Repository Analysis

NVlabs/Sana

SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

18.9 Moderate AI signal View on GitHub

Analysis Overview

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).

18.9
Adjusted Score
18.9
Raw Score
100%
Time Factor
2026-07-14
Last Push
8.5K
Stars
Python
Language
148.3K
Lines of Code
478
Files
1.8K
Pattern Hits
2026-07-14
Scan Date
0.10
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

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.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 46MEDIUM 376LOW 1422

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 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.

Decorative Section Separators331 hits · 1050 pts
SeverityFileLineSnippetContext
MEDIUMenvironment_setup.sh2# -----------------------------------------------------------------------------COMMENT
MEDIUMenvironment_setup.sh13# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py615# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py617# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py875# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py877# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py936# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py938# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py106# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py108# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py220# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py222# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py1046# ============================================================================COMMENT
MEDIUMtools/metrics/sana_wm/eval_unified.py1048# ============================================================================COMMENT
MEDIUMdiffusion/post_training/rewards.py15# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py17# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py81# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py83# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py107# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py109# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/post_training/rewards.py185# =========================================================================COMMENT
MEDIUMdiffusion/post_training/rewards.py187# =========================================================================COMMENT
MEDIUMdiffusion/post_training/rewards.py319# =========================================================================COMMENT
MEDIUMdiffusion/post_training/rewards.py321# =========================================================================COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py32# ---------------------------------------------------------------------------COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py34# ---------------------------------------------------------------------------COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py197# ---------------------------------------------------------------------------COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py199# ---------------------------------------------------------------------------COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py346# ---------------------------------------------------------------------------COMMENT
MEDIUM…post_training/diffusers_patch/pipeline_with_logprob.py348# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py58# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py60# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py144# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py146# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py184# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py186# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py234# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py236# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py464# ---------------------------------------------------------------------------COMMENT
MEDIUM…usion/distributed/context_parallel/distributed_scan.py466# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py663 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py665 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py69# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py71# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py118# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py120# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py151# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py153# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py270# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py272# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py313 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py315 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py346 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py348 # ------------------------------------------------------------------COMMENT
MEDIUMdiffusion/utils/action_overlay.py43# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/utils/action_overlay.py45# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/utils/action_overlay.py121# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/utils/action_overlay.py123# ---------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/model/edm_sample.py28# ----------------------------------------------------------------------------COMMENT
MEDIUMdiffusion/model/edm_sample.py83# ----------------------------------------------------------------------------COMMENT
271 more matches not shown…
Unused Imports347 hits · 326 pts
SeverityFileLineSnippetContext
LOWtools/convert_sana_wm_refiner_to_diffusers.py42CODE
LOWtools/metrics/sana_wm/eval_unified.py51CODE
LOWtools/metrics/sana_wm/pose_utils.py3CODE
LOWtools/metrics/sana_wm/aggregate_results.py20CODE
LOWtools/metrics/geneval/generation/diffusers_generate.py15CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/inception.py7CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/inception.py9CODE
LOWtools/controlnet/inference_controlnet.py37CODE
LOWtools/controlnet/inference_controlnet.py37CODE
LOWtools/convert_scripts/convert_sana_to_svdquant.py2CODE
LOWtools/convert_scripts/convert_sana_to_diffusers.py2CODE
LOW…ols/convert_scripts/convert_sana_video_to_diffusers.py2CODE
LOWtrain_video_scripts/train_video_ivjoint_chunk.py36CODE
LOWtrain_video_scripts/train_video_ivjoint.py31CODE
LOWtrain_video_scripts/train_video_ivjoint.py35CODE
LOWtrain_video_scripts/train_video_ivjoint.py38CODE
LOWtrain_video_scripts/train_video_ivjoint.py47CODE
LOWapp/app_sana_multithread.py17CODE
LOWapp/sana_pipeline.py28CODE
LOWapp/sana_pipeline.py28CODE
LOWapp/sana_pipeline.py28CODE
LOWapp/sana_pipeline.py28CODE
LOWapp/sana_controlnet_pipeline.py31CODE
LOWapp/sana_controlnet_pipeline.py31CODE
LOWapp/sana_controlnet_pipeline.py31CODE
LOWapp/sana_controlnet_pipeline.py31CODE
LOWapp/sana_pipeline_inpaint.py20CODE
LOWapp/sana_pipeline_inpaint.py31CODE
LOWapp/sana_pipeline_inpaint.py31CODE
LOWapp/sana_pipeline_inpaint.py31CODE
LOWapp/sana_pipeline_inpaint.py31CODE
LOWapp/sana_pipeline_inpaint.py41CODE
LOWapp/safety_check.py19CODE
LOWapp/safety_check.py21CODE
LOWapp/safety_check.py21CODE
LOWapp/app_sana_4bit.py21CODE
LOWapp/app_sana.py17CODE
LOWapp/app_sana.py32CODE
LOWapp/sana_sprint_pipeline.py32CODE
LOWapp/sana_sprint_pipeline.py32CODE
LOWapp/app_sana_inpaint.py8CODE
LOWapp/app_sana_sprint.py17CODE
LOWsana/tools/__init__.py1CODE
LOWsana/tools/__init__.py2CODE
LOWsana/tools/__init__.py2CODE
LOWdiffusion/__init__.py3CODE
LOWdiffusion/__init__.py4CODE
LOWdiffusion/__init__.py4CODE
LOWdiffusion/__init__.py4CODE
LOWdiffusion/__init__.py5CODE
LOWdiffusion/__init__.py6CODE
LOWdiffusion/__init__.py7CODE
LOWdiffusion/__init__.py8CODE
LOWdiffusion/__init__.py9CODE
LOWdiffusion/post_training/rewards.py5CODE
LOWdiffusion/post_training/dataset/pickscore/prpocess.py3CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py31CODE
LOW…usion/distributed/context_parallel/distributed_scan.py23CODE
LOWdiffusion/distributed/context_parallel/config.py7CODE
LOWdiffusion/distributed/context_parallel/halo_exchange.py16CODE
287 more matches not shown…
Hyper-Verbose Identifiers290 hits · 286 pts
SeverityFileLineSnippetContext
LOWtools/convert_sana_wm_refiner_to_diffusers.py135def fuse_distilled_lora_inplace(CODE
LOWtools/convert_sana_wm_refiner_to_diffusers.py191def convert_connectors_to_diffusers(checkpoint: dict[str, object]) -> dict[str, object]:CODE
LOWtools/metrics/sana_wm/eval_unified.py620def _build_stripped_video_dir(video_dir: str, output_dir: str) -> str:CODE
LOWtools/metrics/sana_wm/eval_unified.py941def eval_temporal_degradation(CODE
LOWtools/metrics/sana_wm/eval_unified.py94def _resolve_vbench_info_path(vbench_module) -> str:CODE
LOWtools/metrics/sana_wm/eval_unified.py325def _vbench_torch_load_compat():CODE
LOWtools/metrics/sana_wm/aggregate_results.py111def _compute_vbench_total_local(scores: dict[str, float]) -> dict[str, float]:CODE
LOWtools/metrics/sana_wm/aggregate_results.py133def _recompute_vbench_from_raw(eval_dir: str) -> dict[str, float]:CODE
LOWtools/metrics/sana_wm/eval_benchmark_poses.py50def _dataset_root_from_manifest(manifest_path: str) -> str:CODE
LOWtools/metrics/sana_wm/eval_benchmark_poses.py154def _resolve_skip_first_frame(arg_val: str, result_folder: str) -> bool:CODE
LOWtools/metrics/geneval/prompts/create_prompts.py38def generate_single_object_sample(rng: np.random.Generator, size: int = None):CODE
LOWtools/metrics/geneval/prompts/create_prompts.py62def generate_two_object_sample(rng: np.random.Generator):CODE
LOWtools/metrics/geneval/prompts/create_prompts.py128def generate_color_attribution_sample(rng: np.random.Generator):CODE
LOWtools/metrics/clip-score/clip_score.py231def calculate_clip_score_official(dataloader):CODE
LOWtools/metrics/pytorch-fid/compute_fid.py90def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6):CODE
LOWtools/metrics/pytorch-fid/compute_fid.py123def calculate_activation_statistics(files, model, batch_size=50, dims=2048, device="cpu", num_workers=1):CODE
LOWtools/metrics/pytorch-fid/compute_fid.py130def compute_statistics_of_path(path, model, batch_size, dims, device, num_workers=1, flag="ref"):CODE
LOWtools/metrics/pytorch-fid/compute_fid.py168def calculate_fid_given_paths(paths, batch_size, device, dims, num_workers=1):CODE
LOWtools/metrics/pytorch-fid/tests/test_fid_score.py13def test_calculate_fid_given_statistics(mocker, tmp_path, device):CODE
LOWtools/metrics/pytorch-fid/tests/test_fid_score.py41def test_compute_statistics_of_path(mocker, tmp_path, device):CODE
LOWtools/metrics/pytorch-fid/tests/test_fid_score.py62def test_compute_statistics_of_path_from_file(mocker, tmp_path, device):CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py153def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6):CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py206def calculate_activation_statistics(files, model, batch_size=50, dims=2048, device="cpu", num_workers=1):CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py230def compute_statistics_of_path(path, model, batch_size, dims, device, num_workers=1):CODE
LOWtools/metrics/pytorch-fid/src/pytorch_fid/fid_score.py242def calculate_fid_given_paths(paths, batch_size, device, dims, num_workers=1):CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py76def _resolve_cp_runtime_config(config: SanaVideoCamCtrlConfig) -> object:CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py141def _build_parallelism_config(config: SanaVideoCamCtrlConfig, cp_size: int):CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py179def _resolve_data_dirs_under_root(data_dir, root: str):CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py219def _remove_custom_module_call(model, logger) -> None:CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py271def _right_pad_temporal_with_last_frame(tensor: torch.Tensor, dim: int, pad_size: int) -> torch.Tensor:CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py282def _map_global_chunk_index_to_local(CODE
LOWapp/sana_pipeline.py52def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]:CODE
LOWapp/sana_controlnet_pipeline.py54def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]:CODE
LOWapp/sana_pipeline_inpaint.py56def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]:CODE
LOWapp/sana_sprint_pipeline.py40def classify_height_width_bin(height: int, width: int, ratios: dict) -> Tuple[int, int]:CODE
LOWtests/bash/training/test_training_sana_wm_distill.sh128def configure_self_forcing_data(cfg):CODE
LOWdiffusion/post_training/rewards.py97def _get_clip_image_transform(processor):CODE
LOWdiffusion/post_training/rewards.py114def _patch_imagereward_compat():CODE
LOWdiffusion/post_training/rewards.py124 def _apply_chunking_to_forward(forward_fn, chunk_size, chunk_dim, *input_tensors):CODE
LOWdiffusion/post_training/rewards.py136 def _find_pruneable_heads_and_indices(heads, n_heads, head_size, already_pruned_heads):CODE
LOW…post_training/diffusers_patch/pipeline_with_logprob.py203def pipeline_with_logprob_flux(CODE
LOW…post_training/diffusers_patch/pipeline_with_logprob.py352def pipeline_with_logprob_sana(CODE
LOWdiffusion/post_training/diffusers_patch/solver.py299def dpm_solver_first_order_update(CODE
LOWdiffusion/post_training/diffusers_patch/solver.py318def multistep_dpm_solver_second_order_update(CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1732def _clear_cross_attention_kv_cache(transformer: nn.Module) -> None:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1738def _has_cross_attention_kv_cache(transformer: nn.Module) -> bool:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1745def _cross_attention_with_cached_kv(CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2294def _prepared_module_cache_root() -> Path | None:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2301def _prepared_module_cache_hash(payload: dict[str, object]) -> str:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2329def _is_local_callable_for_pickle(value: object) -> bool:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2338def _strip_local_callables_for_pickle(root: object) -> list[tuple[object, object, object, str]]:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py77 def _load_diffusers_components(self) -> tuple[nn.Module, nn.Module]:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py142 def _prepared_transformer_cache_path(self) -> Path | None:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py165 def _save_prepared_transformer_cache(self) -> None:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py242 def offload_video_unused_audio_modules(self, device: torch.device | str = "cpu") -> None:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py259 def _attention_backend_context(self):CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py266 def _uniform_timestep_tensors(CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py729 def _forward_video_only_with_rope(CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1315def _build_rotary_emb_for_absolute_positions(CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1461def _streaming_self_attention(CODE
230 more matches not shown…
Deep Nesting201 hits · 182 pts
SeverityFileLineSnippetContext
LOWtools/create_wids_metadata.py32CODE
LOWtools/convert_sana_wm_refiner_to_diffusers.py135CODE
LOWtools/metrics/utils.py4CODE
LOWtools/metrics/sana_wm/eval_unified.py378CODE
LOWtools/metrics/sana_wm/eval_unified.py673CODE
LOWtools/metrics/sana_wm/eval_unified.py1053CODE
LOWtools/metrics/sana_wm/pose_utils.py128CODE
LOWtools/metrics/sana_wm/eval_benchmark_poses.py177CODE
LOWtools/metrics/geneval/evaluation/evaluate_images.py151CODE
LOWtools/metrics/geneval/generation/diffusers_generate.py84CODE
LOWtools/metrics/clip-score/clip_score.py85CODE
LOWtools/metrics/clip-score/clip_score.py106CODE
LOWtools/metrics/dpg_bench/compute_dpg_bench.py132CODE
LOWtools/metrics/pytorch-fid/compute_fid.py130CODE
LOWtools/convert_scripts/convert_sana_to_svdquant.py47CODE
LOWtools/convert_scripts/convert_sana_to_diffusers.py47CODE
LOW…ols/convert_scripts/convert_sana_video_to_diffusers.py33CODE
LOW…t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py13CODE
LOWtrain_video_scripts/train_longsana.py30CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py456CODE
LOWtrain_video_scripts/train_sana_wm_stage1.py520CODE
LOWtrain_video_scripts/train_video_ivjoint_chunk.py105CODE
LOWtrain_video_scripts/train_video_ivjoint_chunk.py278CODE
LOWtrain_video_scripts/train_video_ivjoint_chunk.py854CODE
LOWtrain_video_scripts/train_video_ivjoint_chunk.py119CODE
LOWtrain_video_scripts/train_video_ivjoint.py240CODE
LOWtrain_video_scripts/train_video_ivjoint.py739CODE
LOWapp/sana_pipeline.py167CODE
LOWapp/sana_controlnet_pipeline.py190CODE
LOWapp/sana_pipeline_inpaint.py324CODE
LOWapp/app_sana_inpaint.py44CODE
LOWapp/app_sana_inpaint.py278CODE
LOWsana/cli/upload2hf.py50CODE
LOWdiffusion/post_training/ema.py27CODE
LOWdiffusion/post_training/diffusers_patch/solver.py15CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1461CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1745CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2005CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2485CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1044CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2439CODE
LOW…usion/distributed/context_parallel/distributed_scan.py192CODE
LOWdiffusion/guiders/adaptive_projected_guidance.py106CODE
LOWdiffusion/scheduler/lcm_scheduler.py175CODE
LOWdiffusion/scheduler/sana_streaming_sampler.py116CODE
LOWdiffusion/scheduler/longlive_flow_euler_sampler.py420CODE
LOWdiffusion/scheduler/self_forcing_flow_euler_sampler.py74CODE
LOWdiffusion/scheduler/self_forcing_flow_euler_sampler.py675CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py138CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py334CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py414CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py438CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py482CODE
LOWdiffusion/utils/misc.py317CODE
LOWdiffusion/utils/checkpoint.py138CODE
LOWdiffusion/utils/logger.py197CODE
LOWdiffusion/utils/optimizer.py52CODE
LOWdiffusion/utils/optimizer.py325CODE
LOWdiffusion/utils/optimizer.py501CODE
LOWdiffusion/utils/optimizer.py623CODE
141 more matches not shown…
Cross-File Repetition36 hits · 180 pts
SeverityFileLineSnippetContext
HIGHapp/app_sana_controlnet_hed.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHapp/app_sana_multithread.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHapp/app_sana.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHapp/app_sana_inpaint.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHscripts/interface.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHapp/app_sana_4bit.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHapp/app_sana_sprint.py0<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> <img src="https://nvlabs.STRING
HIGHdiffusion/scheduler/scm_scheduler.py0output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, nSTRING
HIGHdiffusion/scheduler/lcm_scheduler.py0output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, nSTRING
HIGHdiffusion/scheduler/trigflow_scheduler.py0output class for the scheduler's `step` function output. args: prev_sample (`torch.floattensor` of shape `(batch_size, nSTRING
HIGHdiffusion/scheduler/scm_scheduler.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGHdiffusion/scheduler/lcm_scheduler.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGHdiffusion/scheduler/trigflow_scheduler.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGHdiffusion/model/nets/sana_multi_scale_controlnet.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale_adaln.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale_video.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale_video_v2v.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale_video_camctrl.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_U_shape.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_U_shape_multi_scale.py0forward pass of sanaums. x: (n, c, h, w) tensor of spatial inputs (images or latent representations of images) t: (n,) tSTRING
HIGHdiffusion/model/nets/sana_multi_scale_controlnet.py0this method allows the object to be called like a function. it simply calls the forward method.STRING
HIGHdiffusion/model/nets/sana_multi_scale_video.py0this method allows the object to be called like a function. it simply calls the forward method.STRING
HIGHdiffusion/model/nets/sana_multi_scale.py0this method allows the object to be called like a function. it simply calls the forward method.STRING
HIGHdiffusion/model/nets/sana.py0this method allows the object to be called like a function. it simply calls the forward method.STRING
HIGHdiffusion/model/nets/sana_multi_scale_video.py0a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning.STRING
HIGHdiffusion/model/nets/sana_multi_scale_video_camctrl.py0a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning.STRING
HIGHdiffusion/model/nets/sana_multi_scale.py0a sana block with global shared adaptive layer norm zero (adaln-zero) conditioning.STRING
HIGH…inear/modules/triton_lite_mla_kernels/pad_vk_mm_fwd.py0kernel 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.py0kernel 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.py0kernel 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.py0kernel 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
HIGHscripts/inference_geneval.py0\ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, authorSTRING
HIGHscripts/inference_geneval_diffusers.py0\ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, authorSTRING
HIGHscripts/inference_sana_sprint_geneval.py0\ @article{ghosh2024geneval, title={geneval: an object-focused framework for evaluating text-to-image alignment}, authorSTRING
Over-Commented Block184 hits · 177 pts
SeverityFileLineSnippetContext
LOWenvironment_setup.sh1#!/usr/bin/env bashCOMMENT
LOWtools/create_wids_metadata.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWtools/download.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWtools/convert_sana_wm_refiner_to_diffusers.py1#!/usr/bin/env python3COMMENT
LOWtools/controlnet/inference_controlnet.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWtrain_video_scripts/train_video_ivjoint_chunk.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWtrain_video_scripts/train_video_ivjoint.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/app_sana_multithread.py1#!/usr/bin/env pythonCOMMENT
LOWapp/sana_pipeline.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/sana_controlnet_pipeline.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/sana_pipeline_inpaint.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/safety_check.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/app_sana_4bit.py1#!/usr/bin/env pythonCOMMENT
LOWapp/app_sana.py1#!/usr/bin/env pythonCOMMENT
LOWapp/sana_sprint_pipeline.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWapp/app_sana_sprint.py1#!/usr/bin/env pythonCOMMENT
LOWasset/examples.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWasset/docs/quantize/8bit_sana.md1<!-- Copyright 2024 The HuggingFace Team. All rights reserved.COMMENT
LOWasset/docs/quantize/4bit_sana.md1<!--Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWsana/tools/hf_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWsana/cli/run.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWsana/cli/upload2hf.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATES (authored by @Lyken17)COMMENT
LOWdiffusion/post_training/diffusers_patch/text_encode.py1#!/usr/bin/env pythonCOMMENT
LOWdiffusion/refiner/diffusers_ltx2_refiner.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/guiders/adaptive_projected_guidance.py1# Copyright 2025 The HuggingFace Team. All rights reserved.COMMENT
LOWdiffusion/scheduler/dpm_solver.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/scm_scheduler.py1# Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved.COMMENT
LOWdiffusion/scheduler/flow_euler_sampler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/iddpm.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/sa_sampler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/lcm_scheduler.py1# Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved.COMMENT
LOWdiffusion/scheduler/sana_streaming_sampler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/trigflow_scheduler.py1# Copyright 2023 Stanford University Team and The HuggingFace Team. All rights reserved.COMMENT
LOWdiffusion/scheduler/self_forcing_flow_euler_sampler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/scheduler/self_forcing_flow_euler_sampler.py121#COMMENT
LOWdiffusion/scheduler/self_forcing_flow_euler_sampler.py501 # over [sink + window + current], cached tokens already have theCOMMENT
LOWdiffusion/scheduler/sa_solver_diffusers.py1# Licensed under the Apache License, Version 2.0 (the "License");COMMENT
LOWdiffusion/utils/lr_scheduler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/camctrl_config.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/misc.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/config.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/checkpoint.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/chunk_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/logger.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/action_overlay.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/optimizer.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/cam_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/utils/dist_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/model_growth_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/respace.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/dpm_solver.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/registry.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/timestep_sampler.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/diffusion_utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/edm_sample.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/builder.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/act.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/utils.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/liger_norms.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
LOWdiffusion/model/gaussian_diffusion.py1# Copyright 2024 NVIDIA CORPORATION & AFFILIATESCOMMENT
124 more matches not shown…
AI Structural Patterns141 hits · 136 pts
SeverityFileLineSnippetContext
LOWapp/app_sana_multithread.py234CODE
LOWapp/app_sana_multithread.py283CODE
LOWapp/sana_pipeline.py167CODE
LOWapp/sana_controlnet_pipeline.py190CODE
LOWapp/sana_pipeline_inpaint.py324CODE
LOWapp/sana_video_refiner_pipeline_diffusers.py24CODE
LOWapp/app_sana_4bit.py175CODE
LOWapp/app_sana.py239CODE
LOWapp/sana_sprint_pipeline.py150CODE
LOWapp/app_sana_sprint.py217CODE
LOW…post_training/diffusers_patch/pipeline_with_logprob.py38CODE
LOW…post_training/diffusers_patch/pipeline_with_logprob.py203CODE
LOW…post_training/diffusers_patch/pipeline_with_logprob.py352CODE
LOWdiffusion/distributed/context_parallel/halo_exchange.py127CODE
LOWdiffusion/guiders/adaptive_projected_guidance.py49CODE
LOWdiffusion/scheduler/dpm_solver.py23CODE
LOWdiffusion/scheduler/iddpm.py26CODE
LOWdiffusion/scheduler/sa_sampler.py49CODE
LOWdiffusion/scheduler/lcm_scheduler.py175CODE
LOWdiffusion/scheduler/trigflow_scheduler.py100CODE
LOWdiffusion/scheduler/longlive_flow_euler_sampler.py93CODE
LOWdiffusion/scheduler/sa_solver_diffusers.py138CODE
LOWdiffusion/utils/checkpoint.py30CODE
LOWdiffusion/utils/checkpoint.py76CODE
LOWdiffusion/utils/checkpoint.py138CODE
LOWdiffusion/utils/checkpoint.py230CODE
LOWdiffusion/utils/checkpoint.py264CODE
LOWdiffusion/utils/dist_utils.py293CODE
LOWdiffusion/model/dpm_solver.py266CODE
LOWdiffusion/model/dpm_solver.py1504CODE
LOWdiffusion/model/dpm_solver.py1545CODE
LOWdiffusion/model/dpm_solver.py1789CODE
LOWdiffusion/model/edm_sample.py32CODE
LOWdiffusion/model/edm_sample.py88CODE
LOWdiffusion/model/gaussian_diffusion.py633CODE
LOWdiffusion/model/gaussian_diffusion.py666CODE
LOWdiffusion/model/sa_solver.py211CODE
LOWdiffusion/model/sa_solver.py892CODE
LOWdiffusion/model/sa_solver.py1092CODE
LOWdiffusion/model/sa_solver.py1291CODE
LOWdiffusion/model/wan2_2/vae.py688CODE
LOWdiffusion/model/ltx2/causal_vae.py471CODE
LOWdiffusion/model/ltx2/causal_vae.py831CODE
LOWdiffusion/model/ltx2/causal_vae.py1022CODE
LOWdiffusion/model/ltx2/causal_vae.py1151CODE
LOWdiffusion/model/ltx2/causal_vae.py1303CODE
LOWdiffusion/model/ltx2/causal_vae.py1499CODE
LOWdiffusion/model/nets/sana_multi_scale_controlnet.py87CODE
LOWdiffusion/model/nets/sana_multi_scale_video.py71CODE
LOWdiffusion/model/nets/sana_multi_scale_video.py345CODE
LOWdiffusion/model/nets/sana_blocks.py263CODE
LOWdiffusion/model/nets/sana_blocks.py291CODE
LOWdiffusion/model/nets/sana_blocks.py388CODE
LOWdiffusion/model/nets/sana_blocks.py495CODE
LOWdiffusion/model/nets/sana_blocks.py624CODE
LOWdiffusion/model/nets/sana_blocks.py675CODE
LOWdiffusion/model/nets/sana_blocks.py717CODE
LOWdiffusion/model/nets/sana_blocks.py765CODE
LOWdiffusion/model/nets/sana_blocks.py1194CODE
LOWdiffusion/model/nets/sana_blocks.py1238CODE
81 more matches not shown…
Excessive Try-Catch Wrapping116 hits · 127 pts
SeverityFileLineSnippetContext
LOWtools/metrics/sana_wm/eval_unified.py865 except Exception as e:CODE
LOWtools/metrics/sana_wm/eval_unified.py296 except Exception:CODE
LOWtools/metrics/sana_wm/eval_unified.py306 except Exception:CODE
LOWtools/metrics/sana_wm/eval_unified.py464 except Exception:CODE
LOWtools/metrics/sana_wm/eval_unified.py516 except Exception:CODE
LOWtools/metrics/sana_wm/eval_unified.py666 except Exception as e:CODE
LOWtools/metrics/sana_wm/pose_utils.py140 except Exception as exc:CODE
MEDIUMtools/metrics/sana_wm/pose_utils.py141 print(f"Error loading {video_path}: {exc}")CODE
LOWtools/metrics/sana_wm/pose_utils.py165 except Exception as exc:CODE
LOWtools/metrics/sana_wm/pose_utils.py180 except Exception as exc:CODE
MEDIUMtools/metrics/sana_wm/pose_utils.py181 print(f"Error inferencing {video_paths[valid_index]}: {exc}")CODE
MEDIUMtools/metrics/sana_wm/eval_benchmark_poses.py211 print("Error: Pi3 not found. Install Pi3 or place it on PYTHONPATH.")CODE
LOWtools/metrics/sana_wm/eval_benchmark_poses.py334 except Exception as e:CODE
MEDIUMtools/metrics/sana_wm/eval_benchmark_poses.py335 print(f"Error evaluating {scene_id}: {e}")CODE
LOWtools/metrics/clip-score/clip_score.py199 except Exception as e:CODE
MEDIUMtools/metrics/clip-score/clip_score.py179def process_sample(sample):CODE
LOWtools/metrics/dpg_bench/compute_dpg_bench.py246 except Exception as e:CODE
LOWtools/metrics/pytorch-fid/compute_fid.py42 except Exception as e:CODE
LOW…t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py52 except Exception as e:CODE
MEDIUM…t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py53 print(f"Error processing file {filename}: {e}")CODE
LOWtrain_video_scripts/train_video_ivjoint.py370 except Exception as e:CODE
MEDIUMtrain_video_scripts/train_video_ivjoint.py371 print(f"Error in vae_encode: {e}")CODE
LOWtrain_video_scripts/train_video_ivjoint.py483 except Exception:CODE
LOWapp/app_sana_inpaint.py253 except Exception as e:CODE
LOWapp/app_sana_inpaint.py264 except Exception as e:CODE
LOWapp/app_sana_inpaint.py469 except Exception as e:CODE
LOWsana/tools/hf_utils.py97 except Exception as e:CODE
MEDIUMsana/tools/hf_utils.py98 print(f"Error downloading file: {e}")CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2310 except Exception:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py91 except Exception as exc:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py161 except Exception:CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py187 except Exception as exc:CODE
LOWdiffusion/scheduler/longlive_flow_euler_sampler.py307 except Exception:CODE
LOWdiffusion/scheduler/longlive_flow_euler_sampler.py351 except Exception:CODE
LOWdiffusion/utils/git.py167 except Exception as e:CODE
LOWdiffusion/utils/checkpoint.py170 except Exception as exc:CODE
LOWdiffusion/utils/action_overlay.py138 except Exception:CODE
LOWdiffusion/model/nets/sana_multi_scale_video.py1013 except Exception as e:CODE
MEDIUMdiffusion/model/nets/sana_multi_scale_video.py1014 print(f"Error loading {key}: {e}")CODE
LOWdiffusion/model/nets/sana_multi_scale_video_camctrl.py1527 except Exception as e:CODE
LOWdiffusion/model/nets/sana.py402 except Exception as e:CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/image.py69 except Exception:CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/image.py177 except Exception:CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/dist.py43 except Exception:CODE
LOWdiffusion/model/ops/fused_gdn.py1719 except Exception as e:CODE
LOWdiffusion/model/ops/fused_gdn.py2086 except Exception as e:CODE
LOWdiffusion/model/ops/fused_gdn_chunkwise_cuda.py741 except Exception:CODE
LOWdiffusion/model/ops/fused_gdn_chunkwise_cuda.py827 except Exception as e: # missing toolkit / unexpected shape -> TritonCODE
LOWdiffusion/model/ops/fused_gdn_chunkwise_cuda.py906 except Exception as e: # missing toolkit / unexpected shape -> TritonCODE
LOWdiffusion/model/ops/fused_gdn_chunkwise.py1156 except Exception:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py29 except Exception:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py176 except Exception:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py198 except Exception:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py211 except Exception:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py247 except Exception as e:CODE
LOW…line/sana_inference_interactive_pipeline_long_chunk.py250 except Exception:CODE
LOW…ngsana/pipeline/sana_inference_interactive_pipeline.py32 except Exception:CODE
LOW…ngsana/pipeline/sana_inference_interactive_pipeline.py192 except Exception:CODE
LOW…ngsana/pipeline/sana_inference_interactive_pipeline.py251 except Exception:CODE
LOW…ngsana/pipeline/sana_inference_interactive_pipeline.py265 except Exception:CODE
56 more matches not shown…
Self-Referential Comments28 hits · 84 pts
SeverityFileLineSnippetContext
MEDIUM…t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py57 # Create a TAR file and include all filesCOMMENT
MEDIUMapp/safety_check.py16# This file is copy from https://github.com/mit-han-lab/hart/blob/main/hart/utils/safety_check.pyCOMMENT
MEDIUMdiffusion/post_training/stat_tracking.py93 # Create a mask for the current group.COMMENT
MEDIUMdiffusion/utils/cam_utils.py77 # Create the base (N, 4, 4) tensor (identity matrix padded)COMMENT
MEDIUMdiffusion/model/dpm_solver.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_multi_scale_controlnet.py19# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_multi_scale_video.py18# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_blocks.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_multi_scale_adaln.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_gdn_blocks.py70 """This function is intended to align with the l2norm implementation in the FLA library."""STRING
MEDIUMdiffusion/model/nets/sana_U_shape.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_multi_scale_video_camctrl.py18# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/basic_modules.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_U_shape_multi_scale.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana_multi_scale.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/model/nets/sana.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/data/datasets/sana_data_multi_scale.py18# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/data/datasets/sana_data.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/data/datasets/utils.py17# This file is modified from https://github.com/PixArt-alpha/PixArt-sigmaCOMMENT
MEDIUMdiffusion/data/wids/wids_tar.py17# This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
MEDIUMdiffusion/data/wids/wids_tar.py49 # Create the indexCOMMENT
MEDIUMdiffusion/data/wids/wids_tar.py59 # Create an empty list for the indexCOMMENT
MEDIUMdiffusion/data/wids/wids_mmtar.py17# This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
MEDIUMdiffusion/data/wids/__init__.py2# This file is part of the WebDataset library.COMMENT
MEDIUMdiffusion/data/wids/wids_specs.py17# This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
MEDIUMdiffusion/data/wids/wids.py17# This file is modified from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
MEDIUMdiffusion/data/wids/wids_dl.py17# This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
MEDIUMdiffusion/data/wids/wids_lru.py17# This file is copied from https://github.com/NVlabs/VILA/tree/main/llava/widsCOMMENT
Modern Structural Boilerplate61 hits · 60 pts
SeverityFileLineSnippetContext
LOWapp/safety_check.py23__all__ = ["is_dangerous"]CODE
LOWdiffusion/refiner/diffusers_ltx2_refiner.py2345 def set_value(owner: object, key: object, old_value: object, new_value: object, kind: str) -> None:CODE
LOWdiffusion/distributed/context_parallel/config.py66def set_cp_runtime_config(config: CpRuntimeConfig) -> None:CODE
LOWdiffusion/distributed/context_parallel/config.py77def set_cp_group(group: ProcessGroup | None) -> None:CODE
LOWdiffusion/distributed/context_parallel/__init__.py29__all__ = [CODE
LOWdiffusion/guiders/__init__.py3__all__ = ["AdaptiveProjectedGuidance"]CODE
LOWdiffusion/utils/import_utils.py8logger = logging.getLogger(__name__)CODE
LOWdiffusion/model/act.py21__all__ = ["build_act", "get_act_name"]CODE
LOWdiffusion/model/liger_norms.py33logger = logging.getLogger(__name__)CODE
LOWdiffusion/model/norms.py23__all__ = ["LayerNorm2d", "build_norm", "get_norm_name", "reset_bn", "remove_bn", "set_norm_eps"]CODE
LOWdiffusion/model/norms.py173def set_norm_eps(model: nn.Module, eps: float or None = None, momentum: float or None = None) -> None:CODE
LOWdiffusion/model/wan2_2/vae.py13__all__ = [CODE
LOWdiffusion/model/ltx2/causal_vae.py203 def update_tail(self, z: torch.Tensor, prepend_prev_latent_frames: int) -> None:CODE
LOWdiffusion/model/nets/fastlinear/modules/nn/norm.py24__all__ = ["LayerNorm2d", "build_norm", "get_norm_name", "reset_bn", "remove_bn", "set_norm_eps"]CODE
LOWdiffusion/model/nets/fastlinear/modules/nn/norm.py174def set_norm_eps(model: nn.Module, eps: float or None = None, momentum: float or None = None) -> None:CODE
LOWdiffusion/model/nets/fastlinear/modules/nn/act.py21__all__ = ["build_act", "get_act_name"]CODE
LOWdiffusion/model/wan/attention.py25__all__ = [CODE
LOWdiffusion/model/wan/t5.py12__all__ = [CODE
LOWdiffusion/model/wan/__init__.py8__all__ = [CODE
LOWdiffusion/model/wan/model.py17__all__ = ["WanModel"]CODE
LOWdiffusion/model/wan/clip.py17__all__ = [CODE
LOWdiffusion/model/wan/xlm_roberta.py7__all__ = ["XLMRoberta", "xlm_roberta_large"]CODE
LOWdiffusion/model/wan/vae.py15__all__ = [CODE
LOWdiffusion/model/wan/tokenizers.py9__all__ = ["HuggingfaceTokenizer"]CODE
LOWdiffusion/model/dc_ae/efficientvit/ae_model_zoo.py38__all__ = ["create_dc_ae_model_cfg", "DCAE_HF", "AutoencoderKL"]CODE
LOW…/model/dc_ae/efficientvit/models/nn/triton_rms_norm.py21__all__ = ["TritonRMSNorm2dFunc"]CODE
LOWdiffusion/model/dc_ae/efficientvit/models/nn/norm.py26__all__ = ["LayerNorm2d", "TritonRMSNorm2d", "build_norm", "reset_bn", "set_norm_eps"]CODE
LOWdiffusion/model/dc_ae/efficientvit/models/nn/norm.py201def set_norm_eps(model: nn.Module, eps: Optional[float] = None) -> None:CODE
LOWdiffusion/model/dc_ae/efficientvit/models/nn/ops.py38__all__ = [CODE
LOWdiffusion/model/dc_ae/efficientvit/models/nn/act.py24__all__ = ["build_act"]CODE
LOWdiffusion/model/dc_ae/efficientvit/models/nn/drop.py27__all__ = ["apply_drop_func"]CODE
LOWdiffusion/model/dc_ae/efficientvit/models/utils/list.py19__all__ = [CODE
LOW…fusion/model/dc_ae/efficientvit/models/utils/random.py22__all__ = [CODE
LOW…usion/model/dc_ae/efficientvit/models/utils/network.py26__all__ = [CODE
LOW…/model/dc_ae/efficientvit/models/efficientvit/dc_ae.py41__all__ = ["DCAE", "dc_vae_f32", "dc_ae_f32c32", "dc_ae_f64c128", "dc_ae_f128c512"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/setup.py24__all__ = [CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/misc.py22__all__ = [CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/lr.py24__all__ = ["CosineLRwithWarmup", "ConstantLRwithWarmup"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/ema.py25__all__ = ["EMA"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/ema.py28def update_ema(ema: nn.Module, new_state_dict: dict[str, torch.Tensor], decay: float) -> None:CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/export.py26__all__ = ["export_onnx"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/opt.py21__all__ = ["REGISTERED_OPTIMIZER_DICT", "build_optimizer"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/metric.py23__all__ = ["AverageMeter"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/init.py23__all__ = ["init_modules", "zero_last_gamma"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/image.py26__all__ = ["load_image", "load_image_from_dir", "DMCrop", "CustomImageFolder", "ImageDataset"]CODE
LOWdiffusion/model/dc_ae/efficientvit/apps/utils/dist.py25__all__ = [CODE
LOW…on/model/dc_ae/efficientvit/apps/trainer/run_config.py25__all__ = ["Scheduler", "RunConfig"]CODE
LOW…on/model/dc_ae/efficientvit/apps/trainer/run_config.py107 def update_global_step(self, epoch, batch_id=0) -> None:CODE
LOWdiffusion/model/ops/fused_cam_gdn.py2432__all__ = [CODE
LOWdiffusion/model/ops/fused_gdn_chunkwise_stateful_bwd.py146__all__ = [CODE
LOWdiffusion/model/ops/fused_gdn_cp.py80__all__ = [CODE
LOWdiffusion/model/ops/__init__.py82__all__ = [CODE
LOWdiffusion/model/ops/fused_gdn_chunkwise_stateful_raw.py591__all__ = [CODE
LOWdiffusion/model/ops/frame_gdn/__init__.py5__all__ = ["_build_transition_matrices"]CODE
LOWdiffusion/model/ops/frame_gdn/api.py51__all__ = ["_build_transition_matrices"]CODE
LOWdiffusion/longsana/pipeline/__init__.py5__all__ = [CODE
LOWdiffusion/longsana/model/__init__.py5__all__ = ["DMDSana", "ODERegressionSana", "StreamingSANATrainingModel"]CODE
LOWinference_video_scripts/wm/inference_sana_wm.py202 def set_value(owner: object, key: object, old_value: object, new_value: object, kind: str) -> None:CODE
LOWtrain_scripts/sol_rl/train_flux1.py85logger = logging.getLogger(__name__)CODE
LOWtrain_scripts/sol_rl/train_sana.py84logger = logging.getLogger(__name__)CODE
1 more matches not shown…
Structural Annotation Overuse32 hits · 52 pts
SeverityFileLineSnippetContext
LOWapp/sana_video_refiner_pipeline_diffusers.py53 # Step 1: Generate latent using Sana Video PipelineCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py93 # Step 2: Load LTX2 PipelineCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py168 # Step 3: Manually pack video latent (skip diffusers' normalize, consistent with original code)COMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py180 # Step 4: Create audio latent (becomes zero after normalize, consistent with original code)COMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py202 # Step 5: LTX2 Stage-2 RefinementCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py233 # Step 6: Save outputCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py105 # Step 1: Initialize all modelsCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py126 # Step 2: Initialize all hyperparametersCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py327 # Step 1: Run generator on noisy latentsCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py342 # Step 2: Compute the regression lossCOMMENT
LOWdiffusion/longsana/model/dmd_sana.py575 # Step 1: Sample noise and backward simulate the generator's inputCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py68 # Step 2: Initialize the modelCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py71 # Step 2: Initialize the model and optimizerCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py30 # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py143 # Step 4: Initialize the optimizerCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py157 # Step 5: Initialize the dataloaderCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py172 # Step 6: Initialize the validation dataloader for visualization (fixed prompts)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py446 # Step 1: Get the next batch of text promptsCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py462 # Step 2: Extract the conditional infos for sanaCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py489 # Step 3: Store gradients for the generator (if training the generator)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py510 # Step 4: Store gradients for the critic (if training the critic)COMMENT
LOWdiffusion/longsana/trainer/ode.py92 # Step 4: Initialize the optimizerCOMMENT
LOWdiffusion/longsana/trainer/ode.py100 # Step 5: Initialize the dataloaderCOMMENT
LOWdiffusion/longsana/trainer/ode.py466 # Step 1: Get the next batch of text promptsCOMMENT
LOWdiffusion/longsana/trainer/ode.py471 # Step 2: Extract the conditional infosCOMMENT
LOWdiffusion/longsana/trainer/ode.py475 # Step 3: Train the generatorCOMMENT
LOWdiffusion/longsana/trainer/ode.py32 # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.)COMMENT
LOWdiffusion/longsana/trainer/ode.py69 # Step 2: Initialize the model and optimizerCOMMENT
LOWdiffusion/longsana/trainer/ode.py111 # Step 6: Initialize the validation dataloader for visualization (fixed prompts)COMMENT
LOWdiffusion/longsana/trainer/ode.py512 # Step 4: VisualizationCOMMENT
LOWdiffusion/longsana/trainer/ode.py565 # Step 5: LoggingCOMMENT
LOWinference_video_scripts/wm/inference_sana_wm.py116# NOTE: The default HF checkpoint is bidirectional and is incompatible withCOMMENT
Verbosity Indicators31 hits · 51 pts
SeverityFileLineSnippetContext
LOWapp/sana_video_refiner_pipeline_diffusers.py53 # Step 1: Generate latent using Sana Video PipelineCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py93 # Step 2: Load LTX2 PipelineCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py168 # Step 3: Manually pack video latent (skip diffusers' normalize, consistent with original code)COMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py180 # Step 4: Create audio latent (becomes zero after normalize, consistent with original code)COMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py202 # Step 5: LTX2 Stage-2 RefinementCOMMENT
LOWapp/sana_video_refiner_pipeline_diffusers.py233 # Step 6: Save outputCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py105 # Step 1: Initialize all modelsCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py126 # Step 2: Initialize all hyperparametersCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py327 # Step 1: Run generator on noisy latentsCOMMENT
LOWdiffusion/longsana/model/ode_regression_sana.py342 # Step 2: Compute the regression lossCOMMENT
LOWdiffusion/longsana/model/dmd_sana.py575 # Step 1: Sample noise and backward simulate the generator's inputCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py68 # Step 2: Initialize the modelCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py71 # Step 2: Initialize the model and optimizerCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py30 # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py143 # Step 4: Initialize the optimizerCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py157 # Step 5: Initialize the dataloaderCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py172 # Step 6: Initialize the validation dataloader for visualization (fixed prompts)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py446 # Step 1: Get the next batch of text promptsCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py462 # Step 2: Extract the conditional infos for sanaCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py489 # Step 3: Store gradients for the generator (if training the generator)COMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py510 # Step 4: Store gradients for the critic (if training the critic)COMMENT
LOWdiffusion/longsana/trainer/ode.py92 # Step 4: Initialize the optimizerCOMMENT
LOWdiffusion/longsana/trainer/ode.py100 # Step 5: Initialize the dataloaderCOMMENT
LOWdiffusion/longsana/trainer/ode.py466 # Step 1: Get the next batch of text promptsCOMMENT
LOWdiffusion/longsana/trainer/ode.py471 # Step 2: Extract the conditional infosCOMMENT
LOWdiffusion/longsana/trainer/ode.py475 # Step 3: Train the generatorCOMMENT
LOWdiffusion/longsana/trainer/ode.py32 # Step 1: Initialize the distributed training environment (rank, seed, dtype, logging etc.)COMMENT
LOWdiffusion/longsana/trainer/ode.py69 # Step 2: Initialize the model and optimizerCOMMENT
LOWdiffusion/longsana/trainer/ode.py111 # Step 6: Initialize the validation dataloader for visualization (fixed prompts)COMMENT
LOWdiffusion/longsana/trainer/ode.py512 # Step 4: VisualizationCOMMENT
LOWdiffusion/longsana/trainer/ode.py565 # Step 5: LoggingCOMMENT
Docstring Block Structure8 hits · 40 pts
SeverityFileLineSnippetContext
HIGHdiffusion/utils/chunk_utils.py76Convert chunk_size to chunk_index list with a split strategy. Args: T: Number of latent frames. chuSTRING
HIGHdiffusion/utils/chunk_utils.py135Resolve chunk_index from a config, supporting chunk_size and strategy. Priority: 1) config.model.chunk_index STRING
HIGHdiffusion/utils/chunk_utils.py214Return frame-time positions belonging to size-1 (singleton) chunks. A size-1 chunk has no intra-chunk lookahead, soSTRING
HIGHdiffusion/utils/chunk_utils.py384Normalize chunk_index and detect if uniform. This function handles all the complex logic for: 1. Converting chuSTRING
HIGHdiffusion/model/model_growth_utils.py70 Args: strategy: init strategy name **kwargs: strategy specific parameters RetSTRING
HIGHdiffusion/model/ops/fused_cam_gdn.py1391Fused numerator-only single-path delta-rule scan for the cam branch. Args: q, k, v: ``(B, H, D, N)`` fp32 cSTRING
HIGHdiffusion/model/ops/fused_gdn_cp.py1022End-to-end differentiable CP fused GDN raw entry (num, den). Composes :class:`_CpFusedGdnPrep` -> :func:`cp_frame_gSTRING
HIGHdiffusion/model/ops/fused_gdn.py645One direction of fused BiGDN via the unified kernel. Args: qkv .. eps: see kernel signature. reverse: fSTRING
Redundant / Tautological Comments14 hits · 21 pts
SeverityFileLineSnippetContext
LOWenvironment_setup.sh16# Check if we should skip environment setup entirely (used by CI).COMMENT
LOWtools/metrics/sana_wm/eval_unified.py901 # Check if results already existCOMMENT
LOWapp/app_sana_inpaint.py449 # Check if this is a new image by comparing with stored originalCOMMENT
LOWdiffusion/utils/chunk_utils.py342 # Check if tail (sizes[1:]) is uniformCOMMENT
LOWdiffusion/utils/chunk_utils.py359 # Check if tail (sizes[1:]) is uniformCOMMENT
LOWdiffusion/utils/chunk_utils.py418 # Check if uniform (requires chunk_size for comparison)COMMENT
LOWdiffusion/utils/chunk_utils.py446 # Check if uniformCOMMENT
LOWdiffusion/utils/data_sampler.py262 # Assign samples to each bucketCOMMENT
LOWdiffusion/model/utils.py136 # Check if resizing is neededCOMMENT
LOWdiffusion/longsana/utils/dataset.py294 # Check if all samples list length is consistentCOMMENT
LOWdiffusion/longsana/model/streaming_sana_long.py376 # Check if previous_frames can be used for overlap and auto-compute overlap frame countCOMMENT
LOWdiffusion/longsana/trainer/self_forcing_trainer.py613 # Check if we've reached max iterationsCOMMENT
LOWdiffusion/longsana/trainer/longsana_trainer.py282 # Check if we should train generator on this optimization stepCOMMENT
LOWdiffusion/data/wids/wids.py644 # Check if we're missing the cache too often.COMMENT
Fake / Example Data16 hits · 18 pts
SeverityFileLineSnippetContext
LOWtools/metrics/clip-score/clip_score.py50 self.fake_data = self._load_txt_from_path(fake_path)CODE
LOWtools/metrics/clip-score/clip_score.py63 fake_data = self._load_txt(self.fake_data[index])CODE
LOWtools/metrics/clip-score/clip_score.py64 sample = dict(real=real_data, fake=fake_data, prompt=self.fake_data[index])CODE
LOWtools/metrics/clip-score/src/clip_score/clip_score.py93 fake_data = self._load_modality(fake_path, self.fake_flag)CODE
LOWtools/metrics/clip-score/src/clip_score/clip_score.py95 sample = dict(real=real_data, fake=fake_data)CODE
LOWtools/metrics/clip-score/src/clip_score/clip_score.py124 fake_name = self.fake_folder[idx].split(".")CODE
LOWtools/metrics/clip-score/src/clip_score/clip_score.py125 if fake_name != real_name:CODE
LOWdiffusion/longsana/model/streaming_sana_long.py670 if self.base_model.fake_name == "SANA":CODE
LOWdiffusion/longsana/model/dmd_sana.py256 fake_name = getattr(args, "fake_name", "SANA")CODE
LOWdiffusion/longsana/model/dmd_sana.py257 self.fake_name = fake_nameCODE
LOWdiffusion/longsana/model/dmd_sana.py258 if fake_name == "SANA":CODE
LOWdiffusion/longsana/model/dmd_sana.py314 if self.fake_name == "SANA":CODE
LOWdiffusion/longsana/model/dmd_sana.py416 if self.fake_name == "SANA":CODE
LOWdiffusion/longsana/model/dmd_sana.py762 if self.fake_name == "SANA":CODE
LOW…igs/sana_video_config/longsana/480ms/self_forcing.yaml12fake_name: SANACODE
LOWconfigs/sana_video_config/longsana/480ms/longsana.yaml14fake_name: SANACODE
Magic Placeholder Names2 hits · 10 pts
SeverityFileLineSnippetContext
HIGHasset/docs/sana_lora_dreambooth.md111- `report_to="wandb` will ensure the training runs are tracked on [Weights and Biases](https://wandb.ai/site). To use itCODE
HIGHdocs/sana_lora_dreambooth.md111- `report_to="wandb` will ensure the training runs are tracked on [Weights and Biases](https://wandb.ai/site). To use itCODE
Example Usage Blocks2 hits · 4 pts
SeverityFileLineSnippetContext
LOWenvironment_setup.sh8# Usage:COMMENT
LOWapp/app_sana_inpaint.py315 ### How to use:COMMENT
Modern AI Meta-Vocabulary1 hit · 3 pts
SeverityFileLineSnippetContext
MEDIUMdiffusion/scheduler/self_forcing_flow_euler_sampler.py510 # scaffolding.COMMENT
AI Slop Vocabulary1 hit · 3 pts
SeverityFileLineSnippetContext
MEDIUMdiffusion/longsana/model/dmd_sana.py217 # TODO: Need to make the path more robust.COMMENT
Overly Generic Function Names1 hit · 1 pts
SeverityFileLineSnippetContext
LOW…t_scripts/convert_ImgDataset_to_WebDatasetMS_format.py13def process_data(input_dir, output_tar_name="output.tar"):CODE
Slop Phrases1 hit · 0 pts
SeverityFileLineSnippetContext
LOWtrain_scripts/train_dreambooth_lora_sana.py1016 # make sure to pop weight so that corresponding model is not saved againSTRING