SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
This report presents the forensic synthetic code analysis of NVlabs/Sana, a Python project with 8,470 GitHub stars. SynthScan v2.0 examined 148,335 lines of code across 478 source files, recording 1844 pattern matches distributed across 21 syntactic categories. The overall adjusted score of 18.9 places this repository in the Moderate AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
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 1844 distinct pattern matches across 21 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 |
|---|---|---|---|---|
| MEDIUM⚡ | environment_setup.sh | 2 | # ----------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | environment_setup.sh | 13 | # ----------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 615 | # ============================================================================ | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 617 | # ============================================================================ | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 875 | # ============================================================================ | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 877 | # ============================================================================ | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 936 | # ============================================================================ | COMMENT |
| MEDIUM⚡ | tools/metrics/sana_wm/eval_unified.py | 938 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 106 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 108 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 220 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 222 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 1046 | # ============================================================================ | COMMENT |
| MEDIUM | tools/metrics/sana_wm/eval_unified.py | 1048 | # ============================================================================ | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 15 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 17 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 81 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 83 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | diffusion/post_training/rewards.py | 107 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | diffusion/post_training/rewards.py | 109 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 185 | # ========================================================================= | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 187 | # ========================================================================= | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 319 | # ========================================================================= | COMMENT |
| MEDIUM | diffusion/post_training/rewards.py | 321 | # ========================================================================= | COMMENT |
| MEDIUM | …post_training/diffusers_patch/pipeline_with_logprob.py | 32 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …post_training/diffusers_patch/pipeline_with_logprob.py | 34 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 197 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 199 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 346 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 348 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 58 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 60 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 144 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 146 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 184 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 186 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 234 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 236 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 464 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | …usion/distributed/context_parallel/distributed_scan.py | 466 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 663 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM⚡ | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 665 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 69 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 71 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 118 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 120 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 151 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 153 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 270 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 272 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 313 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 315 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 346 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 348 | # ------------------------------------------------------------------ | COMMENT |
| MEDIUM | diffusion/utils/action_overlay.py | 43 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/utils/action_overlay.py | 45 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/utils/action_overlay.py | 121 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/utils/action_overlay.py | 123 | # --------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/model/edm_sample.py | 28 | # ---------------------------------------------------------------------------- | COMMENT |
| MEDIUM | diffusion/model/edm_sample.py | 83 | # ---------------------------------------------------------------------------- | COMMENT |
| 271 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/convert_sana_wm_refiner_to_diffusers.py | 42 | CODE | |
| LOW | tools/metrics/sana_wm/eval_unified.py | 51 | CODE | |
| LOW | tools/metrics/sana_wm/pose_utils.py | 3 | CODE | |
| LOW | tools/metrics/sana_wm/aggregate_results.py | 20 | CODE | |
| LOW | tools/metrics/geneval/generation/diffusers_generate.py | 15 | CODE | |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/inception.py | 7 | CODE | |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/inception.py | 9 | CODE | |
| LOW | tools/controlnet/inference_controlnet.py | 37 | CODE | |
| LOW | tools/controlnet/inference_controlnet.py | 37 | CODE | |
| LOW | tools/convert_scripts/convert_sana_to_svdquant.py | 2 | CODE | |
| LOW | tools/convert_scripts/convert_sana_to_diffusers.py | 2 | CODE | |
| LOW | …ols/convert_scripts/convert_sana_video_to_diffusers.py | 2 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 36 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 31 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 35 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 38 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 47 | CODE | |
| LOW | app/app_sana_multithread.py | 17 | CODE | |
| LOW | app/sana_pipeline.py | 28 | CODE | |
| LOW | app/sana_pipeline.py | 28 | CODE | |
| LOW | app/sana_pipeline.py | 28 | CODE | |
| LOW | app/sana_pipeline.py | 28 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 31 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 31 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 31 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 31 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 20 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 31 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 31 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 31 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 31 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 41 | CODE | |
| LOW | app/safety_check.py | 19 | CODE | |
| LOW | app/safety_check.py | 21 | CODE | |
| LOW | app/safety_check.py | 21 | CODE | |
| LOW | app/app_sana_4bit.py | 21 | CODE | |
| LOW | app/app_sana.py | 17 | CODE | |
| LOW | app/app_sana.py | 32 | CODE | |
| LOW | app/sana_sprint_pipeline.py | 32 | CODE | |
| LOW | app/sana_sprint_pipeline.py | 32 | CODE | |
| LOW | app/app_sana_inpaint.py | 8 | CODE | |
| LOW | app/app_sana_sprint.py | 17 | CODE | |
| LOW | sana/tools/__init__.py | 1 | CODE | |
| LOW | sana/tools/__init__.py | 2 | CODE | |
| LOW | sana/tools/__init__.py | 2 | CODE | |
| LOW | diffusion/__init__.py | 3 | CODE | |
| LOW | diffusion/__init__.py | 4 | CODE | |
| LOW | diffusion/__init__.py | 4 | CODE | |
| LOW | diffusion/__init__.py | 4 | CODE | |
| LOW | diffusion/__init__.py | 5 | CODE | |
| LOW | diffusion/__init__.py | 6 | CODE | |
| LOW | diffusion/__init__.py | 7 | CODE | |
| LOW | diffusion/__init__.py | 8 | CODE | |
| LOW | diffusion/__init__.py | 9 | CODE | |
| LOW | diffusion/post_training/rewards.py | 5 | CODE | |
| LOW | diffusion/post_training/dataset/pickscore/prpocess.py | 3 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 31 | CODE | |
| LOW | …usion/distributed/context_parallel/distributed_scan.py | 23 | CODE | |
| LOW | diffusion/distributed/context_parallel/config.py | 7 | CODE | |
| LOW | diffusion/distributed/context_parallel/halo_exchange.py | 16 | CODE | |
| 287 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/convert_sana_wm_refiner_to_diffusers.py | 135 | def fuse_distilled_lora_inplace( | CODE |
| LOW | tools/convert_sana_wm_refiner_to_diffusers.py | 191 | def convert_connectors_to_diffusers(checkpoint: dict[str, object]) -> dict[str, object]: | CODE |
| LOW⚡ | tools/metrics/sana_wm/eval_unified.py | 620 | def _build_stripped_video_dir(video_dir: str, output_dir: str) -> str: | CODE |
| LOW⚡ | tools/metrics/sana_wm/eval_unified.py | 941 | def eval_temporal_degradation( | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 94 | def _resolve_vbench_info_path(vbench_module) -> str: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 325 | def _vbench_torch_load_compat(): | CODE |
| LOW | tools/metrics/sana_wm/aggregate_results.py | 111 | def _compute_vbench_total_local(scores: dict[str, float]) -> dict[str, float]: | CODE |
| LOW | tools/metrics/sana_wm/aggregate_results.py | 133 | def _recompute_vbench_from_raw(eval_dir: str) -> dict[str, float]: | CODE |
| LOW | tools/metrics/sana_wm/eval_benchmark_poses.py | 50 | def _dataset_root_from_manifest(manifest_path: str) -> str: | CODE |
| LOW | tools/metrics/sana_wm/eval_benchmark_poses.py | 154 | def _resolve_skip_first_frame(arg_val: str, result_folder: str) -> bool: | CODE |
| LOW | tools/metrics/geneval/prompts/create_prompts.py | 38 | def generate_single_object_sample(rng: np.random.Generator, size: int = None): | CODE |
| LOW | tools/metrics/geneval/prompts/create_prompts.py | 62 | def generate_two_object_sample(rng: np.random.Generator): | CODE |
| LOW | tools/metrics/geneval/prompts/create_prompts.py | 128 | def generate_color_attribution_sample(rng: np.random.Generator): | CODE |
| LOW | tools/metrics/clip-score/clip_score.py | 231 | def calculate_clip_score_official(dataloader): | CODE |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 90 | def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6): | CODE |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 123 | def calculate_activation_statistics(files, model, batch_size=50, dims=2048, device="cpu", num_workers=1): | CODE |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 130 | def compute_statistics_of_path(path, model, batch_size, dims, device, num_workers=1, flag="ref"): | CODE |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 168 | def calculate_fid_given_paths(paths, batch_size, device, dims, num_workers=1): | CODE |
| LOW | tools/metrics/pytorch-fid/tests/test_fid_score.py | 13 | def test_calculate_fid_given_statistics(mocker, tmp_path, device): | CODE |
| LOW | tools/metrics/pytorch-fid/tests/test_fid_score.py | 41 | def test_compute_statistics_of_path(mocker, tmp_path, device): | CODE |
| LOW | tools/metrics/pytorch-fid/tests/test_fid_score.py | 62 | def test_compute_statistics_of_path_from_file(mocker, tmp_path, device): | CODE |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py | 153 | def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6): | CODE |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py | 206 | def calculate_activation_statistics(files, model, batch_size=50, dims=2048, device="cpu", num_workers=1): | CODE |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py | 230 | def compute_statistics_of_path(path, model, batch_size, dims, device, num_workers=1): | CODE |
| LOW | tools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py | 242 | def calculate_fid_given_paths(paths, batch_size, device, dims, num_workers=1): | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 76 | def _resolve_cp_runtime_config(config: SanaVideoCamCtrlConfig) -> object: | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 141 | def _build_parallelism_config(config: SanaVideoCamCtrlConfig, cp_size: int): | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 179 | def _resolve_data_dirs_under_root(data_dir, root: str): | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 219 | def _remove_custom_module_call(model, logger) -> None: | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 271 | def _right_pad_temporal_with_last_frame(tensor: torch.Tensor, dim: int, pad_size: int) -> torch.Tensor: | CODE |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 282 | def _map_global_chunk_index_to_local( | CODE |
| LOW | app/sana_pipeline.py | 52 | def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]: | CODE |
| LOW | app/sana_controlnet_pipeline.py | 54 | def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]: | CODE |
| LOW | app/sana_pipeline_inpaint.py | 56 | def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]: | CODE |
| LOW | app/sana_sprint_pipeline.py | 40 | def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]: | CODE |
| LOW | tests/bash/training/test_training_sana_wm_distill.sh | 128 | def configure_self_forcing_data(cfg): | CODE |
| LOW⚡ | diffusion/post_training/rewards.py | 97 | def _get_clip_image_transform(processor): | CODE |
| LOW⚡ | diffusion/post_training/rewards.py | 114 | def _patch_imagereward_compat(): | CODE |
| LOW⚡ | diffusion/post_training/rewards.py | 124 | def _apply_chunking_to_forward(forward_fn, chunk_size, chunk_dim, *input_tensors): | CODE |
| LOW | diffusion/post_training/rewards.py | 136 | def _find_pruneable_heads_and_indices(heads, n_heads, head_size, already_pruned_heads): | CODE |
| LOW⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 203 | def pipeline_with_logprob_flux( | CODE |
| LOW⚡ | …post_training/diffusers_patch/pipeline_with_logprob.py | 352 | def pipeline_with_logprob_sana( | CODE |
| LOW | diffusion/post_training/diffusers_patch/solver.py | 299 | def dpm_solver_first_order_update( | CODE |
| LOW | diffusion/post_training/diffusers_patch/solver.py | 318 | def multistep_dpm_solver_second_order_update( | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 1732 | def _clear_cross_attention_kv_cache(transformer: nn.Module) -> None: | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 1738 | def _has_cross_attention_kv_cache(transformer: nn.Module) -> bool: | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 1745 | def _cross_attention_with_cached_kv( | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2294 | def _prepared_module_cache_root() -> Path | None: | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2301 | def _prepared_module_cache_hash(payload: dict[str, object]) -> str: | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2329 | def _is_local_callable_for_pickle(value: object) -> bool: | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2338 | def _strip_local_callables_for_pickle(root: object) -> list[tuple[object, object, object, str]]: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 77 | def _load_diffusers_components(self) -> tuple[nn.Module, nn.Module]: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 142 | def _prepared_transformer_cache_path(self) -> Path | None: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 165 | def _save_prepared_transformer_cache(self) -> None: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 242 | def offload_video_unused_audio_modules(self, device: torch.device | str = "cpu") -> None: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 259 | def _attention_backend_context(self): | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 266 | def _uniform_timestep_tensors( | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 729 | def _forward_video_only_with_rope( | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1315 | def _build_rotary_emb_for_absolute_positions( | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1461 | def _streaming_self_attention( | CODE |
| 230 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/create_wids_metadata.py | 32 | CODE | |
| LOW | tools/convert_sana_wm_refiner_to_diffusers.py | 135 | CODE | |
| LOW | tools/metrics/utils.py | 4 | CODE | |
| LOW | tools/metrics/sana_wm/eval_unified.py | 378 | CODE | |
| LOW | tools/metrics/sana_wm/eval_unified.py | 673 | CODE | |
| LOW | tools/metrics/sana_wm/eval_unified.py | 1053 | CODE | |
| LOW | tools/metrics/sana_wm/pose_utils.py | 128 | CODE | |
| LOW | tools/metrics/sana_wm/eval_benchmark_poses.py | 177 | CODE | |
| LOW | tools/metrics/geneval/evaluation/evaluate_images.py | 151 | CODE | |
| LOW | tools/metrics/geneval/generation/diffusers_generate.py | 84 | CODE | |
| LOW | tools/metrics/clip-score/clip_score.py | 85 | CODE | |
| LOW | tools/metrics/clip-score/clip_score.py | 106 | CODE | |
| LOW | tools/metrics/dpg_bench/compute_dpg_bench.py | 132 | CODE | |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 130 | CODE | |
| LOW | tools/convert_scripts/convert_sana_to_svdquant.py | 47 | CODE | |
| LOW | tools/convert_scripts/convert_sana_to_diffusers.py | 47 | CODE | |
| LOW | …ols/convert_scripts/convert_sana_video_to_diffusers.py | 33 | CODE | |
| LOW | …t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py | 13 | CODE | |
| LOW | train_video_scripts/train_longsana.py | 30 | CODE | |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 456 | CODE | |
| LOW | train_video_scripts/train_sana_wm_stage1.py | 520 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 105 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 278 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 854 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 119 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 240 | CODE | |
| LOW | train_video_scripts/train_video_ivjoint.py | 739 | CODE | |
| LOW | app/sana_pipeline.py | 167 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 190 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 324 | CODE | |
| LOW | app/app_sana_inpaint.py | 44 | CODE | |
| LOW | app/app_sana_inpaint.py | 278 | CODE | |
| LOW | sana/cli/upload2hf.py | 50 | CODE | |
| LOW | diffusion/post_training/ema.py | 27 | CODE | |
| LOW | diffusion/post_training/diffusers_patch/solver.py | 15 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1461 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1745 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 2005 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 2485 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1044 | CODE | |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 2439 | CODE | |
| LOW | …usion/distributed/context_parallel/distributed_scan.py | 192 | CODE | |
| LOW | diffusion/guiders/adaptive_projected_guidance.py | 106 | CODE | |
| LOW | diffusion/scheduler/lcm_scheduler.py | 175 | CODE | |
| LOW | diffusion/scheduler/sana_streaming_sampler.py | 116 | CODE | |
| LOW | diffusion/scheduler/longlive_flow_euler_sampler.py | 420 | CODE | |
| LOW | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 74 | CODE | |
| LOW | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 675 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 138 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 334 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 414 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 438 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 482 | CODE | |
| LOW | diffusion/utils/misc.py | 317 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 138 | CODE | |
| LOW | diffusion/utils/logger.py | 197 | CODE | |
| LOW | diffusion/utils/optimizer.py | 52 | CODE | |
| LOW | diffusion/utils/optimizer.py | 325 | CODE | |
| LOW | diffusion/utils/optimizer.py | 501 | CODE | |
| LOW | diffusion/utils/optimizer.py | 623 | CODE | |
| 141 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | app/app_sana_controlnet_hed.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | app/app_sana_multithread.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | app/app_sana.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | app/app_sana_inpaint.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | scripts/interface.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | app/app_sana_4bit.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | app/app_sana_sprint.py | 0 | <div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs. | STRING |
| HIGH | diffusion/scheduler/scm_scheduler.py | 0 | output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, n | STRING |
| HIGH | diffusion/scheduler/lcm_scheduler.py | 0 | output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, n | STRING |
| HIGH | diffusion/scheduler/trigflow_scheduler.py | 0 | output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, n | STRING |
| HIGH | diffusion/scheduler/scm_scheduler.py | 0 | sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`) | STRING |
| HIGH | diffusion/scheduler/lcm_scheduler.py | 0 | sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`) | STRING |
| HIGH | diffusion/scheduler/trigflow_scheduler.py | 0 | sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`) | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_controlnet.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_adaln.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video_v2v.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video_camctrl.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_U_shape.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_U_shape_multi_scale.py | 0 | forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) t | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_controlnet.py | 0 | this method allows the object to be called like a function. it simply calls the forward method. | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video.py | 0 | this method allows the object to be called like a function. it simply calls the forward method. | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale.py | 0 | this method allows the object to be called like a function. it simply calls the forward method. | STRING |
| HIGH | diffusion/model/nets/sana.py | 0 | this method allows the object to be called like a function. it simply calls the forward method. | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video.py | 0 | a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning. | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale_video_camctrl.py | 0 | a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning. | STRING |
| HIGH | diffusion/model/nets/sana_multi_scale.py | 0 | a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning. | STRING |
| HIGH | …inear/modules/triton_lite_mla_kernels/pad_vk_mm_fwd.py | 0 | kernel for computing the matmul c = a x b. a has shape (m, k), b has shape (k, n) and c has shape (m, n) | STRING |
| HIGH | …ear/modules/triton_lite_mla_kernels/linear_relu_fwd.py | 0 | kernel for computing the matmul c = a x b. a has shape (m, k), b has shape (k, n) and c has shape (m, n) | STRING |
| HIGH | …ear/modules/triton_lite_mla_kernels/proj_divide_bwd.py | 0 | kernel for computing the matmul c = a x b. a has shape (m, k), b has shape (k, n) and c has shape (m, n) | STRING |
| HIGH | …/nets/fastlinear/modules/triton_lite_mla_kernels/mm.py | 0 | kernel for computing the matmul c = a x b. a has shape (m, k), b has shape (k, n) and c has shape (m, n) | STRING |
| HIGH | scripts/inference_geneval.py | 0 | \ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, author | STRING |
| HIGH | scripts/inference_geneval_diffusers.py | 0 | \ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, author | STRING |
| HIGH | scripts/inference_sana_sprint_geneval.py | 0 | \ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, author | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | environment_setup.sh | 1 | #!/usr/bin/env bash | COMMENT |
| LOW | tools/create_wids_metadata.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | tools/download.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | tools/convert_sana_wm_refiner_to_diffusers.py | 1 | #!/usr/bin/env python3 | COMMENT |
| LOW | tools/controlnet/inference_controlnet.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | train_video_scripts/train_video_ivjoint_chunk.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | train_video_scripts/train_video_ivjoint.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/app_sana_multithread.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | app/sana_pipeline.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/sana_controlnet_pipeline.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/sana_pipeline_inpaint.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/safety_check.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/app_sana_4bit.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | app/app_sana.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | app/sana_sprint_pipeline.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | app/app_sana_sprint.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | asset/examples.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | asset/docs/quantize/8bit_sana.md | 1 | <!-- Copyright 2024 The HuggingFace Team. All rights reserved. | COMMENT |
| LOW | asset/docs/quantize/4bit_sana.md | 1 | <!--Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | sana/tools/hf_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | sana/cli/run.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | sana/cli/upload2hf.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES (authored by @Lyken17) | COMMENT |
| LOW | diffusion/post_training/diffusers_patch/text_encode.py | 1 | #!/usr/bin/env python | COMMENT |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/guiders/adaptive_projected_guidance.py | 1 | # Copyright 2025 The HuggingFace Team. All rights reserved. | COMMENT |
| LOW | diffusion/scheduler/dpm_solver.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/scm_scheduler.py | 1 | # Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved. | COMMENT |
| LOW | diffusion/scheduler/flow_euler_sampler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/iddpm.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/sa_sampler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/lcm_scheduler.py | 1 | # Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved. | COMMENT |
| LOW | diffusion/scheduler/sana_streaming_sampler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/trigflow_scheduler.py | 1 | # Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved. | COMMENT |
| LOW | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 121 | # | COMMENT |
| LOW | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 501 | # over [sink + window + current], cached tokens already have the | COMMENT |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 1 | # Licensed under the Apache License, Version 2.0 (the "License"); | COMMENT |
| LOW | diffusion/utils/lr_scheduler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/camctrl_config.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/misc.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/config.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/checkpoint.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/chunk_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/logger.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/action_overlay.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/optimizer.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/cam_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/utils/dist_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/model_growth_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/respace.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/dpm_solver.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/registry.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/timestep_sampler.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/diffusion_utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/edm_sample.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/builder.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/act.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/utils.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/liger_norms.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| LOW | diffusion/model/gaussian_diffusion.py | 1 | # Copyright 2024 NVIDIA CORPORATION & AFFILIATES | COMMENT |
| 124 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | app/app_sana_multithread.py | 234 | CODE | |
| LOW | app/app_sana_multithread.py | 283 | CODE | |
| LOW | app/sana_pipeline.py | 167 | CODE | |
| LOW | app/sana_controlnet_pipeline.py | 190 | CODE | |
| LOW | app/sana_pipeline_inpaint.py | 324 | CODE | |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 24 | CODE | |
| LOW | app/app_sana_4bit.py | 175 | CODE | |
| LOW | app/app_sana.py | 239 | CODE | |
| LOW | app/sana_sprint_pipeline.py | 150 | CODE | |
| LOW | app/app_sana_sprint.py | 217 | CODE | |
| LOW | …post_training/diffusers_patch/pipeline_with_logprob.py | 38 | CODE | |
| LOW | …post_training/diffusers_patch/pipeline_with_logprob.py | 203 | CODE | |
| LOW | …post_training/diffusers_patch/pipeline_with_logprob.py | 352 | CODE | |
| LOW | diffusion/distributed/context_parallel/halo_exchange.py | 127 | CODE | |
| LOW | diffusion/guiders/adaptive_projected_guidance.py | 49 | CODE | |
| LOW | diffusion/scheduler/dpm_solver.py | 23 | CODE | |
| LOW | diffusion/scheduler/iddpm.py | 26 | CODE | |
| LOW | diffusion/scheduler/sa_sampler.py | 49 | CODE | |
| LOW | diffusion/scheduler/lcm_scheduler.py | 175 | CODE | |
| LOW | diffusion/scheduler/trigflow_scheduler.py | 100 | CODE | |
| LOW | diffusion/scheduler/longlive_flow_euler_sampler.py | 93 | CODE | |
| LOW | diffusion/scheduler/sa_solver_diffusers.py | 138 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 30 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 76 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 138 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 230 | CODE | |
| LOW | diffusion/utils/checkpoint.py | 264 | CODE | |
| LOW | diffusion/utils/dist_utils.py | 293 | CODE | |
| LOW | diffusion/model/dpm_solver.py | 266 | CODE | |
| LOW | diffusion/model/dpm_solver.py | 1504 | CODE | |
| LOW | diffusion/model/dpm_solver.py | 1545 | CODE | |
| LOW | diffusion/model/dpm_solver.py | 1789 | CODE | |
| LOW | diffusion/model/edm_sample.py | 32 | CODE | |
| LOW | diffusion/model/edm_sample.py | 88 | CODE | |
| LOW | diffusion/model/gaussian_diffusion.py | 633 | CODE | |
| LOW | diffusion/model/gaussian_diffusion.py | 666 | CODE | |
| LOW | diffusion/model/sa_solver.py | 211 | CODE | |
| LOW | diffusion/model/sa_solver.py | 892 | CODE | |
| LOW | diffusion/model/sa_solver.py | 1092 | CODE | |
| LOW | diffusion/model/sa_solver.py | 1291 | CODE | |
| LOW | diffusion/model/wan2_2/vae.py | 688 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 471 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 831 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 1022 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 1151 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 1303 | CODE | |
| LOW | diffusion/model/ltx2/causal_vae.py | 1499 | CODE | |
| LOW | diffusion/model/nets/sana_multi_scale_controlnet.py | 87 | CODE | |
| LOW | diffusion/model/nets/sana_multi_scale_video.py | 71 | CODE | |
| LOW | diffusion/model/nets/sana_multi_scale_video.py | 345 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 263 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 291 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 388 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 495 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 624 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 675 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 717 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 765 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 1194 | CODE | |
| LOW | diffusion/model/nets/sana_blocks.py | 1238 | CODE | |
| 81 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | tools/metrics/sana_wm/eval_unified.py | 865 | except Exception as e: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 296 | except Exception: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 306 | except Exception: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 464 | except Exception: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 516 | except Exception: | CODE |
| LOW | tools/metrics/sana_wm/eval_unified.py | 666 | except Exception as e: | CODE |
| LOW | tools/metrics/sana_wm/pose_utils.py | 140 | except Exception as exc: | CODE |
| MEDIUM | tools/metrics/sana_wm/pose_utils.py | 141 | print(f"Error loading {video_path}: {exc}") | CODE |
| LOW | tools/metrics/sana_wm/pose_utils.py | 165 | except Exception as exc: | CODE |
| LOW | tools/metrics/sana_wm/pose_utils.py | 180 | except Exception as exc: | CODE |
| MEDIUM | tools/metrics/sana_wm/pose_utils.py | 181 | print(f"Error inferencing {video_paths[valid_index]}: {exc}") | CODE |
| MEDIUM | tools/metrics/sana_wm/eval_benchmark_poses.py | 211 | print("Error: Pi3 not found. Install Pi3 or place it on PYTHONPATH.") | CODE |
| LOW | tools/metrics/sana_wm/eval_benchmark_poses.py | 334 | except Exception as e: | CODE |
| MEDIUM | tools/metrics/sana_wm/eval_benchmark_poses.py | 335 | print(f"Error evaluating {scene_id}: {e}") | CODE |
| LOW | tools/metrics/clip-score/clip_score.py | 199 | except Exception as e: | CODE |
| MEDIUM | tools/metrics/clip-score/clip_score.py | 179 | def process_sample(sample): | CODE |
| LOW | tools/metrics/dpg_bench/compute_dpg_bench.py | 246 | except Exception as e: | CODE |
| LOW | tools/metrics/pytorch-fid/compute_fid.py | 42 | except Exception as e: | CODE |
| LOW⚡ | …t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py | 52 | except Exception as e: | CODE |
| MEDIUM⚡ | …t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py | 53 | print(f"Error processing file {filename}: {e}") | CODE |
| LOW | train_video_scripts/train_video_ivjoint.py | 370 | except Exception as e: | CODE |
| MEDIUM | train_video_scripts/train_video_ivjoint.py | 371 | print(f"Error in vae_encode: {e}") | CODE |
| LOW | train_video_scripts/train_video_ivjoint.py | 483 | except Exception: | CODE |
| LOW | app/app_sana_inpaint.py | 253 | except Exception as e: | CODE |
| LOW | app/app_sana_inpaint.py | 264 | except Exception as e: | CODE |
| LOW | app/app_sana_inpaint.py | 469 | except Exception as e: | CODE |
| LOW | sana/tools/hf_utils.py | 97 | except Exception as e: | CODE |
| MEDIUM | sana/tools/hf_utils.py | 98 | print(f"Error downloading file: {e}") | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2310 | except Exception: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 91 | except Exception as exc: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 161 | except Exception: | CODE |
| LOW | diffusion/refiner/diffusers_ltx2_refiner.py | 187 | except Exception as exc: | CODE |
| LOW | diffusion/scheduler/longlive_flow_euler_sampler.py | 307 | except Exception: | CODE |
| LOW | diffusion/scheduler/longlive_flow_euler_sampler.py | 351 | except Exception: | CODE |
| LOW | diffusion/utils/git.py | 167 | except Exception as e: | CODE |
| LOW | diffusion/utils/checkpoint.py | 170 | except Exception as exc: | CODE |
| LOW | diffusion/utils/action_overlay.py | 138 | except Exception: | CODE |
| LOW | diffusion/model/nets/sana_multi_scale_video.py | 1013 | except Exception as e: | CODE |
| MEDIUM | diffusion/model/nets/sana_multi_scale_video.py | 1014 | print(f"Error loading {key}: {e}") | CODE |
| LOW | diffusion/model/nets/sana_multi_scale_video_camctrl.py | 1527 | except Exception as e: | CODE |
| LOW | diffusion/model/nets/sana.py | 402 | except Exception as e: | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/image.py | 69 | except Exception: | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/image.py | 177 | except Exception: | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/dist.py | 43 | except Exception: | CODE |
| LOW | diffusion/model/ops/fused_gdn.py | 1719 | except Exception as e: | CODE |
| LOW | diffusion/model/ops/fused_gdn.py | 2086 | except Exception as e: | CODE |
| LOW | diffusion/model/ops/fused_gdn_chunkwise_cuda.py | 741 | except Exception: | CODE |
| LOW | diffusion/model/ops/fused_gdn_chunkwise_cuda.py | 827 | except Exception as e: # missing toolkit / unexpected shape -> Triton | CODE |
| LOW | diffusion/model/ops/fused_gdn_chunkwise_cuda.py | 906 | except Exception as e: # missing toolkit / unexpected shape -> Triton | CODE |
| LOW⚡ | diffusion/model/ops/fused_gdn_chunkwise.py | 1156 | except Exception: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 29 | except Exception: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 176 | except Exception: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 198 | except Exception: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 211 | except Exception: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 247 | except Exception as e: | CODE |
| LOW | …line/sana_inference_interactive_pipeline_long_chunk.py | 250 | except Exception: | CODE |
| LOW | …ngsana/pipeline/sana_inference_interactive_pipeline.py | 32 | except Exception: | CODE |
| LOW | …ngsana/pipeline/sana_inference_interactive_pipeline.py | 192 | except Exception: | CODE |
| LOW | …ngsana/pipeline/sana_inference_interactive_pipeline.py | 251 | except Exception: | CODE |
| LOW | …ngsana/pipeline/sana_inference_interactive_pipeline.py | 265 | except Exception: | CODE |
| 56 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | …t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py | 57 | # Create a TAR file and include all files | COMMENT |
| MEDIUM | app/safety_check.py | 16 | # This file is copy from https://github.com/mit-han-lab/hart/blob/main/hart/utils/safety_check.py | COMMENT |
| MEDIUM | diffusion/post_training/stat_tracking.py | 93 | # Create a mask for the current group. | COMMENT |
| MEDIUM | diffusion/utils/cam_utils.py | 77 | # Create the base (N, 4, 4) tensor (identity matrix padded) | COMMENT |
| MEDIUM | diffusion/model/dpm_solver.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_multi_scale_controlnet.py | 19 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_multi_scale_video.py | 18 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_blocks.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_multi_scale_adaln.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_gdn_blocks.py | 70 | """This function is intended to align with the l2norm implementation in the FLA library.""" | STRING |
| MEDIUM | diffusion/model/nets/sana_U_shape.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_multi_scale_video_camctrl.py | 18 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/basic_modules.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_U_shape_multi_scale.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana_multi_scale.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/model/nets/sana.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/data/datasets/sana_data_multi_scale.py | 18 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/data/datasets/sana_data.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/data/datasets/utils.py | 17 | # This file is modified from https://github.com/PixArt-alpha/PixArt-sigma | COMMENT |
| MEDIUM | diffusion/data/wids/wids_tar.py | 17 | # This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| MEDIUM | diffusion/data/wids/wids_tar.py | 49 | # Create the index | COMMENT |
| MEDIUM | diffusion/data/wids/wids_tar.py | 59 | # Create an empty list for the index | COMMENT |
| MEDIUM | diffusion/data/wids/wids_mmtar.py | 17 | # This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| MEDIUM | diffusion/data/wids/__init__.py | 2 | # This file is part of the WebDataset library. | COMMENT |
| MEDIUM | diffusion/data/wids/wids_specs.py | 17 | # This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| MEDIUM | diffusion/data/wids/wids.py | 17 | # This file is modified from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| MEDIUM | diffusion/data/wids/wids_dl.py | 17 | # This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| MEDIUM | diffusion/data/wids/wids_lru.py | 17 | # This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/wids | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | app/safety_check.py | 23 | __all__ = ["is_dangerous"] | CODE |
| LOW⚡ | diffusion/refiner/diffusers_ltx2_refiner.py | 2345 | def set_value(owner: object, key: object, old_value: object, new_value: object, kind: str) -> None: | CODE |
| LOW | diffusion/distributed/context_parallel/config.py | 66 | def set_cp_runtime_config(config: CpRuntimeConfig) -> None: | CODE |
| LOW | diffusion/distributed/context_parallel/config.py | 77 | def set_cp_group(group: ProcessGroup | None) -> None: | CODE |
| LOW | diffusion/distributed/context_parallel/__init__.py | 29 | __all__ = [ | CODE |
| LOW | diffusion/guiders/__init__.py | 3 | __all__ = ["AdaptiveProjectedGuidance"] | CODE |
| LOW | diffusion/utils/import_utils.py | 8 | logger = logging.getLogger(__name__) | CODE |
| LOW | diffusion/model/act.py | 21 | __all__ = ["build_act", "get_act_name"] | CODE |
| LOW | diffusion/model/liger_norms.py | 33 | logger = logging.getLogger(__name__) | CODE |
| LOW | diffusion/model/norms.py | 23 | __all__ = ["LayerNorm2d", "build_norm", "get_norm_name", "reset_bn", "remove_bn", "set_norm_eps"] | CODE |
| LOW | diffusion/model/norms.py | 173 | def set_norm_eps(model: nn.Module, eps: float or None = None, momentum: float or None = None) -> None: | CODE |
| LOW | diffusion/model/wan2_2/vae.py | 13 | __all__ = [ | CODE |
| LOW | diffusion/model/ltx2/causal_vae.py | 203 | def update_tail(self, z: torch.Tensor, prepend_prev_latent_frames: int) -> None: | CODE |
| LOW | diffusion/model/nets/fastlinear/modules/nn/norm.py | 24 | __all__ = ["LayerNorm2d", "build_norm", "get_norm_name", "reset_bn", "remove_bn", "set_norm_eps"] | CODE |
| LOW | diffusion/model/nets/fastlinear/modules/nn/norm.py | 174 | def set_norm_eps(model: nn.Module, eps: float or None = None, momentum: float or None = None) -> None: | CODE |
| LOW | diffusion/model/nets/fastlinear/modules/nn/act.py | 21 | __all__ = ["build_act", "get_act_name"] | CODE |
| LOW | diffusion/model/wan/attention.py | 25 | __all__ = [ | CODE |
| LOW | diffusion/model/wan/t5.py | 12 | __all__ = [ | CODE |
| LOW | diffusion/model/wan/__init__.py | 8 | __all__ = [ | CODE |
| LOW | diffusion/model/wan/model.py | 17 | __all__ = ["WanModel"] | CODE |
| LOW | diffusion/model/wan/clip.py | 17 | __all__ = [ | CODE |
| LOW | diffusion/model/wan/xlm_roberta.py | 7 | __all__ = ["XLMRoberta", "xlm_roberta_large"] | CODE |
| LOW | diffusion/model/wan/vae.py | 15 | __all__ = [ | CODE |
| LOW | diffusion/model/wan/tokenizers.py | 9 | __all__ = ["HuggingfaceTokenizer"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/ae_model_zoo.py | 38 | __all__ = ["create_dc_ae_model_cfg", "DCAE_HF", "AutoencoderKL"] | CODE |
| LOW | …/model/dc_ae/efficientvit/models/nn/triton_rms_norm.py | 21 | __all__ = ["TritonRMSNorm2dFunc"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/nn/norm.py | 26 | __all__ = ["LayerNorm2d", "TritonRMSNorm2d", "build_norm", "reset_bn", "set_norm_eps"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/nn/norm.py | 201 | def set_norm_eps(model: nn.Module, eps: Optional[float] = None) -> None: | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/nn/ops.py | 38 | __all__ = [ | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/nn/act.py | 24 | __all__ = ["build_act"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/nn/drop.py | 27 | __all__ = ["apply_drop_func"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/models/utils/list.py | 19 | __all__ = [ | CODE |
| LOW | …fusion/model/dc_ae/efficientvit/models/utils/random.py | 22 | __all__ = [ | CODE |
| LOW | …usion/model/dc_ae/efficientvit/models/utils/network.py | 26 | __all__ = [ | CODE |
| LOW | …/model/dc_ae/efficientvit/models/efficientvit/dc_ae.py | 41 | __all__ = ["DCAE", "dc_vae_f32", "dc_ae_f32c32", "dc_ae_f64c128", "dc_ae_f128c512"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/setup.py | 24 | __all__ = [ | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/misc.py | 22 | __all__ = [ | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/lr.py | 24 | __all__ = ["CosineLRwithWarmup", "ConstantLRwithWarmup"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/ema.py | 25 | __all__ = ["EMA"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/ema.py | 28 | def update_ema(ema: nn.Module, new_state_dict: dict[str, torch.Tensor], decay: float) -> None: | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/export.py | 26 | __all__ = ["export_onnx"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/opt.py | 21 | __all__ = ["REGISTERED_OPTIMIZER_DICT", "build_optimizer"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/metric.py | 23 | __all__ = ["AverageMeter"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/init.py | 23 | __all__ = ["init_modules", "zero_last_gamma"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/image.py | 26 | __all__ = ["load_image", "load_image_from_dir", "DMCrop", "CustomImageFolder", "ImageDataset"] | CODE |
| LOW | diffusion/model/dc_ae/efficientvit/apps/utils/dist.py | 25 | __all__ = [ | CODE |
| LOW | …on/model/dc_ae/efficientvit/apps/trainer/run_config.py | 25 | __all__ = ["Scheduler", "RunConfig"] | CODE |
| LOW | …on/model/dc_ae/efficientvit/apps/trainer/run_config.py | 107 | def update_global_step(self, epoch, batch_id=0) -> None: | CODE |
| LOW | diffusion/model/ops/fused_cam_gdn.py | 2432 | __all__ = [ | CODE |
| LOW | diffusion/model/ops/fused_gdn_chunkwise_stateful_bwd.py | 146 | __all__ = [ | CODE |
| LOW | diffusion/model/ops/fused_gdn_cp.py | 80 | __all__ = [ | CODE |
| LOW | diffusion/model/ops/__init__.py | 82 | __all__ = [ | CODE |
| LOW | diffusion/model/ops/fused_gdn_chunkwise_stateful_raw.py | 591 | __all__ = [ | CODE |
| LOW | diffusion/model/ops/frame_gdn/__init__.py | 5 | __all__ = ["_build_transition_matrices"] | CODE |
| LOW | diffusion/model/ops/frame_gdn/api.py | 51 | __all__ = ["_build_transition_matrices"] | CODE |
| LOW | diffusion/longsana/pipeline/__init__.py | 5 | __all__ = [ | CODE |
| LOW | diffusion/longsana/model/__init__.py | 5 | __all__ = ["DMDSana", "ODERegressionSana", "StreamingSANATrainingModel"] | CODE |
| LOW⚡ | inference_video_scripts/wm/inference_sana_wm.py | 202 | def set_value(owner: object, key: object, old_value: object, new_value: object, kind: str) -> None: | CODE |
| LOW | train_scripts/sol_rl/train_flux1.py | 85 | logger = logging.getLogger(__name__) | CODE |
| LOW | train_scripts/sol_rl/train_sana.py | 84 | logger = logging.getLogger(__name__) | CODE |
| 1 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 53 | # Step 1: Generate latent using Sana Video Pipeline | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 93 | # Step 2: Load LTX2 Pipeline | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 168 | # Step 3: Manually pack video latent (skip diffusers' normalize, consistent with original code) | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 180 | # Step 4: Create audio latent (becomes zero after normalize, consistent with original code) | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 202 | # Step 5: LTX2 Stage-2 Refinement | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 233 | # Step 6: Save output | COMMENT |
| LOW⚡ | diffusion/longsana/model/ode_regression_sana.py | 105 | # Step 1: Initialize all models | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 126 | # Step 2: Initialize all hyperparameters | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 327 | # Step 1: Run generator on noisy latents | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 342 | # Step 2: Compute the regression loss | COMMENT |
| LOW | diffusion/longsana/model/dmd_sana.py | 575 | # Step 1: Sample noise and backward simulate the generator's input | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/self_forcing_trainer.py | 68 | # Step 2: Initialize the model | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/self_forcing_trainer.py | 71 | # Step 2: Initialize the model and optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 30 | # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 143 | # Step 4: Initialize the optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 157 | # Step 5: Initialize the dataloader | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 172 | # Step 6: Initialize the validation dataloader for visualization (fixed prompts) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 446 | # Step 1: Get the next batch of text prompts | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 462 | # Step 2: Extract the conditional infos for sana | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 489 | # Step 3: Store gradients for the generator (if training the generator) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 510 | # Step 4: Store gradients for the critic (if training the critic) | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 92 | # Step 4: Initialize the optimizer | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 100 | # Step 5: Initialize the dataloader | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 466 | # Step 1: Get the next batch of text prompts | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 471 | # Step 2: Extract the conditional infos | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 475 | # Step 3: Train the generator | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 32 | # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.) | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 69 | # Step 2: Initialize the model and optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 111 | # Step 6: Initialize the validation dataloader for visualization (fixed prompts) | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 512 | # Step 4: Visualization | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 565 | # Step 5: Logging | COMMENT |
| LOW | inference_video_scripts/wm/inference_sana_wm.py | 116 | # NOTE: The default HF checkpoint is bidirectional and is incompatible with | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 53 | # Step 1: Generate latent using Sana Video Pipeline | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 93 | # Step 2: Load LTX2 Pipeline | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 168 | # Step 3: Manually pack video latent (skip diffusers' normalize, consistent with original code) | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 180 | # Step 4: Create audio latent (becomes zero after normalize, consistent with original code) | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 202 | # Step 5: LTX2 Stage-2 Refinement | COMMENT |
| LOW | app/sana_video_refiner_pipeline_diffusers.py | 233 | # Step 6: Save output | COMMENT |
| LOW⚡ | diffusion/longsana/model/ode_regression_sana.py | 105 | # Step 1: Initialize all models | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 126 | # Step 2: Initialize all hyperparameters | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 327 | # Step 1: Run generator on noisy latents | COMMENT |
| LOW | diffusion/longsana/model/ode_regression_sana.py | 342 | # Step 2: Compute the regression loss | COMMENT |
| LOW | diffusion/longsana/model/dmd_sana.py | 575 | # Step 1: Sample noise and backward simulate the generator's input | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/self_forcing_trainer.py | 68 | # Step 2: Initialize the model | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/self_forcing_trainer.py | 71 | # Step 2: Initialize the model and optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 30 | # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 143 | # Step 4: Initialize the optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 157 | # Step 5: Initialize the dataloader | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 172 | # Step 6: Initialize the validation dataloader for visualization (fixed prompts) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 446 | # Step 1: Get the next batch of text prompts | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 462 | # Step 2: Extract the conditional infos for sana | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 489 | # Step 3: Store gradients for the generator (if training the generator) | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 510 | # Step 4: Store gradients for the critic (if training the critic) | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 92 | # Step 4: Initialize the optimizer | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 100 | # Step 5: Initialize the dataloader | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 466 | # Step 1: Get the next batch of text prompts | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 471 | # Step 2: Extract the conditional infos | COMMENT |
| LOW⚡ | diffusion/longsana/trainer/ode.py | 475 | # Step 3: Train the generator | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 32 | # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.) | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 69 | # Step 2: Initialize the model and optimizer | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 111 | # Step 6: Initialize the validation dataloader for visualization (fixed prompts) | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 512 | # Step 4: Visualization | COMMENT |
| LOW | diffusion/longsana/trainer/ode.py | 565 | # Step 5: Logging | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | diffusion/utils/chunk_utils.py | 76 | Convert chunk_size to chunk_index list with a split strategy. Args: T: Number of latent frames. chu | STRING |
| HIGH | diffusion/utils/chunk_utils.py | 135 | Resolve chunk_index from a config, supporting chunk_size and strategy. Priority: 1) config.model.chunk_index | STRING |
| HIGH | diffusion/utils/chunk_utils.py | 214 | Return frame-time positions belonging to size-1 (singleton) chunks. A size-1 chunk has no intra-chunk lookahead, so | STRING |
| HIGH | diffusion/utils/chunk_utils.py | 384 | Normalize chunk_index and detect if uniform. This function handles all the complex logic for: 1. Converting chu | STRING |
| HIGH | diffusion/model/model_growth_utils.py | 70 | Args: strategy: init strategy name **kwargs: strategy specific parameters Ret | STRING |
| HIGH | diffusion/model/ops/fused_cam_gdn.py | 1391 | Fused numerator-only single-path delta-rule scan for the cam branch. Args: q, k, v: ``(B, H, D, N)`` fp32 c | STRING |
| HIGH | diffusion/model/ops/fused_gdn_cp.py | 1022 | End-to-end differentiable CP fused GDN raw entry (num, den). Composes :class:`_CpFusedGdnPrep` -> :func:`cp_frame_g | STRING |
| HIGH | diffusion/model/ops/fused_gdn.py | 645 | One direction of fused BiGDN via the unified kernel. Args: qkv .. eps: see kernel signature. reverse: f | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | environment_setup.sh | 16 | # Check if we should skip environment setup entirely (used by CI). | COMMENT |
| LOW | tools/metrics/sana_wm/eval_unified.py | 901 | # Check if results already exist | COMMENT |
| LOW | app/app_sana_inpaint.py | 449 | # Check if this is a new image by comparing with stored original | COMMENT |
| LOW | diffusion/utils/chunk_utils.py | 342 | # Check if tail (sizes[1:]) is uniform | COMMENT |
| LOW | diffusion/utils/chunk_utils.py | 359 | # Check if tail (sizes[1:]) is uniform | COMMENT |
| LOW | diffusion/utils/chunk_utils.py | 418 | # Check if uniform (requires chunk_size for comparison) | COMMENT |
| LOW | diffusion/utils/chunk_utils.py | 446 | # Check if uniform | COMMENT |
| LOW | diffusion/utils/data_sampler.py | 262 | # Assign samples to each bucket | COMMENT |
| LOW | diffusion/model/utils.py | 136 | # Check if resizing is needed | COMMENT |
| LOW | diffusion/longsana/utils/dataset.py | 294 | # Check if all samples list length is consistent | COMMENT |
| LOW | diffusion/longsana/model/streaming_sana_long.py | 376 | # Check if previous_frames can be used for overlap and auto-compute overlap frame count | COMMENT |
| LOW | diffusion/longsana/trainer/self_forcing_trainer.py | 613 | # Check if we've reached max iterations | COMMENT |
| LOW | diffusion/longsana/trainer/longsana_trainer.py | 282 | # Check if we should train generator on this optimization step | COMMENT |
| LOW | diffusion/data/wids/wids.py | 644 | # Check if we're missing the cache too often. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/metrics/clip-score/clip_score.py | 50 | self.fake_data = self._load_txt_from_path(fake_path) | CODE |
| LOW | tools/metrics/clip-score/clip_score.py | 63 | fake_data = self._load_txt(self.fake_data[index]) | CODE |
| LOW | tools/metrics/clip-score/clip_score.py | 64 | sample = dict(real=real_data, fake=fake_data, prompt=self.fake_data[index]) | CODE |
| LOW | tools/metrics/clip-score/src/clip_score/clip_score.py | 93 | fake_data = self._load_modality(fake_path, self.fake_flag) | CODE |
| LOW | tools/metrics/clip-score/src/clip_score/clip_score.py | 95 | sample = dict(real=real_data, fake=fake_data) | CODE |
| LOW | tools/metrics/clip-score/src/clip_score/clip_score.py | 124 | fake_name = self.fake_folder[idx].split(".") | CODE |
| LOW | tools/metrics/clip-score/src/clip_score/clip_score.py | 125 | if fake_name != real_name: | CODE |
| LOW | diffusion/longsana/model/streaming_sana_long.py | 670 | if self.base_model.fake_name == "SANA": | CODE |
| LOW⚡ | diffusion/longsana/model/dmd_sana.py | 256 | fake_name = getattr(args, "fake_name", "SANA") | CODE |
| LOW⚡ | diffusion/longsana/model/dmd_sana.py | 257 | self.fake_name = fake_name | CODE |
| LOW⚡ | diffusion/longsana/model/dmd_sana.py | 258 | if fake_name == "SANA": | CODE |
| LOW | diffusion/longsana/model/dmd_sana.py | 314 | if self.fake_name == "SANA": | CODE |
| LOW | diffusion/longsana/model/dmd_sana.py | 416 | if self.fake_name == "SANA": | CODE |
| LOW | diffusion/longsana/model/dmd_sana.py | 762 | if self.fake_name == "SANA": | CODE |
| LOW | …igs/sana_video_config/longsana/480ms/self_forcing.yaml | 12 | fake_name: SANA | CODE |
| LOW | configs/sana_video_config/longsana/480ms/longsana.yaml | 14 | fake_name: SANA | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | asset/docs/sana_lora_dreambooth.md | 111 | - `report_to="wandb` will ensure the training runs are tracked on [Weights and Biases](https://wandb.ai/site). To use it | CODE |
| HIGH | docs/sana_lora_dreambooth.md | 111 | - `report_to="wandb` will ensure the training runs are tracked on [Weights and Biases](https://wandb.ai/site). To use it | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | environment_setup.sh | 8 | # Usage: | COMMENT |
| LOW | app/app_sana_inpaint.py | 315 | ### How to use: | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | diffusion/scheduler/self_forcing_flow_euler_sampler.py | 510 | # scaffolding. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | diffusion/longsana/model/dmd_sana.py | 217 | # TODO: Need to make the path more robust. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py | 13 | def process_data(input_dir, output_tar_name="output.tar"): | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | train_scripts/train_dreambooth_lora_sana.py | 1016 | # make sure to pop weight so that corresponding model is not saved again | STRING |