The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
This report presents the forensic synthetic code analysis of huggingface/pytorch-image-models, a Python project with 36,981 GitHub stars. SynthScan v2.0 examined 337,290 lines of code across 356 source files, recording 2077 pattern matches distributed across 18 syntactic categories. The overall adjusted score of 8.2 places this repository in the Low AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 2077 distinct pattern matches across 18 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | timm/optim/mars.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/lamb.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/adafactor.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/nvnovograd.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/adabelief.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/adamw.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/laprop.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/nadam.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/rmsprop_tf.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/madgrad.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/sgdw.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/lars.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/nadamw.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/optim/adopt.py | 0 | perform a single optimization step. args: closure (callable, optional): a closure that reevaluates the model and returns | STRING |
| HIGH | timm/models/repvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/tiny_vit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/ghostnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/davit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/efficientvit_mit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/rexnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/edgenext.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/swiftformer.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/nest.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/regnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/resnetv2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/efficientvit_msra.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/shvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/tresnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/fastvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/fasternet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/efficientformer.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/levit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/vovnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/inception_v4.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/maxxvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/metaformer.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/repghost.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/swin_transformer_v2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/pvt_v2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/mambaout.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/gcvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/starnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/inception_next.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/focalnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/pit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/swin_transformer_v2_cr.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/efficientformer_v2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/nextvit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/hgnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/volo.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/xcit.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/mvitv2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/twins.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/vision_transformer_sam.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/hiera.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/hieradet_sam2.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/vision_transformer_relpos.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/byobnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/tnt.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| HIGH | timm/models/rdnet.py | 0 | forward features that returns intermediates. args: x: input image tensor indices: take last n blocks if an int, if is a | STRING |
| 136 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | legacy_train.py | 53 | CODE | |
| LOW | train.py | 60 | CODE | |
| LOW | inference.py | 9 | CODE | |
| LOW | clean_checkpoint.py | 15 | CODE | |
| LOW | tests/test_scheduler.py | 18 | CODE | |
| LOW | tests/test_models.py | 30 | CODE | |
| LOW | timm/__init__.py | 1 | CODE | |
| LOW | timm/__init__.py | 2 | CODE | |
| LOW | timm/__init__.py | 2 | CODE | |
| LOW | timm/__init__.py | 2 | CODE | |
| LOW | timm/__init__.py | 2 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/__init__.py | 8 | CODE | |
| LOW | timm/layers/squeeze_excite.py | 13 | CODE | |
| LOW | timm/layers/classifier.py | 11 | CODE | |
| LOW | timm/layers/create_act.py | 4 | CODE | |
| LOW | timm/layers/create_act.py | 4 | CODE | |
| LOW | timm/layers/create_act.py | 6 | CODE | |
| LOW | timm/layers/create_act.py | 7 | CODE | |
| LOW | timm/layers/create_norm.py | 9 | CODE | |
| LOW | timm/layers/separable_conv.py | 8 | CODE | |
| LOW | timm/layers/trace_utils.py | 2 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 1 | CODE | |
| LOW | timm/layers/__init__.py | 11 | CODE | |
| LOW | timm/layers/__init__.py | 12 | CODE | |
| LOW | timm/layers/__init__.py | 12 | CODE | |
| LOW | timm/layers/__init__.py | 12 | CODE | |
| LOW | timm/layers/__init__.py | 12 | CODE | |
| LOW | timm/layers/__init__.py | 18 | CODE | |
| LOW | timm/layers/__init__.py | 18 | CODE | |
| LOW | timm/layers/__init__.py | 18 | CODE | |
| LOW | timm/layers/__init__.py | 18 | CODE | |
| LOW | timm/layers/__init__.py | 19 | CODE | |
| LOW | timm/layers/__init__.py | 19 | CODE | |
| LOW | timm/layers/__init__.py | 19 | CODE | |
| LOW | timm/layers/__init__.py | 20 | CODE | |
| LOW | timm/layers/__init__.py | 20 | CODE | |
| LOW | timm/layers/__init__.py | 21 | CODE | |
| LOW | timm/layers/__init__.py | 21 | CODE | |
| LOW | timm/layers/__init__.py | 22 | CODE | |
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| LOW | timm/layers/__init__.py | 23 | CODE | |
| LOW | timm/layers/__init__.py | 23 | CODE | |
| LOW | timm/layers/__init__.py | 23 | CODE | |
| LOW | timm/layers/__init__.py | 23 | CODE | |
| LOW | timm/layers/__init__.py | 24 | CODE | |
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| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | legacy_train.py | 1076 | CODE | |
| LOW | benchmark.py | 208 | CODE | |
| LOW | train.py | 1176 | CODE | |
| LOW | timm/layers/std_conv.py | 35 | CODE | |
| LOW | timm/layers/std_conv.py | 76 | CODE | |
| LOW | timm/layers/std_conv.py | 121 | CODE | |
| LOW | timm/layers/std_conv.py | 182 | CODE | |
| LOW | timm/layers/squeeze_excite.py | 30 | CODE | |
| LOW | timm/layers/squeeze_excite.py | 109 | CODE | |
| LOW | timm/layers/attention.py | 53 | CODE | |
| LOW | timm/layers/attention.py | 158 | CODE | |
| LOW | timm/layers/classifier.py | 226 | CODE | |
| LOW | timm/layers/attention_pool2d.py | 36 | CODE | |
| LOW | timm/layers/attention_pool2d.py | 187 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 168 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 86 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 337 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 404 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 542 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 1116 | CODE | |
| LOW | timm/layers/separable_conv.py | 19 | CODE | |
| LOW | timm/layers/separable_conv.py | 85 | CODE | |
| LOW | timm/layers/gather_excite.py | 29 | CODE | |
| LOW | timm/layers/non_local_attn.py | 153 | CODE | |
| LOW | timm/layers/other_pool.py | 195 | CODE | |
| LOW | timm/layers/other_pool.py | 286 | CODE | |
| LOW | timm/layers/bottleneck_attn.py | 122 | CODE | |
| LOW | timm/layers/bottleneck_attn.py | 185 | CODE | |
| LOW | timm/layers/lambda_layer.py | 73 | CODE | |
| LOW | timm/layers/lambda_layer.py | 171 | CODE | |
| LOW | timm/layers/attention_pool.py | 20 | CODE | |
| LOW | timm/layers/mlp.py | 19 | CODE | |
| LOW | timm/layers/mlp.py | 63 | CODE | |
| LOW | timm/layers/mlp.py | 120 | CODE | |
| LOW | timm/layers/mlp.py | 171 | CODE | |
| LOW | timm/layers/mlp.py | 218 | CODE | |
| LOW | timm/layers/mlp.py | 256 | CODE | |
| LOW | timm/layers/diff_attention.py | 37 | CODE | |
| LOW | timm/layers/hybrid_embed.py | 28 | CODE | |
| LOW | timm/layers/hybrid_embed.py | 228 | CODE | |
| LOW | timm/layers/conv_bn_act.py | 16 | CODE | |
| LOW | timm/layers/halo_attn.py | 142 | CODE | |
| LOW | timm/layers/halo_attn.py | 247 | CODE | |
| LOW | timm/layers/attention2d.py | 27 | CODE | |
| LOW | timm/layers/attention2d.py | 107 | CODE | |
| LOW | timm/layers/attention2d.py | 324 | CODE | |
| LOW | timm/layers/patch_embed.py | 32 | CODE | |
| LOW | timm/layers/patch_embed.py | 150 | CODE | |
| LOW | timm/layers/eca.py | 61 | CODE | |
| LOW | timm/layers/eca.py | 135 | CODE | |
| LOW | timm/layers/global_context.py | 23 | CODE | |
| LOW | timm/layers/split_attn.py | 38 | CODE | |
| LOW | timm/layers/selective_kernel.py | 63 | CODE | |
| LOW | timm/layers/cbam.py | 24 | CODE | |
| LOW | timm/layers/cbam.py | 54 | CODE | |
| LOW | timm/layers/cbam.py | 116 | CODE | |
| LOW | timm/layers/cbam.py | 150 | CODE | |
| LOW | timm/layers/cond_conv2d.py | 46 | CODE | |
| LOW | timm/layers/cond_conv2d.py | 139 | CODE | |
| LOW | timm/layers/norm_act.py | 64 | CODE | |
| 381 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_utils.py | 16 | def test_average_meter_zero_count(): | CODE |
| LOW | tests/test_utils.py | 74 | def test_activation_stats_hook_validation(): | CODE |
| LOW | tests/test_utils.py | 107 | def test_freeze_unfreeze_bn_root(): | CODE |
| LOW | tests/test_utils.py | 124 | def test_activation_stats_functions(): | CODE |
| LOW | tests/test_utils.py | 143 | def test_reparameterize_model(): | CODE |
| LOW | tests/test_utils.py | 172 | def test_get_state_dict_custom_unwrap(): | CODE |
| LOW | tests/test_utils.py | 190 | def test_freeze_unfreeze_string_input(): | CODE |
| LOW | tests/test_task.py | 64 | def _param_group_weight_decay(optimizer): | CODE |
| LOW | tests/test_task.py | 72 | def test_task_checkpoint_omits_empty_task_state_and_keeps_legacy_paths(tmp_path): | CODE |
| LOW | tests/test_task.py | 103 | def test_feature_distillation_checkpoint_keeps_projection_in_task_state(tmp_path): | CODE |
| LOW | tests/test_task.py | 141 | def test_feature_distillation_trainable_module_optimizer_grouping(): | CODE |
| LOW | tests/test_task.py | 167 | def test_base_eval_model_preserves_trainable_wrapper_for_use(): | CODE |
| LOW | tests/test_task.py | 177 | def test_compiled_ema_eval_model_reflects_update(): | CODE |
| LOW | tests/test_task.py | 202 | def test_compiled_eval_checkpoint_load_uses_unwrapped_state_dict_target(): | CODE |
| LOW | tests/test_layers.py | 81 | def test_get_act_layer_empty_string(): | CODE |
| LOW | tests/test_layers.py | 86 | def test_create_act_layer_inplace_error(): | CODE |
| LOW | tests/test_layers.py | 98 | def test_create_act_layer_edge_cases(): | CODE |
| LOW | tests/test_optim.py | 29 | def _test_basic_cases_template(weight, bias, input, constructor, scheduler_constructors): | CODE |
| LOW | tests/test_optim.py | 289 | def _build_params_dict_single(weight, bias, **kwargs): | CODE |
| LOW | tests/test_optim.py | 392 | def test_compiled_foreach_adam_optimizers(optimizer_name, foreach): | CODE |
| LOW | tests/test_optim.py | 434 | def test_compiled_muon_fallback(nesterov): | CODE |
| LOW | tests/test_optim.py | 615 | def test_param_groups_layer_decay_with_min(): | CODE |
| LOW | tests/test_optim.py | 638 | def test_param_groups_layer_decay_with_matcher(): | CODE |
| LOW | tests/test_optim.py | 665 | def test_param_groups_layer_decay_reg_token_stem(model_name): | CODE |
| LOW | tests/test_optim.py | 715 | def test_param_groups_weight_decay(): | CODE |
| LOW | tests/test_scheduler.py | 70 | def test_plateau_scheduler_step(self): | CODE |
| LOW | tests/test_scheduler.py | 122 | def test_warmup_prefix_reaches_target_lr(self, scheduler_cls, kwargs): | CODE |
| LOW | tests/test_scheduler.py | 347 | def test_state_dict_save_load(self, scheduler_cls, kwargs): | CODE |
| LOW | tests/test_scheduler.py | 368 | def test_plateau_state_dict_save_load(self): | CODE |
| LOW | tests/test_scheduler.py | 400 | def test_step_update_with_t_in_epochs_false(self, scheduler_cls, kwargs): | CODE |
| LOW | tests/test_scheduler.py | 430 | def test_multiple_param_groups(self, scheduler_cls, kwargs): | CODE |
| LOW⚡ | tests/test_models.py | 412 | def test_model_load_pretrained(model_name, batch_size): | CODE |
| LOW⚡ | tests/test_models.py | 421 | def test_model_features_pretrained(model_name, batch_size): | CODE |
| LOW⚡ | tests/test_models.py | 431 | def test_model_forward_torchscript(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 341 | def test_model_default_cfgs_non_std(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 461 | def test_model_forward_features(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 492 | def test_model_forward_intermediates_features(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 523 | def test_model_forward_intermediates(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 712 | def test_model_forward_fx_torchscript(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 737 | def test_model_forward_torchscript_with_features_fx(model_name, batch_size): | CODE |
| LOW | tests/test_models.py | 766 | def _create_naflex_pos_embed_test_module(ar_preserving): | CODE |
| LOW | tests/test_models.py | 782 | def _create_naflex_pos_embed_test_inputs(): | CODE |
| LOW | tests/test_models.py | 793 | def _naflex_dense_grid_sample_reference(module, x, patch_coord): | CODE |
| LOW | tests/test_models.py | 829 | def test_naflexvit_direct_grid_sample_parity(ar_preserving): | CODE |
| LOW | tests/test_models.py | 849 | def test_naflexvit_direct_grid_sample_fullgraph(ar_preserving): | CODE |
| LOW | tests/test_models.py | 867 | def test_naflexvit_direct_grid_sample_export(ar_preserving): | CODE |
| LOW | tests/test_models.py | 880 | def test_naflexvit_forward_intermediates_dict_input(): | CODE |
| LOW | tests/test_models.py | 918 | def test_naflexvit_key_only_attn_mask_is_opt_in_and_post_patch_dropout(): | CODE |
| LOW | tests/test_models.py | 953 | def test_naflexvit_key_only_attn_mask_output_parity(global_pool): | CODE |
| LOW | tests/test_checkpoint_loading.py | 23 | def test_weights_only_allows_argparse_namespace(tmp_path): | CODE |
| LOW | tests/test_checkpoint_loading.py | 36 | def test_weights_only_blocks_non_allowlisted_globals(tmp_path): | CODE |
| LOW | tests/test_checkpoint_loading.py | 52 | def test_resume_checkpoint_default_weights_only_namespace(tmp_path): | CODE |
| LOW | tests/test_checkpoint_loading.py | 82 | def test_resume_checkpoint_blocks_non_allowlisted_globals(tmp_path): | CODE |
| LOW | tests/test_checkpoint_loading.py | 95 | def test_resume_checkpoint_weights_only_false_allows_custom_globals(tmp_path): | CODE |
| LOW | tests/test_layers_drop.py | 125 | def test_deprecated_args_accepted(self): | CODE |
| LOW | tests/test_layers_drop.py | 156 | def test_couple_channels_parameter(self): | CODE |
| LOW | tests/test_layers_drop.py | 186 | def test_no_drop_when_prob_zero(self): | CODE |
| LOW | tests/test_layers_drop.py | 192 | def test_no_drop_when_not_training(self): | CODE |
| LOW | tests/test_layers_drop.py | 214 | def test_drop_path_no_scaling(self): | CODE |
| LOW | tests/test_layers_pool.py | 78 | def test_attention_pool_latent_basic(self): | CODE |
| 193 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | legacy_train.py | 428 | CODE | |
| LOW | legacy_train.py | 1076 | CODE | |
| LOW | legacy_train.py | 1288 | CODE | |
| LOW | benchmark.py | 163 | CODE | |
| LOW | benchmark.py | 564 | CODE | |
| LOW | benchmark.py | 620 | CODE | |
| LOW | benchmark.py | 305 | CODE | |
| LOW | validate.py | 175 | CODE | |
| LOW | validate.py | 462 | CODE | |
| LOW | validate.py | 491 | CODE | |
| LOW | train.py | 460 | CODE | |
| LOW | train.py | 1176 | CODE | |
| LOW | train.py | 1392 | CODE | |
| LOW | bulk_runner.py | 96 | CODE | |
| LOW | bulk_runner.py | 141 | CODE | |
| LOW | inference.py | 151 | CODE | |
| LOW | inference.py | 373 | CODE | |
| LOW | results/generate_csv_results.py | 20 | CODE | |
| LOW | timm/layers/classifier.py | 282 | CODE | |
| LOW | timm/layers/pos_embed_sincos.py | 1315 | CODE | |
| LOW | timm/layers/gather_excite.py | 29 | CODE | |
| LOW | timm/layers/non_local_attn.py | 71 | CODE | |
| LOW | timm/layers/adaptive_avgmax_pool.py | 42 | CODE | |
| LOW | timm/layers/adaptive_avgmax_pool.py | 127 | CODE | |
| LOW | timm/layers/inplace_abn.py | 43 | CODE | |
| LOW | timm/layers/pool1d.py | 4 | CODE | |
| LOW | timm/layers/create_attn.py | 22 | CODE | |
| LOW | timm/layers/weight_init.py | 110 | CODE | |
| LOW | timm/layers/norm_act.py | 278 | CODE | |
| LOW | timm/layers/norm_act.py | 322 | CODE | |
| LOW | timm/scheduler/scheduler_factory.py | 63 | CODE | |
| LOW | timm/optim/_param_groups.py | 19 | CODE | |
| LOW | timm/optim/sgdw.py | 195 | CODE | |
| LOW | timm/optim/sgdw.py | 241 | CODE | |
| LOW | timm/optim/_optim_factory.py | 177 | CODE | |
| LOW | timm/optim/lamb.py | 153 | CODE | |
| LOW | timm/optim/adafactor.py | 128 | CODE | |
| LOW | timm/optim/adafactor_bv.py | 210 | CODE | |
| LOW | timm/optim/adafactor_bv.py | 123 | CODE | |
| LOW | timm/optim/lars.py | 76 | CODE | |
| LOW | timm/optim/nvnovograd.py | 67 | CODE | |
| LOW | timm/optim/adamp.py | 90 | CODE | |
| LOW | timm/optim/adabelief.py | 107 | CODE | |
| LOW | timm/optim/adamw.py | 103 | CODE | |
| LOW | timm/optim/kron.py | 400 | CODE | |
| LOW | timm/optim/kron.py | 218 | CODE | |
| LOW | timm/optim/radam.py | 38 | CODE | |
| LOW | timm/optim/laprop.py | 80 | CODE | |
| LOW | timm/optim/muon.py | 531 | CODE | |
| LOW | timm/optim/muon.py | 783 | CODE | |
| LOW | timm/optim/rmsprop_tf.py | 100 | CODE | |
| LOW | timm/optim/sgdp.py | 50 | CODE | |
| LOW | timm/optim/madgrad.py | 91 | CODE | |
| LOW | timm/utils/model.py | 111 | CODE | |
| LOW | timm/utils/model.py | 233 | CODE | |
| LOW | timm/utils/model.py | 237 | CODE | |
| LOW | timm/models/davit.py | 470 | CODE | |
| LOW | timm/models/inception_resnet_v2.py | 299 | CODE | |
| LOW | timm/models/inception_resnet_v2.py | 303 | CODE | |
| LOW | timm/models/hrnet.py | 439 | CODE | |
| 89 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | timm/layers/attention.py | 12 | __all__ = ['Attention', 'AttentionRope', 'maybe_add_mask', 'resolve_self_attn_mask'] | CODE |
| LOW | timm/layers/config.py | 9 | __all__ = [ | CODE |
| LOW | timm/layers/_fx.py | 15 | __all__ = [ | CODE |
| LOW | timm/layers/typing.py | 7 | __all__ = ["LayerType", "PadType", "nullwrap", "disable_compiler"] | CODE |
| LOW | timm/scheduler/scheduler.py | 91 | def update_groups(self, values: Union[float, List[float]]) -> None: | CODE |
| LOW | timm/optim/_types.py | 29 | __all__ = ['ParamsT', 'OptimType', 'OptimizerCallable'] | CODE |
| LOW | timm/optim/sgdw.py | 22 | __all__ = ['SGDW', 'sgdw'] | CODE |
| LOW | timm/optim/adopt.py | 26 | __all__ = ["Adopt", "adopt"] | CODE |
| LOW | timm/models/repvit.py | 29 | __all__ = ['RepVit'] | CODE |
| LOW | timm/models/tiny_vit.py | 9 | __all__ = ['TinyVit'] | CODE |
| LOW | timm/models/deit.py | 25 | __all__ = ['VisionTransformerDistilled'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/ghostnet.py | 30 | __all__ = ['GhostNet'] | CODE |
| LOW | timm/models/volo.py | 36 | __all__ = ['VOLO'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/volo.py | 922 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/davit.py | 31 | __all__ = ['DaVit'] | CODE |
| LOW | timm/models/efficientvit_mit.py | 9 | __all__ = ['EfficientVit', 'EfficientVitLarge'] | CODE |
| LOW | timm/models/gemma4_vit.py | 29 | __all__ = ['Gemma4VitEncoder', 'Gemma4VitClassifier'] | CODE |
| LOW | timm/models/gemma4_vit.py | 787 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/gemma4_vit.py | 791 | def set_clamp_enabled(self, enabled: bool = True) -> None: | CODE |
| LOW | timm/models/gemma4_vit.py | 1120 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/gemma4_vit.py | 1124 | def set_clamp_enabled(self, enabled: bool = True) -> None: | CODE |
| LOW | timm/models/_efficientnet_blocks.py | 26 | __all__ = [ | CODE |
| LOW | timm/models/selecsls.py | 22 | __all__ = ['SelecSls'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/rexnet.py | 28 | __all__ = ['RexNet'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/rexnet.py | 335 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/inception_resnet_v2.py | 16 | __all__ = ['InceptionResnetV2'] | CODE |
| LOW | timm/models/edgenext.py | 36 | __all__ = ['EdgeNeXt'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/hrnet.py | 24 | __all__ = ['HighResolutionNet', 'HighResolutionNetFeatures'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/hieradet_sam2.py | 459 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/vgg.py | 20 | __all__ = ['VGG'] | CODE |
| LOW | timm/models/vgg.py | 195 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/byoanet.py | 22 | __all__ = [] | CODE |
| LOW | timm/models/convmixer.py | 15 | __all__ = ['ConvMixer'] | CODE |
| LOW | timm/models/swiftformer.py | 27 | __all__ = ['SwiftFormer'] | CODE |
| LOW | timm/models/nest.py | 49 | __all__ = ['Nest'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/cspnet.py | 28 | __all__ = ['CspNet'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/hardcorenas.py | 13 | __all__ = [] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/beit.py | 70 | __all__ = ['Beit'] | CODE |
| LOW | timm/models/vision_transformer_relpos.py | 39 | __all__ = ['VisionTransformerRelPos'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/xcit.py | 30 | __all__ = ['Xcit'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/regnet.py | 42 | __all__ = ['RegNet', 'RegNetCfg'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/regnet.py | 714 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/sequencer.py | 23 | __all__ = ['Sequencer2d'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/mvitv2.py | 33 | __all__ = ['MultiScaleVit', 'MultiScaleVitCfg'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/resnetv2.py | 47 | __all__ = ['ResNetV2'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/resnetv2.py | 664 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/vision_transformer.py | 79 | __all__ = ['VisionTransformer'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/vision_transformer.py | 979 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| LOW | timm/models/efficientvit_msra.py | 9 | __all__ = ['EfficientVitMsra'] | CODE |
| LOW | timm/models/xception_aligned.py | 21 | __all__ = ['XceptionAligned'] | CODE |
| LOW | timm/models/shvit.py | 27 | __all__ = ['SHViT'] | CODE |
| LOW | timm/models/tresnet.py | 21 | __all__ = ['TResNet'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/senet.py | 27 | __all__ = ['SENet'] | CODE |
| LOW | timm/models/fastvit.py | 32 | __all__ = ['FastVit'] | CODE |
| LOW | timm/models/_efficientnet_builder.py | 23 | __all__ = ["EfficientNetBuilder", "BlockArgs", "decode_arch_def", "efficientnet_init_weights", | CODE |
| LOW | timm/models/fasternet.py | 32 | __all__ = ['FasterNet'] | CODE |
| LOW | timm/models/efficientformer.py | 36 | __all__ = ['EfficientFormer'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/twins.py | 30 | __all__ = ['Twins'] # model_registry will add each entrypoint fn to this | CODE |
| LOW | timm/models/byobnet.py | 64 | __all__ = ['ByobNet', 'ByoModelCfg', 'ByoBlockCfg', 'create_byob_stem', 'create_block'] | CODE |
| LOW | timm/models/byobnet.py | 1635 | def set_grad_checkpointing(self, enable: bool = True) -> None: | CODE |
| 85 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | timm/optim/_optim_factory.py | 161 | Get the OptimInfo for an optimizer. Args: name: Name of the optimizer Returns: | STRING |
| HIGH | timm/optim/_optim_factory.py | 182 | Get the optimizer class with any default arguments applied. This allows direct instantiation of optimizers with | STRING |
| HIGH | timm/optim/_optim_factory.py | 245 | Create an optimizer instance. Args: model_or_params: Model or parameters to optimize op | STRING |
| HIGH | timm/optim/_optim_factory.py | 1107 | List available optimizer names, optionally filtered. List all registered optimizers, with optional filtering using | STRING |
| HIGH | timm/optim/_optim_factory.py | 1148 | Get the OptimInfo for an optimizer. Args: name: Name of the optimizer Returns: OptimInfo confi | STRING |
| HIGH | timm/optim/_optim_factory.py | 1166 | Get optimizer class by name with option to bind default arguments. Retrieves the optimizer class or a partial funct | STRING |
| HIGH | timm/optim/_optim_factory.py | 1215 | Create an optimizer instance via timm registry. Creates and configures an optimizer with appropriate parameter grou | STRING |
| HIGH | timm/optim/muon.py | 267 | Check if a parameter is suitable for Muon optimization. Args: param: Parameter tensor min_dim_size: | STRING |
| HIGH | timm/models/_efficientnet_builder.py | 82 | Decode block definition string Gets a list of block arg (dicts) through a string notation of arguments. E.g. i | STRING |
| HIGH | timm/data/auto_augment.py | 587 | Create a AutoAugment transform Args: config_str: String defining configuration of auto augmentation. Consi | STRING |
| HIGH | timm/data/auto_augment.py | 767 | Create a RandAugment transform Args: config_str (str): String defining configuration of random augmentatio | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | timm/optim/lion.py | 22 | # ============================================================================== | COMMENT |
| MEDIUM | timm/models/beit.py | 29 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/twins.py | 8 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/twins.py | 13 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2.py | 9 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2.py | 14 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer.py | 12 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer.py | 17 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/focalnet.py | 14 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/focalnet.py | 19 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/hiera.py | 11 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/hiera.py | 24 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 24 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 29 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | timm/data/tf_preprocessing.py | 23 | # ============================================================================== | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | timm/models/hieradet_sam2.py | 426 | self.head.fc.weight.data.mul_(head_init_scale) | CODE |
| CRITICAL | timm/models/hieradet_sam2.py | 427 | self.head.fc.bias.data.mul_(head_init_scale) | CODE |
| CRITICAL | timm/models/hiera.py | 631 | self.head.fc.weight.data.mul_(head_init_scale) | CODE |
| CRITICAL | timm/models/hiera.py | 632 | self.head.fc.bias.data.mul_(head_init_scale) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_optim.py | 341 | # _test_basic_cases( | COMMENT |
| LOW | timm/layers/pos_embed_rel.py | 41 | COMMENT | |
| LOW | timm/layers/patch_embed.py | 601 | return output | COMMENT |
| LOW | timm/layers/patch_embed.py | 621 | # embed_dim=768, | COMMENT |
| LOW | timm/layers/patch_embed.py | 641 | # self.flatten = flatten | COMMENT |
| LOW | timm/layers/cond_conv2d.py | 121 | COMMENT | |
| LOW | timm/optim/lion.py | 1 | """ Lion Optimizer | COMMENT |
| LOW | timm/optim/lamb.py | 21 | # Copyright (c) 2021, Habana Labs Ltd. All rights reserved. | COMMENT |
| LOW | timm/optim/lamb.py | 41 | # Permission is hereby granted, free of charge, to any person obtaining a copy | COMMENT |
| LOW | timm/optim/adan.py | 1 | """ Adan Optimizer | COMMENT |
| LOW | timm/utils/distributed.py | 121 | dist_backend = dist_backends.get(device_type, 'gloo') | COMMENT |
| LOW | timm/models/volo.py | 1 | """ Vision OutLOoker (VOLO) implementation | COMMENT |
| LOW | timm/models/efficientvit_mit.py | 1161 | hf_hub_id='timm/', | COMMENT |
| LOW | timm/models/efficientvit_mit.py | 1261 | # def efficientvit_l0_sam(pretrained=False, **kwargs): | COMMENT |
| LOW | timm/models/beit.py | 21 | primaryClass={cs.CV} | COMMENT |
| LOW | timm/models/efficientvit_msra.py | 661 | COMMENT | |
| LOW | timm/models/efficientvit_msra.py | 681 | # for k, v in tmp_dict.items(): | COMMENT |
| LOW | timm/models/shvit.py | 461 | COMMENT | |
| LOW | timm/models/shvit.py | 481 | # downsample_mapping[f'^stages\\.{i}\\.blocks\\.{j}\\.'] = f'stages.{i}.blocks.{j - 3}.' | COMMENT |
| LOW | timm/models/fasternet.py | 401 | # } | COMMENT |
| LOW | timm/models/twins.py | 101 | x = x[:, :H, :W, :].contiguous() | COMMENT |
| LOW | timm/models/twins.py | 121 | # x = x.reshape(B, _h, self.ws, _w, self.ws, C).transpose(2, 3) # B, _h, _w, ws, ws, C | COMMENT |
| LOW | timm/models/visformer.py | 521 | attn_stage='011', spatial_conv='100', norm_layer=nn.BatchNorm2d, conv_init=True, | COMMENT |
| LOW | timm/models/visformer.py | 541 | # model.default_cfg = _cfg() | COMMENT |
| LOW | timm/models/visformer.py | 561 | # | COMMENT |
| LOW | timm/models/visformer.py | 581 | # @register_model | COMMENT |
| LOW | timm/models/hiera.py | 1 | """ An PyTorch implementation of Hiera | COMMENT |
| LOW | timm/data/tf_preprocessing.py | 1 | """ Tensorflow Preprocessing Adapter | COMMENT |
| LOW | .github/workflows/trufflehog.yml | 21 | # unreachable), so we still fail on maybe-real secrets; 'unverified' (the noisy | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | avg_checkpoints.py | 85 | print("Error: Output filename ({}) already exists.".format(output)) | CODE |
| MEDIUM | avg_checkpoints.py | 113 | print('Error: No checkpoints found to average.') | CODE |
| MEDIUM | avg_checkpoints.py | 121 | print(f"Error: Checkpoint ({c}) doesn't exist") | CODE |
| LOW | bulk_runner.py | 203 | except Exception as e: | CODE |
| MEDIUM | clean_checkpoint.py | 42 | print("Error: Output filename ({}) already exists.".format(args.output)) | CODE |
| MEDIUM | clean_checkpoint.py | 110 | print("Error: Checkpoint ({}) doesn't exist".format(checkpoint)) | CODE |
| LOW | tests/test_models.py | 199 | except Exception: | CODE |
| LOW | tests/test_models.py | 560 | except Exception: | CODE |
| LOW | timm/layers/blur_pool.py | 118 | except Exception: | CODE |
| LOW | timm/optim/lion.py | 159 | except Exception: | STRING |
| LOW | timm/optim/adan.py | 127 | except Exception: | CODE |
| MEDIUM | timm/optim/adan.py | 34 | def __init__(self, chunk_size): | CODE |
| LOW | timm/optim/adamw.py | 216 | except Exception: | STRING |
| LOW | timm/optim/nadamw.py | 197 | except Exception: | STRING |
| LOW | timm/utils/jit.py | 33 | except Exception: | CODE |
| LOW | timm/utils/jit.py | 42 | except Exception: | CODE |
| LOW | timm/utils/checkpoint_saver.py | 122 | except Exception as e: | CODE |
| LOW | timm/utils/checkpoint_saver.py | 178 | except Exception as e: | CODE |
| LOW | timm/models/eva.py | 1237 | except Exception as e: | CODE |
| LOW | timm/models/_hub.py | 572 | except Exception as _: | CODE |
| LOW⚡ | timm/models/_helpers.py | 36 | except Exception: | CODE |
| LOW | timm/data/naflex_dataset.py | 550 | except Exception as e: | CODE |
| LOW | timm/data/readers/reader_wds.py | 57 | except Exception as e: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | legacy_train.py | 689 | # Check if we should use the NaFlex scheduled loader | COMMENT |
| LOW | legacy_train.py | 753 | # Check if we have model's patch size for NaFlex mode | COMMENT |
| LOW | train.py | 671 | # Check if we should use the NaFlex scheduled loader | COMMENT |
| LOW | train.py | 735 | # Check if we have model's patch size for NaFlex mode | COMMENT |
| LOW | timm/layers/pos_embed_sincos.py | 682 | # Check if we have pre-computed bands | COMMENT |
| LOW | timm/layers/blur_pool.py | 143 | # Check if aa_layer is a partial and already has device/dtype set | COMMENT |
| LOW | timm/optim/muon.py | 576 | # Increment step | COMMENT |
| LOW | timm/models/vision_transformer.py | 3072 | # Check if we should use NaFlexVit instead | COMMENT |
| LOW | timm/models/fastvit.py | 96 | # Check if SE-ReLU is requested | COMMENT |
| LOW | timm/models/naflexvit.py | 297 | # Check if we need EVA block features | COMMENT |
| LOW | timm/models/naflexvit.py | 1982 | # Check if it's a perfect square for a standard grid | COMMENT |
| LOW | timm/models/eva.py | 1306 | # Check if we should use NaFlexVit implementation | COMMENT |
| LOW | timm/models/_hub.py | 419 | # Check if README file already exist in repo | COMMENT |
| LOW | timm/models/_helpers.py | 111 | # Check if safetensors or not and load weights accordingly | COMMENT |
| LOW | timm/data/naflex_dataset.py | 119 | # Check if patches are flattened or unflattened | COMMENT |
| LOW | convert/convert_gemma4_vit.py | 97 | # Check if this is a vision key (vision_tower or vision_model) | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | timm/models/_factory.py | 85 | >>> # Create a MobileNetV3-Large model with no pretrained weights. | STRING |
| MEDIUM⚡ | timm/models/_factory.py | 88 | >>> # Create a MobileNetV3-Large model with pretrained weights. | STRING |
| MEDIUM⚡ | timm/models/_factory.py | 93 | >>> # Create a MobileNetV3-Large model with pretrained weights and a new head with 10 classes. | STRING |
| MEDIUM⚡ | timm/models/_factory.py | 98 | >>> # Create a Dinov2 small model with pretrained weights and save weights in a custom directory. | STRING |
| MEDIUM | timm/models/naflexvit.py | 1032 | # Create the float mask and apply masking using additive mask convention | COMMENT |
| MEDIUM | timm/models/hiera.py | 154 | # Create a view of the tensor with the patch stride as separate dims | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 98 | r"""This class implements window-based Multi-Head-Attention with log-spaced continuous position bias. | CODE |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 246 | r"""This class implements the Swin transformer block. | CODE |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 594 | r"""This class implements a stage of the Swin transformer including multiple layers. | CODE |
| MEDIUM | timm/data/naflex_loader.py | 422 | # Create the collator | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | timm/layers/norm_act.py | 156 | # but ONLY when used in conjunction with the timm conversion function below. | STRING |
| MEDIUM | timm/models/gemma4_vit.py | 1376 | # so the test harness' size-clamp doesn't land at 128 and blow the | COMMENT |
| MEDIUM | timm/models/swin_transformer_v2_cr.py | 681 | """ Updates the resolution to utilize and the window size and so the pair-wise relative positions. | STRING |
| MEDIUM | timm/data/imagenet_info.py | 41 | # which will be more robust than a guess based on num_classes | COMMENT |
| LOW | timm/data/naflex_dataset.py | 61 | # If no divisor specified, just use integer division | COMMENT |
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|---|---|---|---|---|
| HIGH | timm/models/naflexvit.py | 1620 | spatial reshape is undefined); with ``output_dict=True`` the result also carries 'patch_valid' | STRING |
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| LOW | timm/models/xception.py | 286 | # The resize parameter of the validation transform should be 333, and make sure to center crop at 299x299 | COMMENT |
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| LOW | timm/data/naflex_transforms.py | 261 | # Step 1: Get the maximum allowed dimensions from sequence length constraint | COMMENT |
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| LOW | timm/data/naflex_transforms.py | 261 | # Step 1: Get the maximum allowed dimensions from sequence length constraint | COMMENT |