moe/modeling.py216except:CODE
HIGHpaddleformers/transformers/auto/processing.py247except Exception:CODE
HIGHpaddleformers/transformers/minicpm/modeling.py57except:CODE
HIGHpaddleformers/transformers/intern_lm3/modeling.py35except Exception:CODE
HIGH…formers/transformers/ernie4_5_moe_vl/vision_process.py180except Exception:CODE
HIGH…ansformers/ernie4_5_moe_vl/model/modeling_moe_vl_pp.py1265except Exception:CODE
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Decorative Section Separators85 hits · 279 pts
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MEDIUM⚡tests/integration_test/run_fleet_cice.sh424# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh427# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh437# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh439# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh476# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh479# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh481# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/integration_test/run_fleet_cice.sh483# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh48# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh50# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh155# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh158# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh302# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh305# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh389# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh392# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh404# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh406# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh451# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh454# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh510# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/integration_test/run_fleet_cice.sh514# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/dataset/test_collate.py97# ---------------------------------------------------------------------------COMMENT
MEDIUM⚡tests/dataset/test_collate.py107# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/dataset/test_collate.py189# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/dataset/test_collate.py202# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/dataset/test_collate.py258# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/dataset/test_collate.py272# ---------------------------------------------------------------------------COMMENT
MEDIUMtests/dataset/test_mix_datasets.py35# ===========================================================================COMMENT
MEDIUMtests/dataset/test_mix_datasets.py37# ===========================================================================COMMENT
MEDIUM⚡tests/dataset/test_mix_datasets.py211# ===========================================================================COMMENT
MEDIUM⚡tests/dataset/test_mix_datasets.py213# ===========================================================================COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py635 # -------------------------COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py637 # -------------------------COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py665 # -------------------------COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py668 # -------------------------COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py709 # -------------------------COMMENT
MEDIUMtests/transformers/glm_ocr/test_modeling.py711 # -------------------------COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/table_ocr.md135# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/table_ocr.md137# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/table_ocr.md285# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/table_ocr.md287# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md140# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md334# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md336# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md484# ==========================================COMMENT
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md486# ==========================================COMMENT
MEDIUM…ples/best_practices/DeepSeek-V4/dequant_fp8_to_bf16.py156# ---------------------------------------------------------------------------COMMENT
MEDIUM…ples/best_practices/DeepSeek-V4/dequant_fp8_to_bf16.py158# ---------------------------------------------------------------------------COMMENT
MEDIUM.github/workflows/formers_bot_analysis.yml86 # ── 定时触发路径 ──────────────────────────────────────────────────COMMENT
MEDIUM.github/workflows/formers_bot_analysis.yml114 # ── PR 触发路径 ───────────────────────────────────────────────────COMMENT
MEDIUM.github/workflows/formers_bot_analysis.yml297 # ── 写入 GITHUB_OUTPUT，供 report-to-monitor 步骤读取 ──────────COMMENT
MEDIUMpaddleformers/utils/upcast_downcast_triton.py352# -----------------------------------------------------------------------------COMMENT
MEDIUMpaddleformers/utils/upcast_downcast_triton.py354# -----------------------------------------------------------------------------COMMENT
MEDIUMpaddleformers/utils/upcast_downcast_triton.py476# ------------COMMENT
MEDIUM⚡paddleformers/quantization/hf_checkpoint.py39# -----------------------------------------------------------------------------COMMENT
MEDIUM⚡paddleformers/quantization/hf_checkpoint.py47# -----------------------------------------------------------------------------COMMENT
MEDIUMpaddleformers/quantization/hf_checkpoint.py124# -----------------------------------------------------------------------------COMMENT
MEDIUMpaddleformers/quantization/hf_checkpoint.py126# -----------------------------------------------------------------------------COMMENT
MEDIUMpaddleformers/quantization/hf_checkpoint.py176# -----------------------------------------------------------------------------COMMENT
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Modern Structural Boilerplate275 hits · 262 pts
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LOWsetup.py76__all__ = ['show']CODE
LOWtests/testing_utils.py39__all__ = ["get_vocab_list", "stable_softmax", "cross_entropy"]CODE
LOWtests/common_test.py20__all__ = ["CommonTest", "CpuCommonTest"]CODE
LOW…ples/experiments/paddlefleet/deepseek_v3_2_provider.py40logger = logging.getLogger(__name__)CODE
LOWexamples/experiments/paddlefleet/glm45_provider.py27logger = logging.getLogger(__name__)CODE
LOWexamples/experiments/paddlefleet/qwen_provider.py27logger = logging.getLogger(__name__)CODE
LOWexamples/experiments/deepseek_v3_pretrain/fp8_linear.py42__all__ = [CODE
LOWexamples/experiments/deepseek_v3_pretrain/modeling.py135__all__ = [CODE
LOW…amples/experiments/deepseek_v3_pretrain/modeling_pp.py72__all__ = [CODE
LOW…periments/deepseek_v3_pretrain/config/configuration.py18__all__ = [CODE
LOW…rnie_pretrain/tools/sharded_to_uc/merge_sharding_ep.py33logger = logging.getLogger(__name__)CODE
LOW…amples/experiments/ernie_pretrain/models/fp8_linear.py41__all__ = ["Fp8FusedMlp"]CODE
LOWexamples/experiments/ernie_pretrain/models/utils.py21logger = logging.getLogger(__name__)CODE
LOW…ments/ernie_pretrain/models/sequence_parallel_utils.py41logger = logging.getLogger(__name__)CODE
LOW…amples/experiments/ernie_pretrain/models/comm_utils.py30logger = logging.getLogger(__name__)CODE
LOW…periments/ernie_pretrain/models/ernie/configuration.py24logger = logging.getLogger(__name__)CODE
LOW…periments/ernie_pretrain/models/ernie/configuration.py26__all__ = [CODE
LOW…xperiments/ernie_pretrain/models/ernie/modeling_moe.py90logger = logging.getLogger(__name__)CODE
LOW…xperiments/ernie_pretrain/models/ernie/modeling_moe.py111__all__ = [CODE
LOW…es/experiments/ernie_pretrain/models/ernie/modeling.py71logger = logging.getLogger(__name__)CODE
LOW…es/experiments/ernie_pretrain/models/ernie/modeling.py120__all__ = [CODE
LOW…experiments/ernie_pretrain/models/ernie/modeling_pp.py87logger = logging.getLogger(__name__)CODE
LOW…les/experiments/ernie_pretrain/models/moe/top2_gate.py32logger = logging.getLogger(__name__)CODE
LOW…les/experiments/ernie_pretrain/models/moe/moe_layer.py53logger = logging.getLogger(__name__)CODE
LOW…rnie_pretrain/models/moe/token_dispatcher/fp8_utils.py37__all__ = [CODE
LOW…mples/experiments/ernie_pretrain/ernie/model_config.py18__all__ = ["ModelConfig"]CODE
LOW…e_pretrain/ernie/src/callbacks/moe_logging_callback.py42__all__ = ["GlobalRNGCallback", "MoeLoggingCallback"]CODE
LOW…riments/ernie_pretrain/ernie/src/callbacks/__init__.py24__all__ = [CODE
LOW…ernie_pretrain/ernie/src/callbacks/logging_callback.py19logger = logging.getLogger(__name__)CODE
LOW…_pretrain/ernie/src/callbacks/sp_grad_sync_callback.py25logger = logging.getLogger(__name__)CODE
LOW…e/src/callbacks/moe_correction_bias_adjust_callback.py25logger = logging.getLogger(__name__)CODE
LOW…train/ernie/src/callbacks/fp8_quant_weight_callback.py21logger = logging.getLogger(__name__)CODE
LOW…/experiments/ernie_pretrain/ernie/src/clip/__init__.py17__all__ = ["ClipGradForMOEByGlobalNorm"]CODE
LOW…/experiments/ernie_pretrain/ernie/src/clip/moe_clip.py25logger = logging.getLogger(__name__)CODE
LOW…nts/ernie_pretrain/ernie/src/lr_schedulers/__init__.py17__all__ = ["get_wsd_schedule_with_warmup", "get_cosine_schedule_with_warmup"]CODE
LOW…les/experiments/ernie_pretrain/ernie/src/utils/misc.py23logger = logging.getLogger(__name__)CODE
LOW…experiments/ernie_pretrain/ernie/src/utils/__init__.py17__all__ = ["logger", "setup_logger_output_file"]CODE
LOW…ments/ernie_pretrain/ernie/src/utils/training_utils.py17logger = logging.getLogger(__name__)CODE
LOW…eriments/ernie_pretrain/ernie/src/trainers/__init__.py21__all__ = [CODE
LOW…nie_pretrain/ernie/src/trainers/pretraining_trainer.py15__all__ = [CODE
LOW…nie_pretrain/ernie/src/trainers/pretraining_trainer.py94logger = logging.getLogger(__name__)CODE
LOW…rainers/dygraph_optimizer/hybrid_parallel_optimizer.py34__all__ = []CODE
LOWpaddleformers/nn/embedding.py21__all__ = ["Embedding"]CODE
LOWpaddleformers/nn/linear.py26__all__ = ["Linear"]CODE
LOWpaddleformers/nn/norm.py26__all__ = ["Norm"]CODE
LOWpaddleformers/nn/mlp.py30__all__ = ["MLP"]CODE
LOWpaddleformers/nn/lm_head.py24__all__ = ["LMHead"]CODE
LOWpaddleformers/nn/attention/interface.py19__all__ = ["AttentionInterface"]CODE
LOWpaddleformers/nn/moe_deepep/modular_moe_layer.py36logger = logging.getLogger(__name__)CODE
LOWpaddleformers/nn/moe_deepep/moe_factory.py62__all__ = ["QuickAccessMoEFactory"]CODE
LOWpaddleformers/nn/moe_deepep/moe_loss.py24logger = logging.getLogger(__name__)CODE
LOWpaddleformers/datasets/dataset.py48__all__ = ["MapDataset", "DatasetBuilder", "IterDataset", "load_dataset"]CODE
LOWpaddleformers/datasets/rlhf_datasets/protocol.py28__all__ = [CODE
LOWpaddleformers/utils/hf_bitexact_clip.py68__all__ = [CODE
LOWpaddleformers/utils/downloader.py44__all__ = ["get_weights_path_from_url"]CODE
LOWpaddleformers/utils/moe_hybrid_parallel_optimizer.py55__all__ = [CODE
LOWpaddleformers/utils/batch_sampler.py19__all__ = ["MappingBatchSampler", "MappingDistributedBatchSampler", "DistributedBatchSampler"]CODE
LOWpaddleformers/utils/initializer.py26__all__ = [CODE
LOWpaddleformers/utils/accuracy_target.py42__all__ = [CODE
LOWpaddleformers/utils/hf_bitexact_hybrid_clip.py60__all__ = [CODE
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Self-Referential Comments86 hits · 260 pts
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MEDIUMtests/nn/test_mlp.py25 # Create a mock config with default valuesCOMMENT
MEDIUMtests/nn/test_attention.py267 # Create the ground truth dense causal mask for the naive implementationCOMMENT
MEDIUMtests/nn/test_attention.py297 # Create the ground truth dense mask from the FlashMask sparse formatCOMMENT
MEDIUMtests/coverage_test/nn/test_coverage_pp_model.py407 # Create a config where head_dim attribute doesn't exist at all,COMMENT
MEDIUMtests/coverage_test/nn/test_coverage_pp_model.py697 # Create a mock layer that has a weight attributeCOMMENT
MEDIUM⚡tests/coverage_test/datasets/test_coverage_mm_plugin.py210 # Create a new plugin classCOMMENT
MEDIUMtests/coverage_test/utils/test_coverage_doc_parser.py52 # Create a temp file with content < 1024 charsCOMMENT
MEDIUM…coverage_test/utils/test_coverage_aistudio_download.py243 # Create the expected cache structureCOMMENT
MEDIUMtests/coverage_test/utils/test_coverage_optimizer.py34 # Create a simple model and optimizer so we can call the methodCOMMENT
MEDIUMtests/coverage_test/utils/test_coverage_image_utils.py69 # Create a simple test image and its base64 encodingCOMMENT
MEDIUM…sts/coverage_test/cli/test_coverage_ernie_top2_gate.py134 # Create a near-orthogonal weight matrixCOMMENT
MEDIUM⚡…/coverage_test/cli/test_coverage_dataset_formatting.py186 # Create a dataset with unsupported featuresCOMMENT
MEDIUM⚡tests/coverage_test/cli/test_coverage_cli.py60 # Create the partial after mocking printCOMMENT
MEDIUMtests/coverage_test/peft/test_coverage_loraga_utils.py111 # Create a mock LoRA moduleCOMMENT
MEDIUM…erage_test/transformers/test_coverage_moe_gate_auto.py146 # Create a weight parameter for the gateCOMMENT
MEDIUM…e_test/transformers/test_coverage_kimi_k2_tokenizer.py33 # Create a minimal tiktoken model file for testingCOMMENT
MEDIUM⚡tests/coverage_test/trainer/test_coverage_timer.py178 # Create a _Timer firstCOMMENT
MEDIUMtests/coverage_test/trainer/test_coverage_timer.py190 # Create a distinct class to force type mismatchCOMMENT
MEDIUMtests/transformers/test_processing_common.py379 # Define the kwargs for each modalityCOMMENT
MEDIUMtests/transformers/test_processing_common.py400 # Define the kwargs for each modalityCOMMENT
MEDIUMtests/transformers/test_processing_common.py570 # Define the kwargs for each modalityCOMMENT
MEDIUMtests/transformers/test_processing_common.py591 # Define the kwargs for each modalityCOMMENT
MEDIUM⚡tests/transformers/ernie4_5_moe_vl/test_processor.py461 # Define the kwargs for each modalityCOMMENT
MEDIUM⚡tests/transformers/ernie4_5_moe_vl/test_processor.py477 # Define the kwargs for each modalityCOMMENT
MEDIUMtests/trainer/test_trainer_callback.py16# This file is modified fromCOMMENT
MEDIUMexamples/experiments/paddlefleet/run_pretrain.py614 # Create the learning_rate sheduler and optimizerCOMMENT
MEDIUM…mples/experiments/deepseek_v3_pretrain/run_pretrain.py577 # Create the learning_rate sheduler and optimizerCOMMENT
MEDIUMexamples/experiments/deepseek_v3_pretrain/moe_utils.py118 # Create an output tensor filled with zerosCOMMENT
MEDIUMexamples/experiments/deepseek_v3_pretrain/moe_utils.py335 # Create an output tensor filled with zerosCOMMENT
MEDIUMexamples/experiments/deepseek_v3_pretrain/moe_gate.py186 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUMexamples/experiments/deepseek_v3_pretrain/moe_gate.py252 # Create a mask for 1st's expert per token.COMMENT
MEDIUMexamples/experiments/deepseek_v3_pretrain/moe_gate.py257 # Create a mask for 2nd's expert per token using Gumbel-max trick.COMMENT
MEDIUMscripts/iluvatar_ci/test_ernie_21b_sft.py27 # Define the exact shell command to executeCOMMENT
MEDIUMscripts/xpu_ci/test_ernie_21b_sft.py27 # Define the exact shell command to executeCOMMENT
MEDIUMscripts/xpu_ci/test_ernie_28b_thinking_sft.py27 # Define the exact shell command to executeCOMMENT
MEDIUMscripts/codestyle/check_dead_links.py118 # Create the symlinkCOMMENT
MEDIUM.github/workflows/cherry-pick.yml97 # Create a new branch for the cherry-pickCOMMENT
MEDIUMpaddleformers/datasets/template/mm_plugin.py645 # Create an image with a white background and the same size as the original imageCOMMENT
MEDIUMpaddleformers/utils/download/common.py310 # Create a factory function that returns a Session with configured proxiesSTRING
MEDIUMpaddleformers/cli/cli.py98 # Create a default GPU list string (e.g., "0,1,2" for 3 GPUs)COMMENT
MEDIUM…dleformers/cli/train/deepseek_v3_pretrain/moe_utils.py118 # Create an output tensor filled with zerosCOMMENT
MEDIUM…dleformers/cli/train/deepseek_v3_pretrain/moe_utils.py335 # Create an output tensor filled with zerosCOMMENT
MEDIUM…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py186 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUM…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py252 # Create a mask for 1st's expert per token.COMMENT
MEDIUM…ddleformers/cli/train/deepseek_v3_pretrain/moe_gate.py257 # Create a mask for 2nd's expert per token using Gumbel-max trick.COMMENT
MEDIUM…ddleformers/cli/train/deepseek_v3_pretrain/workflow.py507 # Create the learning_rate sheduler and optimizerCOMMENT
MEDIUMpaddleformers/cli/train/auto_parallel/workflow.py320 # Create the learning_rate scheduler and optimizerCOMMENT
MEDIUMpaddleformers/cli/train/sft/workflow.py724 # Create the learning_rate sheduler and optimizerCOMMENT
MEDIUMpaddleformers/transformers/video_utils.py220 # Create a batched list from single objectCOMMENT
MEDIUMpaddleformers/transformers/image_transforms.py722 # Create the outer listCOMMENT
MEDIUMpaddleformers/transformers/moe_utils.py66 # Create a dense expert-to-token mapping from the sparse token-to-expert mappingCOMMENT
MEDIUMpaddleformers/transformers/moe_utils.py109 # Create an output tensor filled with zerosCOMMENT
MEDIUMpaddleformers/transformers/processing_utils.py471 # Create a unified `preprocessor_config.json` and save all attributes as a composite config, except for tokeCOMMENT
MEDIUMpaddleformers/transformers/image_processing_utils.py53 # Define the key methods that should support Paddle tensor return types.COMMENT
MEDIUMpaddleformers/transformers/moe_gate.py345 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUMpaddleformers/transformers/moe_gate.py413 # Create a mask for 1st's expert per token.COMMENT
MEDIUMpaddleformers/transformers/moe_gate.py418 # Create a mask for 2nd's expert per token using Gumbel-max trick.COMMENT
MEDIUMpaddleformers/transformers/moe_gate_auto.py348 # Create a mask for 1st's expert per tokenCOMMENT
MEDIUMpaddleformers/transformers/moe_gate_auto.py414 # Create a mask for 1st's expert per token.COMMENT
MEDIUMpaddleformers/transformers/moe_gate_auto.py419 # Create a mask for 2nd's expert per token using Gumbel-max trick.COMMENT
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Docstring Block Structure47 hits · 235 pts
SeverityFileLineSnippetContext
HIGHexamples/experiments/deepseek_v3_pretrain/fp8_linear.py57 Applies a linear transformation to the incoming data: y = xA^T + b. This function supports specialized implemenSTRING
HIGHexamples/experiments/deepseek_v3_pretrain/kernel.py101 Dequantizes the given weight tensor using the provided scale tensor. Args: x (paddle.Tensor): The quantSTRING
HIGH…rnie_pretrain/models/moe/token_dispatcher/moe_utils.py110Permute tokens based on expert assignment indices. Args: tokens (paddle.Tensor): Input tokens to be permuteSTRING
HIGH…rnie_pretrain/models/moe/token_dispatcher/moe_utils.py136Restore original token order from permuted tokens. Args: permuted_tokens (paddle.Tensor): Permuted tokens tSTRING
HIGHscripts/regression/test_models.py116Load model configuration from YAML file. Args: model_key: The model identifier to load configuratioSTRING
HIGHpaddleformers/nn/pp_model.py114 Determines the layer partitioning scheme for Pipeline Parallelism (PP) and Virtual Pipeline Parallelism (VP) wiSTRING
HIGHpaddleformers/nn/attention/sink_impl.py561 A unified, high-performance attention implementation with Sink mechanism support. This function automatically STRING
HIGHpaddleformers/datasets/data_utils.py119Convert batch dialogue into input_ids. The API support multiple data format: `pt`, `sft. Args: dials (STRING
HIGHpaddleformers/datasets/DPODataset.py161Generate packed sequences using greedy strategy. Args: examples: List of examples to pack. STRING
HIGHpaddleformers/datasets/DPODataset.py187Preprocess DPO training examples Args: example: Raw training example containing: - STRING
HIGHpaddleformers/utils/downloader.py94Get weights path from WEIGHT_HOME, if not exists, download it from url. Args: url (str): download url STRING
HIGHpaddleformers/utils/tools.py148 Args: version (str): The first version string needed to be compared. The format of version striSTRING
HIGHpaddleformers/utils/distributed.py167nested all gather function with offload Args: tensor (Any): the desired tensor, list of tensor, dict of tenSTRING
HIGHpaddleformers/utils/download/aistudio_hub_download.py628 Checks if a file exists in a repository on the Aistudio Hub. Args: repo_id (`str`): A nameSTRING
HIGHpaddleformers/cli/hparams/parser.py120_summary_ Args: parser (PdArgumentParser): _description_ args (Optional[Union[dict[str, Any], list[STRING
HIGH…leformers/cli/train/deepseek_v3_pretrain/fp8_linear.py57 Applies a linear transformation to the incoming data: y = xA^T + b. This function supports specialized implemenSTRING
HIGHpaddleformers/cli/train/deepseek_v3_pretrain/kernel.py101 Dequantizes the given weight tensor using the provided scale tensor. Args: x (paddle.Tensor): The quantSTRING
HIGH…rnie_pretrain/models/moe/token_dispatcher/moe_utils.py110Permute tokens based on expert assignment indices. Args: tokens (paddle.Tensor): Input tokens to be permuteSTRING
HIGH…rnie_pretrain/models/moe/token_dispatcher/moe_utils.py136Restore original token order from permuted tokens. Args: permuted_tokens (paddle.Tensor): Permuted tokens tSTRING
HIGHpaddleformers/transformers/configuration_utils.py1125 Instantiate a [`PretrainedConfig`] (or a derived class) from a pretrained model configuration. Args: STRING
HIGHpaddleformers/transformers/model_utils.py211 This function chunks the `input_tensors` into smaller input tensor parts of size `chunk_size` over the dimension STRING
HIGHpaddleformers/transformers/feature_extraction_utils.py231 Instantiate a type of [`~feature_extraction_utils.FeatureExtractionMixin`] from a feature extractor, *e.g.* a STRING
HIGHpaddleformers/transformers/fp8_utils.py227 FP8 Linear computation function supporting multiple return modes and quantized/unquantized inputs. ArgSTRING
HIGHpaddleformers/transformers/conversion_utils.py1400get name mapping of PretrainedModel Args: config (PretrainedConfig): the configuration of name-mappSTRING
HIGHpaddleformers/transformers/conversion_utils.py1526get fused parameter mapping of PretrainedModel Args: config (PretrainedConfig): the configuration oSTRING
HIGHpaddleformers/transformers/utils.py511 Tries to locate a file in a local folder and repo, downloads and cache it if necessary. Args: path_or_rSTRING
HIGHpaddleformers/transformers/auto/video_processing.py87 Loads the video processor configuration from a pretrained model video processor configuration. Args: pSTRING
HIGHpaddleformers/transformers/auto/feature_extraction.py95 Loads the feature extractor configuration from a pretrained model feature extractor configuration. Args: STRING
HIGHpaddleformers/transformers/auto/tokenizer.py65 Loads the tokenizer configuration from a pretrained model tokenizer configuration. Args: pretrained_moSTRING
HIGHpaddleformers/transformers/auto/image_processing.py114 Loads the image processor configuration from a pretrained model image processor configuration. Args: pSTRING
HIGHpaddleformers/transformers/legacy/tokenizer_utils.py1093 Add a list of new tokens to the tokenizer class. If the new tokens are not in the vocabulary, they are added toSTRING
HIGH…dleformers/transformers/legacy/tokenizer_utils_base.py839 Add a dictionary of special tokens (eos, pad, cls, etc.) to the encoder and link them to class attributes. If STRING
HIGH…dleformers/transformers/legacy/tokenizer_utils_base.py933 Add a list of new tokens to the tokenizer class. If the new tokens are not in the vocabulary, they are added toSTRING
HIGHpaddleformers/transformers/qwen2_5_vl/modeling.py1245 Calculate the 3D rope index based on image and video's temporal, height and width in LLM. Explanation:STRING
HIGH…/transformers/ernie4_5_moe_vl/model/modeling_moe_vl.py1080 Calculate the 3D rope index based on image and video's temporal, height and width in LLM. Explanation:STRING
HIGH…/transformers/ernie4_5_moe_vl/model/modeling_moe_pp.py93 Determines the layer partitioning scheme for Pipeline Parallelism (PP) and Virtual Pipeline Parallelism (VP) wiSTRING
HIGH…ansformers/ernie4_5_moe_vl/model/modeling_moe_vl_pp.py830 Convert input data into a format acceptable by the model, including image processing, text processing, etc. STRING
HIGH…ernie4_5_moe_vl/model/distributed/common_dist_utils.py83 Performs parallel matrix multiplication with tensor model parallelism support. Args: x (paddle.Tensor)STRING
HIGH…rmers/transformers/ernie4_5_moe_vl/model/utils/misc.py89TrainingLogs Args: object (_type_): _description_ Raises: AttributeError: _description_ RSTRING
HIGH…rmers/transformers/ernie4_5_moe_vl/model/utils/misc.py170gate attr Args: attr (_type_): _description_ Raises: AttributeError: _descriptSTRING
HIGH…/ernie4_5_moe_vl/model/fusion_ops/common_fusion_ops.py49 Performs fused flash attention with multiple implementation variants. Args: q (paddle.Tensor): Query tSTRING
HIGHpaddleformers/transformers/glm4v_moe/modeling.py1340 Calculate the 3D rope index based on image and video's temporal, height and width in LLM. Explanation:STRING
HIGHpaddleformers/transformers/qwen2_vl/vision_process.py162calculate the number of frames for video used for model inputs. Args: ele (dict): a dict contains the confiSTRING
HIGHpaddleformers/transformers/qwen2_vl/vision_process.py202 Calculate the start and end frame indices based on the given time range. Args: ele (dict): A dictionarSTRING
HIGHpaddleformers/transformers/paddleocr_vl/modeling.py1798 Calculate the 3D rope index based on image and video's temporal, height and width in LLM. Explanation:STRING
HIGHpaddleformers/data/causal_dataset.py36 Retrieve logits with retry mechanism if no response is received within the specified time Parameters: STRING
HIGHpaddleformers/generation/configuration_utils.py346 Instantiate a [`GenerationConfig`] from a generation configuration file. Args: pretrained_STRING
Excessive Try-Catch Wrapping190 hits · 212 pts
SeverityFileLineSnippetContext
LOWsetup.py220except Exception as e:STRING
LOWtests/coverage_test/nn/test_coverage_loss_utils.py131 except Exception:CODE
LOW⚡tests/coverage_test/datasets/test_coverage_template.py374 except Exception:CODE
LOW…sts/coverage_test/cli/test_coverage_ernie_moe_utils.py72 except Exception:CODE
LOW…/coverage_test/cli/test_coverage_deepseek_v3_kernel.py52 except Exception:CODE
LOW⚡…/coverage_test/cli/test_coverage_deepseek_v3_kernel.py91except Exception as e:CODE
LOW⚡…overage_test/cli/test_coverage_tensorboard_callback.py115 except Exception:CODE
LOW⚡…e_test/transformers/test_coverage_kimi_k2_tokenizer.py168 except Exception:CODE
LOW⚡…e_test/transformers/test_coverage_kimi_k2_tokenizer.py176 except Exception:CODE
LOWtests/peft/test_lora.py213 except Exception as e:CODE
LOWtests/peft/test_lora.py283 except Exception as e:CODE
LOWtests/transformers/phi4/test_phi4_modeling.py149 except Exception:CODE
LOWtests/transformers/phi4/test_phi4_modeling.py210 except Exception:CODE
LOWtests/transformers/phi4/test_phi4_modeling.py426 except Exception:CODE
LOW⚡tests/transformers/intern_lm3/test_tokenizer.py28 except Exception:CODE
MEDIUMtests/transformers/intern_lm3/test_tokenizer.py25def setUpClass(cls):CODE
LOW⚡tests/transformers/intern_lm2_5/test_tokenizer.py29 except Exception:CODE
MEDIUMtests/transformers/intern_lm2_5/test_tokenizer.py26def setUpClass(cls):CODE
LOWtests/transformers/qwen3_vl/test_modeling_fleet.py33except Exception as error:CODE
LOWdocs/zh/custom_datasets_format_zh.md14 except Exception:CODE
MEDIUMdocs/zh/custom_datasets_format_zh.md9def load_parquet(file_path):CODE
LOW…mples/experiments/deepseek_v3_pretrain/load_hf_ckpt.py369 except Exception as e:CODE
LOW…rnie_pretrain/tools/sharded_to_uc/merge_sharding_ep.py612 except Exception:CODE
MEDIUM…rnie_pretrain/tools/sharded_to_uc/merge_sharding_ep.py614 print("Error !!!!")CODE
LOWexamples/experiments/ernie_pretrain/ernie/pretrain.py539 except Exception:CODE
LOW…e_pretrain/ernie/src/callbacks/tensorboard_callback.py25except Exception:CODE
LOWexamples/best_practices/PaddleOCR-VL/README.md565 except Exception:CODE
LOWexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md153 except Exception:CODE
LOWexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md231 except Exception:CODE
LOWexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md950 except Exception:CODE
MEDIUMexamples/best_practices/PaddleOCR-VL-1.5/region_ocr.md146def download_image_cv2(url):CODE
LOW…ples/best_practices/DeepSeek-V4/dequant_fp8_to_bf16.py188 except Exception as e:CODE
LOW…ples/best_practices/DeepSeek-V4/dequant_fp8_to_bf16.py285 except Exception as e:CODE
LOW…ces/tutorials/how_to_train_a_visual_grounding_model.md151 except Exception as e:CODE
LOW…ces/tutorials/how_to_train_a_visual_grounding_model.md178 except Exception as e:CODE
LOW…ces/tutorials/how_to_train_a_visual_grounding_model.md195 except Exception as e:CODE
LOW…ces/tutorials/how_to_train_a_visual_grounding_model.md296 except Exception as e:CODE
MEDIUM…ces/tutorials/how_to_train_a_visual_grounding_model.md678 print(f"Error: Image not found at: {full_image_path}")CODE
LOW…ces/tutorials/how_to_train_a_visual_grounding_model.md688 except Exception as e:CODE
LOWscripts/ci_utils/training_utils.py92 except Exception as e:CODE
LOWscripts/codestyle/check_dead_links.py68 except Exception as e:CODE
MEDIUMscripts/codestyle/check_dead_links.py69 print(f"Error reading {file_path}: {e}")CODE
MEDIUMscripts/regression/merge_configs.py210 print(f"Error: {origin_config_path} does not exist")CODE
MEDIUMscripts/regression/merge_configs.py214 print(f"Error: {update_config_path} does not exist")CODE
LOWscripts/regression/test_models.py212 except Exception as e:CODE
LOWscripts/regression/test_models.py235 except Exception as e:CODE
LOWscripts/regression/test_models.py634 except Exception as e:CODE
LOWscripts/ckpt_utils/kimik3_dequant_mxfp4_to_bf16.py437 except Exception:CODE
LOWscripts/ckpt_utils/kimik3_dequant_mxfp4_to_bf16.py500 except Exception as error:CODE
MEDIUM⚡.github/workflows/cleanup_ci_gists.yml55 print(f"Error: API returned {resp.status_code}: {resp.text}")CODE
LOW⚡.github/workflows/cleanup_ci_gists.yml60 except Exception as e:CODE
MEDIUM⚡.github/workflows/cleanup_ci_gists.yml61 print(f"Error parsing JSON: {e}")CODE
LOWpaddleformers/nn/pp_model.py651 except Exception:CODE
LOWpaddleformers/nn/moe_deepep/modular_moe_layer.py86 except Exception:CODE
LOWpaddleformers/datasets/collate.py640 except Exception:CODE
MEDIUMpaddleformers/datasets/SFTDataset.py246def _rss_mb():CODE
LOW⚡paddleformers/datasets/SFTDataset.py224 except Exception as e:CODE
LOW⚡paddleformers/datasets/SFTDataset.py228 except Exception:CODE
LOWpaddleformers/datasets/SFTDataset.py252 except Exception:CODE
LOWpaddleformers/datasets/SFTDataset.py327 except Exception as e:CODE
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Cross-Language Confusion16 hits · 88 pts
SeverityFileLineSnippetContext
HIGH⚡…age_test/transformers/test_coverage_longcontext_ops.py39 heap.push((0, 5))CODE
HIGH⚡…age_test/transformers/test_coverage_longcontext_ops.py40 heap.push((1, 3))CODE
HIGH⚡…age_test/transformers/test_coverage_longcontext_ops.py41 heap.push((2, 8))CODE
HIGHscripts/regression/test_models.py673 subprocess.run("pkill -9 -f 'paddleformers/cli/launcher.py' 2>/dev/null || true", shell=True)CODE
HIGHpaddleformers/quantization/quantization_linear.py332 "2) cd PaddleSlim && pip install -e .\n"CODE
HIGHpaddleformers/quantization/quantization_linear.py333 "3) cd csrc && python ./setup_cuda.py install"CODE
HIGHpaddleformers/quantization/quantization_linear.py522 "2) cd PaddleSlim && pip install -e .\n"CODE
HIGHpaddleformers/quantization/quantization_linear.py523 "3) cd csrc && python ./setup_cuda.py install"CODE
HIGHpaddleformers/quantization/quantization_linear.py761 "2) cd PaddleSlim && pip install -e .\n"CODE
HIGHpaddleformers/quantization/quantization_linear.py762 "3) cd csrc && python ./setup_cuda.py install"CODE
HIGHpaddleformers/transformers/video_utils.py323 f" 1. Install dependencies: `conda install ffmpeg -c conda-forge` or `apt-get update && apt-get install fCODE
HIGHpaddleformers/transformers/audio_processing_utils.py23 print("need to install audioread and librosa. Please try: pip install audioread && pip install librosa")CODE
HIGHpaddleformers/transformers/kimi_k25/media_utils.py103 f" 1. Install dependencies: `conda install ffmpeg -c conda-forge` or `apt-get update && apt-get install fCODE
HIGH…/transformers/ernie4_5_moe_vl/model/longcontext_ops.py134 surplus_piles.push([src_rank, surplus - move_amount])CODE
HIGH…/transformers/ernie4_5_moe_vl/model/longcontext_ops.py136 deficit_piles.push([dst_rank, deficit - move_amount])CODE
HIGHpaddleformers/transformers/qwen2_vl/vision_process.py286 f" 1. Install dependencies: `conda install ffmpeg -c conda-forge` or `apt-get update && apt-get install fCODE
Redundant / Tautological Comments51 hits · 74 pts
SeverityFileLineSnippetContext
LOWtests/transformers/test_video_processing_common.py277 # Set sampling to True. Video frames should be sampled with `num_frames` in the outputCOMMENT
LOWtests/transformers/test_cache_utils.py424 # Check if they are on the same device as the model parametersCOMMENT
LOWtests/transformers/qwen2_vl/test_video_processor.py302 # Set sampling to True. Video frames should be sampled with `num_frames` in the outputCOMMENT
LOWscripts/regression/prepare_datasets.py95 # Check if already existsCOMMENT
LOWscripts/regression/ci_model_unittest.sh130 # Check if file is in transformer directories (don't check file existence, rely on git diff)COMMENT
LOW.github/workflows/cherry-pick.yml90 # Check if target branch exists on remoteCOMMENT
LOW.github/workflows/cherry-pick.yml154 # Check if PR already existsCOMMENT
LOWpaddleformers/datasets/dataset.py206 # Check if selected name and split is valid in this DatasetBuilderCOMMENT
LOWpaddleformers/datasets/SFTDataset.py406 # Set flag to False and yield empty list to signal the end of estimationCOMMENT
LOWpaddleformers/datasets/SFTDataset.py443 # Set flag to False and yield empty list to signal the end of estimationCOMMENT
LOWpaddleformers/datasets/SFTDataset.py475 # Set flag to False and yield empty list to signal the end of estimationCOMMENT
LOWpaddleformers/datasets/SFTDataset.py506 # Set flag to False and yield empty list to signal the end of estimationCOMMENT
LOWpaddleformers/datasets/SFTDataset.py547 # Set flag to False and yield empty list to signal the end of estimationCOMMENT
LOWpaddleformers/datasets/DPODataset.py218 # Check if multimedia tags are included in "messages"+"chosen_response", and "messages"+"rejected_response"COMMENT
LOWpaddleformers/utils/upcast_downcast_triton.py726 # # Check if blocks and scales are on CPU, and move to GPU if soCOMMENT
LOWpaddleformers/utils/import_utils.py118 # Check if the package spec exists and grab its version to avoid importing a local directoryCOMMENT
LOWpaddleformers/utils/import_utils.py131 # Check if the version contains "dev"COMMENT
LOWpaddleformers/utils/import_utils.py161 # Check if the package spec exists and grab its version to avoid importing a local directoryCOMMENT
LOWpaddleformers/utils/import_utils.py174 # Check if the version contains "dev"COMMENT
LOW⚡paddleformers/utils/download/aistudio_hub_download.py714 # Check if file is cached as "no_exist"COMMENT
LOW⚡paddleformers/utils/download/aistudio_hub_download.py718 # Check if revision folder existsCOMMENT
LOW⚡paddleformers/utils/download/aistudio_hub_download.py726 # Check if file exists in cacheCOMMENT
LOWpaddleformers/cli/export/export.py97 # Check if the output directory is a valid model directory (contains .safetensors or .pdparams files)COMMENT
LOWpaddleformers/transformers/model_utils.py1741 # Check if README file already exist in repoSTRING
LOWpaddleformers/transformers/model_utils.py3061 # Check if `_keep_in_fp32_modules` is not NoneSTRING
LOW…dleformers/transformers/image_processing_utils_fast.py605 # Check if we have nested structure, assuming the nesting is consistentCOMMENT
LOWpaddleformers/transformers/image_utils.py752 # Check if image is in (n_channels, height, width) or (height, width, n_channels) formatCOMMENT
LOWpaddleformers/transformers/image_utils.py762 # Check if cropped area is within image boundariesCOMMENT
LOWpaddleformers/transformers/image_transforms.py438 # Check if cropped area is within image boundariesCOMMENT
LOWpaddleformers/transformers/feature_extraction_utils.py174 # Check if the args are a device or a dtypeSTRING
LOWpaddleformers/transformers/processing_utils.py913 # Check if tokenizer is fast - use backend attribute if available, otherwise fall back to class nameCOMMENT
LOWpaddleformers/transformers/utils.py690 # Check if the model is already cached or not. We only try the last checkpoint, this should cover most cases ofSTRING
LOWpaddleformers/transformers/gpt_provider.py214 # Check if mtp_block_spec parameter is supportedCOMMENT
LOWpaddleformers/transformers/masking_utils.py247 # Check if the mask can be safely skippedCOMMENT
LOWpaddleformers/transformers/kimi_k2/modeling.py186 # Check if mtp_block_spec parameter is supportedCOMMENT
LOWpaddleformers/transformers/kimi_k2/modeling.py228 # Check if mtp_block_spec parameter is supportedCOMMENT
LOW…dleformers/transformers/legacy/tokenizer_utils_base.py1981 # Check if README file already exist in repoCOMMENT
LOWpaddleformers/transformers/ernie4_5_moe_vl/tokenizer.py240 # Check if padding is neededCOMMENT
LOW…ddleformers/transformers/qwen3_vl_moe/configuration.py320 # Check if the attribute exists in sub-configsCOMMENT
LOW…ddleformers/transformers/qwen3_vl_moe/configuration.py356 # Check if user has set a top-level overrideCOMMENT
LOWpaddleformers/transformers/qwen3_vl/configuration.py309 # Check if the attribute exists in sub-configsCOMMENT
LOWpaddleformers/transformers/qwen3_vl/configuration.py345 # Check if user has set a top-level overrideCOMMENT
LOWpaddleformers/data/data_collator.py571 # Check if padding is necessary.COMMENT
LOWpaddleformers/data/data_collator.py607 # Check if padding is necessary.COMMENT
LOWpaddleformers/trainer/trainer.py2333 # Check if continuing training from a checkpointCOMMENT
LOWpaddleformers/trainer/trainer.py5011 # Check if we should delete older checkpoint(s)COMMENT
LOWpaddleformers/trainer/trainer.py5037 # Check if we should delete older hf checkpoint(s)COMMENT
LOWpaddleformers/trainer/trainer.py5628 # Set back to None to begin a new accumulationCOMMENT
LOWpaddleformers/trainer/integrations.py287 # Check if a Weights & Biases (wandb) API key is provided in the training argumentsCOMMENT
LOWpaddleformers/trainer/integrations.py453 # Check if SwanLab is disabled via environment variableCOMMENT
LOWpaddleformers/generation/utils.py282 # Check if we are done so that we can save a pad step if all(done)COMMENT
Verbosity Indicators38 hits · 73 pts
SeverityFileLineSnippetContext
LOW⚡tests/nn/test_attention.py163 # Step 1: Reshape tensors from [B, S, H, D] to [B, H, S, D] for matrix multiplicationCOMMENT
LOW⚡tests/nn/test_attention.py168 # Step 2: Transpose key for matmul: [B, H, S, D] -> [B, H, D, S]COMMENT
LOW⚡tests/nn/test_attention.py171 # Step 3: Calculate attention scores (Query @ Key^T) and apply scalingCOMMENT
LOW⚡tests/nn/test_attention.py174 # Step 4: Apply the attention mask if providedCOMMENT
LOW⚡tests/nn/test_attention.py179 # Step 5: Prepare and concatenate the sink logits. The sink is a special tokenCOMMENT
LOW⚡tests/nn/test_attention.py184 # Step 6: Apply softmax over the combined logits (scores + sink)COMMENT
LOW⚡tests/nn/test_attention.py188 # Step 7: Separate the attention probabilities from the sink probabilitiesCOMMENT
LOW⚡tests/nn/test_attention.py191 # Step 8: Apply dropout to the scoresCOMMENT
LOW⚡tests/nn/test_attention.py194 # Step 9: Compute the weighted sum of values (Scores @ Value)COMMENT
LOW⚡tests/nn/test_attention.py197 # Step 10: Reshape the output back to [B, S, H, D] and flatten the head dimensionCOMMENT
LOWpaddleformers/datasets/dataset.py669 # We need to check if the example contains label column and confirm its name.COMMENT
LOWpaddleformers/datasets/dataset.py705 # We need to check if the example contains label column and confirm its name.COMMENT
LOW⚡paddleformers/transformers/minimax_m2/modeling.py1091 # Step 1: Transpose fleet weightCOMMENT
LOW⚡paddleformers/transformers/minimax_m2/modeling.py1096 # Step 2: Split into per-group chunks along axis=0COMMENT
LOWpaddleformers/transformers/minimax_m2/modeling.py1118 # Step 3: Reassemble q_proj (interleaved Q+Gate)COMMENT
LOWpaddleformers/transformers/auto/feature_extraction.py180 # not all of these are nested. We need to check if it was saved recently as nested or if it is legacy styleCOMMENT
LOW⚡paddleformers/transformers/deepseek_v4/modeling.py1010 # Step 1: split up_gate_proj back to w1/w3 (intermediate, no transpose yet)COMMENT
LOW⚡paddleformers/transformers/deepseek_v4/modeling.py1016 # Step 2: transpose each piece to HF shapeCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py272 # Step 1: Split q_proj into 2*num_heads equal chunks (each = head_dim)COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py277 # Step 2: Split k_proj and v_proj into num_kv_heads chunksCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py282 # Step 3: Assemble per-group in fleet order and concatCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py353 # Step 2: 6 sources (q, k, v, z, b, a) → fused_in_proj with TP interleavingCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py357 # Step 3: Transpose to Fleet layout [hidden, in_proj_dim]COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py642 # Step 1: Transpose fleet weight [in, out] -> [out, in]COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py645 # Step 2: Split into per-group chunks along axis=0COMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py297 # Step 4: Transpose the fused weightCOMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py337 # Step 1: Split in_proj_qkv [qk_dim+qk_dim+v_dim, hidden] into q, k, v along axis=0COMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py662 # Step 3: Reassemble into HF formatCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py46 # Step 1: mock _add_accumulatorCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py56 # Step 2: mock _C_ops.adamw_ and _C_ops.adamwCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py203 # Step 1: mock _add_accumulatorCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py213 # Step 2: mock _C_ops.adamw_ and _C_ops.adamwCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py77 # Step 3: mock _insert_syncCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py95 # Step 4: mock Muon's momentum update and Muon._apply_optimizeCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py233 # Step 3: mock _insert_syncCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py251 # Step 4: mock Muon's momentum update and Muon._apply_optimizeCOMMENT
LOW⚡paddleformers/generation/utils.py389 # Step 1: Process input mask to generate basic expanded maskSTRING
LOWpaddleformers/generation/utils.py447 # Step 2: Convert boolean mask to numerical mask (adapt to different devices)STRING
Structural Annotation Overuse35 hits · 67 pts
SeverityFileLineSnippetContext
LOW⚡tests/nn/test_attention.py163 # Step 1: Reshape tensors from [B, S, H, D] to [B, H, S, D] for matrix multiplicationCOMMENT
LOW⚡tests/nn/test_attention.py168 # Step 2: Transpose key for matmul: [B, H, S, D] -> [B, H, D, S]COMMENT
LOW⚡tests/nn/test_attention.py171 # Step 3: Calculate attention scores (Query @ Key^T) and apply scalingCOMMENT
LOW⚡tests/nn/test_attention.py174 # Step 4: Apply the attention mask if providedCOMMENT
LOW⚡tests/nn/test_attention.py179 # Step 5: Prepare and concatenate the sink logits. The sink is a special tokenCOMMENT
LOW⚡tests/nn/test_attention.py184 # Step 6: Apply softmax over the combined logits (scores + sink)COMMENT
LOW⚡tests/nn/test_attention.py188 # Step 7: Separate the attention probabilities from the sink probabilitiesCOMMENT
LOW⚡tests/nn/test_attention.py191 # Step 8: Apply dropout to the scoresCOMMENT
LOW⚡tests/nn/test_attention.py194 # Step 9: Compute the weighted sum of values (Scores @ Value)COMMENT
LOW⚡tests/nn/test_attention.py197 # Step 10: Reshape the output back to [B, S, H, D] and flatten the head dimensionCOMMENT
LOW⚡paddleformers/transformers/minimax_m2/modeling.py1091 # Step 1: Transpose fleet weightCOMMENT
LOW⚡paddleformers/transformers/minimax_m2/modeling.py1096 # Step 2: Split into per-group chunks along axis=0COMMENT
LOWpaddleformers/transformers/minimax_m2/modeling.py1118 # Step 3: Reassemble q_proj (interleaved Q+Gate)COMMENT
LOW⚡paddleformers/transformers/deepseek_v4/modeling.py1010 # Step 1: split up_gate_proj back to w1/w3 (intermediate, no transpose yet)COMMENT
LOW⚡paddleformers/transformers/deepseek_v4/modeling.py1016 # Step 2: transpose each piece to HF shapeCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py272 # Step 1: Split q_proj into 2*num_heads equal chunks (each = head_dim)COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py277 # Step 2: Split k_proj and v_proj into num_kv_heads chunksCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py282 # Step 3: Assemble per-group in fleet order and concatCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py353 # Step 2: 6 sources (q, k, v, z, b, a) → fused_in_proj with TP interleavingCOMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py357 # Step 3: Transpose to Fleet layout [hidden, in_proj_dim]COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py642 # Step 1: Transpose fleet weight [in, out] -> [out, in]COMMENT
LOW⚡paddleformers/transformers/qwen3_5/modeling.py645 # Step 2: Split into per-group chunks along axis=0COMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py297 # Step 4: Transpose the fused weightCOMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py337 # Step 1: Split in_proj_qkv [qk_dim+qk_dim+v_dim, hidden] into q, k, v along axis=0COMMENT
LOWpaddleformers/transformers/qwen3_5/modeling.py662 # Step 3: Reassemble into HF formatCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py46 # Step 1: mock _add_accumulatorCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py56 # Step 2: mock _C_ops.adamw_ and _C_ops.adamwCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py203 # Step 1: mock _add_accumulatorCOMMENT
LOW⚡paddleformers/trainer/utils/offload_optimizer.py213 # Step 2: mock _C_ops.adamw_ and _C_ops.adamwCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py77 # Step 3: mock _insert_syncCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py95 # Step 4: mock Muon's momentum update and Muon._apply_optimizeCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py233 # Step 3: mock _insert_syncCOMMENT
LOWpaddleformers/trainer/utils/offload_optimizer.py251 # Step 4: mock Muon's momentum update and Muon._apply_optimizeCOMMENT
LOW⚡paddleformers/generation/utils.py389 # Step 1: Process input mask to generate basic expanded maskSTRING
LOWpaddleformers/generation/utils.py447 # Step 2: Convert boolean mask to numerical mask (adapt to different devices)STRING
Dead Code26 hits · 52 pts
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MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py77CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py79CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py80CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py85CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py90CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py91CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py99CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py111CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py112CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py116CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py117CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py118CODE
MEDIUM…e_pretrain/ernie/src/callbacks/moe_logging_callback.py120CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py78CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py80CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py81CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py86CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py91CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py92CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py100CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py112CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py113CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py117CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py118CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py119CODE
MEDIUM…n/ernie_pretrain/src/callbacks/moe_logging_callback.py121CODE
Fake / Example Data26 hits · 36 pts
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LOW⚡tests/coverage_test/datasets/test_coverage_mm_plugin.py171 mock_response.content = b"fake_data"CODE
LOW…ctices/tutorials/how_to_train_a_function_call_model.md96{"messages": [{"role": "user", "content": "I need to generate an invoice for a customer named John Doe. He bought 2 applCODE
LOW…ansformers/ernie4_5_moe_vl/model/modeling_moe_vl_pp.py969 fake_data = paddle.ones([pp_sd_group.nranks, 1])CODE
LOW…ansformers/ernie4_5_moe_vl/model/modeling_moe_vl_pp.py971 dist.alltoall(fake_out, fake_data, pp_sd_group)CODE
LOW⚡paddleformers/data/dist_dataloader.py151 fake_data = [nested_reduce_tensor(data)]CODE
LOW⚡paddleformers/data/dist_dataloader.py157 fake_data = [None]CODE
LOW⚡paddleformers/data/dist_dataloader.py160 fake_data = [nested_reduce_tensor(data)]CODE
LOW⚡paddleformers/data/dist_dataloader.py166 fake_data = [None]CODE
LOW⚡paddleformers/data/dist_dataloader.py169 fake_data,CODE
LOW⚡paddleformers/data/dist_dataloader.py175 fake_data,CODE
LOW⚡paddleformers/data/dist_dataloader.py180 fake_data = fake_data[0]CODE
LOW⚡paddleformers/data/dist_dataloader.py181 if fake_data is None:CODE
LOW⚡paddleformers/data/dist_dataloader.py187 data = nested_empty_tensor(fake_data)CODE
LOW⚡paddleformers/data/dist_dataloader.py190 data = nested_empty_tensor(fake_data)CODE
LOW⚡paddleformers/data/dist_dataloader.py436 fake_data = [nested_reduce_tensor(data)]CODE
LOW⚡paddleformers/data/dist_dataloader.py440 fake_data = [None]CODE
LOW⚡paddleformers/data/dist_dataloader.py443 fake_data = [nested_reduce_tensor(data)]CODE
LOW⚡paddleformers/data/dist_dataloader.py447 fake_data = [None]CODE
LOW⚡paddleformers/data/dist_dataloader.py450 fake_data,CODE
LOW⚡paddleformers/data/dist_dataloader.py456 fake_data,CODE
LOW⚡paddleformers/data/dist_dataloader.py461 fake_data = fake_data[0]CODE
LOW⚡paddleformers/data/dist_dataloader.py462 if fake_data is None:CODE
LOW⚡paddleformers/data/dist_dataloader.py468 data = nested_empty_tensor(fake_data)CODE
LOW⚡paddleformers/data/dist_dataloader.py471 data = nested_empty_tensor(fake_data)CODE
LOWpaddleformers/data/dist_dataloader.py387 fake_data = [None] * self._dataset_world_sizeCODE
LOWpaddleformers/data/dist_dataloader.py389 fake_data, src=self._stream_data_src, group=self._stream_data_groupCODE
AI Slop Vocabulary5 hits · 10 pts
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MEDIUMtests/generation/test_logits_process.py330 # scores = 0 to facilitate checksCOMMENT
LOWpaddleformers/datasets/DPODataset.py386 # The sequnece is too long, just return NoneCOMMENT
LOWpaddleformers/peft/lora/lora_model.py101 # If paddle_xpu is not installed, just use PaddleFormers's native lora layersCOMMENT
LOWpaddleformers/transformers/linear_utils.py82 # If paddle_xpu is not installed, just use Paddle's native Linear implementationsCOMMENT
MEDIUMpaddleformers/transformers/auto/tokenizer.py234 # First, let's see whether the tokenizer_type is passed so that we can leverage itCOMMENT
Slop Phrases5 hits · 6 pts
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LOWpaddleformers/nn/moe_deepep/modular_moe_layer.py314 # the current expert. We need to make sure to multiply the output hiddenCOMMENT
LOWpaddleformers/transformers/qwen2_moe/modeling.py370 # the current expert. We need to make sure to multiply the output hiddenCOMMENT
LOWpaddleformers/transformers/minicpm3/modeling.py542 # f"The cache structure has changed since version v4.36. If you are using {self.__class__.__name__} COMMENT
LOWpaddleformers/transformers/qwen3_moe/modeling.py368 # the current expert. We need to make sure to multiply the output hiddenCOMMENT
LOWpaddleformers/trainer/training_args.py353 If you set this value, `greater_is_better` will default to `True`. Don't forget to set it to `False` ifSTRING
Overly Generic Function Names3 hits · 4 pts
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LOW⚡tests/coverage_test/nn/test_coverage_loss_utils.py84 def my_function(x):CODE
LOW…/coverage_test/trainer/test_coverage_zero_cost_ckpt.py151 def my_function(state_dict):CODE
LOWpaddleformers/data/data_collator.py507 def process_data(self, data, pad_idx, max_len):CODE
TODO Padding2 hits · 3 pts
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LOWpaddleformers/nn/moe/moe_alltoall_layer.py82 # TODO: implement reduce in cuda opsCOMMENT
LOW…rs/transformers/ernie4_5_moe_vl/model/moe/moe_layer.py133 # TODO: implement reduce in cuda opsCOMMENT
Modern AI Meta-Vocabulary1 hit · 1 pts
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MEDIUMpaddleformers/transformers/tokenizer_utils.py227 "documents": [] # RAG context documentsSTRING