Repository Analysis

ModelTC/LightX2V

Lightweight Image Video Action Generation Inference Framework

15.9 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of ModelTC/LightX2V, a Python project with 2,745 GitHub stars. SynthScan v2.0 examined 355,880 lines of code across 2759 source files, recording 3948 pattern matches distributed across 22 syntactic categories. The overall adjusted score of 15.9 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).

15.9
Adjusted Score
15.9
Raw Score
100%
Time Factor
2026-08-28
Last Push
2.7K
Stars
Python
Language
355.9K
Lines of Code
2.8K
Files
3.9K
Pattern Hits
2026-08-29
Scan Date
0.06
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 13HIGH 142MEDIUM 408LOW 3385

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 3948 distinct pattern matches across 22 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 Separators364 hits · 1221 pts
SeverityFileLineSnippetContext
MEDIUMtools/preprocess/dwpose_onnx.py28# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py30# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py143# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py145# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py253# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py255# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py411# -----------------------------------------------------------------------------COMMENT
MEDIUMtools/preprocess/dwpose_onnx.py413# -----------------------------------------------------------------------------COMMENT
MEDIUMlightx2v_platform/ops/attn/intel_xpu/xpu_flash_attn.py110 # ── normalise 4-D input [B, S, H, D] → [B*S, H, D] ──────────────────COMMENT
MEDIUMlightx2v_platform/ops/attn/intel_xpu/xpu_flash_attn.py123 # ── fast single-sequence path ─────────────────────────────────────COMMENT
MEDIUMlightx2v_platform/ops/attn/intel_xpu/xpu_flash_attn.py130 # ── varlen path: one SDPA call per sequence in the batch ──────────────COMMENT
MEDIUMlightx2v_platform/ops/mm/template.py106 # =========================COMMENT
MEDIUMlightx2v_platform/ops/mm/template.py108 # =========================COMMENT
MEDIUMlightx2v_platform/ops/mm/template.py394 # =========================COMMENT
MEDIUMlightx2v_platform/ops/mm/template.py396 # =========================COMMENT
MEDIUM…x2v/models/video_encoders/hf/ltx2/audio_vae/vocoder.py39# ---------------------------------------------------------------------------COMMENT
MEDIUM…x2v/models/video_encoders/hf/ltx2/audio_vae/vocoder.py42# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py717 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py721 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py991 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py994 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py1004 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py1006 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py36# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py40# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py155# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py158# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py188# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py190# ---------------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py286 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py289 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py337 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py339 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py374 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py376 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py467 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py478 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py566 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py568 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py966 # ------------------------------------------------------------------COMMENT
MEDIUMlightx2v/models/networks/worldmirror/model.py968 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py425 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py431 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py465 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py472 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py499 # ------------------------------------------------------------------COMMENT
MEDIUM…ls/networks/worldmirror/weights/transformer_weights.py501 # ------------------------------------------------------------------COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py183# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py185# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py37# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py39# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py118# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py120# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py341# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py343# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py528# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py530# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py810# ============================================================COMMENT
MEDIUM…v/models/networks/worldmirror/utils/inference_utils.py812# ============================================================COMMENT
MEDIUMlightx2v/models/networks/bagel/modeling_utils.py20# --------------------------------------------------------COMMENT
304 more matches not shown…
Hyper-Verbose Identifiers1129 hits · 1157 pts
SeverityFileLineSnippetContext
LOWtools/preprocess/retarget_pose.py357def fix_lack_keypoints_use_sym(skeleton):CODE
LOWtools/preprocess/process_pipepline.py72 def _get_valid_body_keypoint_mask(cls, pose_meta, keypoint_indices=None):CODE
LOWtools/preprocess/process_pipepline.py90 def _count_valid_body_keypoints(cls, pose_meta):CODE
LOWtools/preprocess/process_pipepline.py105 def _trim_tail_invalid_frames(frames, pose_metas, pose_valid_flags, mode_name):CODE
LOWtools/preprocess/utils.py27def skip_replace_frame_outputs(frame):CODE
LOWtools/preprocess/pose2d_utils.py740def keypoints_from_regression(regression_preds, center, scale, img_size):CODE
LOWtools/preprocess/pose2d_utils.py932def multilabel_classification_accuracy(pred, gt, mask, thr=0.5):CODE
LOWtools/profile/analyze_torch_trace_gap.py127def _collect_gpu_activity_intervals(events: Iterable[dict]) -> list[Interval]:CODE
LOWtools/extract/lora_merger.py350def _find_source_key_from_diff(diff_key: str, source_weights: Dict[str, torch.Tensor]) -> Optional[str]:CODE
LOWtools/postprocess/postprocess_paint.py15def get_postprocess_paint_parser():CODE
LOWtools/postprocess/torchvision_fix.py7def fix_torchvision_functional_tensor():CODE
LOWtools/postprocess/paint_pipeline.py90def _load_texture_gen_pipeline_module(hy3dpaint_root: str) -> ModuleType:CODE
LOWtools/postprocess/paint_pipeline.py110def resolve_paint_output_paths(save_path: str) -> tuple[str, str]:CODE
LOWtools/postprocess/paint_pipeline.py120def _resolve_local_paint_hf_root(model_path: str) -> str:CODE
LOWtools/postprocess/paint_pipeline.py131def _paint_model_source_overlay(model_path: str, hy3dpaint_root: str) -> Iterator[str]:CODE
LOWtools/convert/export_dummy_meta.py43def write_dummy_meta_safetensors(tensor_meta: dict, output_path: str, source_filename: str = ""):CODE
LOWtools/convert/seko_talk_converter.py132def checkpoint_to_safetensors(ckpt_path: Path, output_path: Path, description: str = ""):CODE
LOWapp/utils/model_utils.py458def is_distill_model_from_name(model_name):CODE
LOWapp/utils/video_page.py442 def update_image_path_and_gallery(files):CODE
LOWapp/utils/model_choices.py23def _filter_and_format_models(hf_models, model_path, is_valid_func, require_safetensors=True, additional_filters=None):CODE
LOWapp/utils/model_choices.py209def get_clip_tokenizer_choices(model_path):CODE
LOWapp/utils/model_choices.py230def get_qwen_image_dit_choices(model_path):CODE
LOWapp/utils/model_choices.py285def get_qwen_image_vae_choices(model_path):CODE
LOWapp/utils/model_choices.py321def get_qwen_image_scheduler_choices(model_path):CODE
LOWapp/utils/model_choices.py507def get_z_image_turbo_dit_choices(model_path):CODE
LOWapp/utils/model_choices.py562def get_z_image_turbo_vae_choices(model_path):CODE
LOWapp/utils/model_choices.py598def get_z_image_turbo_scheduler_choices(model_path):CODE
LOWapp/utils/image_page.py308 def update_image_path_and_gallery(files):CODE
LOWapp/utils/image_page.py362 def on_model_type_change_for_defaults(model_type_val):CODE
LOWapp/utils/model_components.py339def build_qwen_image_components(model_path, model_path_input, download_source_input, model_type_input, lang="zh"):CODE
LOWapp/utils/model_components.py369 def get_scheduler_choices_func(model_path_val):CODE
LOWapp/utils/model_components.py381 def get_initial_download_btn_visibility(choices, model_path_val, model_type_val, base_category):CODE
LOWapp/utils/model_components.py506 def update_choices_on_model_type_change(model_type_val, model_path_val):CODE
LOWapp/utils/model_components.py550 def download_qwen_image_scheduler(model_path_val, model_name, download_source_val, progress=gr.Progress()):CODE
LOWapp/utils/model_components.py645def build_z_image_turbo_components(model_path, model_path_input, download_source_input, model_type_input, lang="zh"):CODE
LOWapp/utils/model_components.py780 def download_z_image_turbo_dit(model_path_val, model_name, download_source_val, progress=gr.Progress()):CODE
LOWapp/utils/model_components.py783 def download_z_image_turbo_vae(model_path_val, model_name, download_source_val, progress=gr.Progress()):CODE
LOWapp/utils/model_components.py786 def download_z_image_turbo_scheduler(model_path_val, model_name, download_source_val, progress=gr.Progress()):CODE
LOWapp/utils/model_handlers.py541def download_tokenizer_handler(model_path_val, tokenizer_type, download_source_val, progress=gr.Progress()):CODE
LOWapp/utils/model_handlers.py566def create_update_status_wrappers():CODE
LOWapp/utils/model_handlers.py585 def update_clip_tokenizer_status(model_path_val):CODE
LOWapp/utils/model_handlers.py591 def update_vae_encoder_status(model_path_val, model_name):CODE
LOWapp/utils/model_handlers.py594 def update_vae_decoder_status(model_path_val, model_name):CODE
LOWapp/utils/model_handlers.py603 def update_qwen_image_dit_status(model_path_val, model_name):CODE
LOWapp/utils/model_handlers.py606 def update_qwen_image_vae_status(model_path_val, model_name):CODE
LOWapp/utils/model_handlers.py609 def update_qwen_image_scheduler_status(model_path_val, model_name):CODE
LOWapp/utils/model_handlers.py676 def download_high_noise_model(model_path_val, model_name, task_type_val, download_source_val, progress=gr.Progress()CODE
LOWapp/utils/model_handlers.py706 def download_qwen_image_scheduler(model_path_val, model_name, download_source_val, progress=gr.Progress()):CODE
LOWlightx2v_platform/ops/rope/rope_template.py70 def load_state_dict_from_disk(self, block_index, adapter_block_index=None):CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py11def _load_metax_rotary_embedding_op():CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py38def _metax_rotary_embedding_fake(query, key, positions, freqs, head_size, split_half):CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py47def metax_rotary_embedding_single(CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py61def _metax_rotary_embedding_single_fake(tensor, positions, freqs, head_size, split_half):CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py66def _register_metax_rotary_embedding_lowering():CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py122 def _metax_rotary_embedding_lowering(query, key, positions, freqs, head_size, split_half):CODE
LOWlightx2v_platform/ops/rope/metax_cuda/metax_rope.py129 def _metax_rotary_embedding_single_lowering(tensor, positions, freqs, head_size, split_half):CODE
LOWlightx2v_platform/ops/norm/norm_template.py136 def load_state_dict_from_disk(self, block_index, adapter_block_index=None):CODE
LOWlightx2v_platform/ops/norm/norm_template.py299 def load_state_dict_from_disk(self, block_index, adapter_block_index=None):CODE
LOWlightx2v_platform/ops/norm/metax_cuda/metax_rms_norm.py36def _register_metax_rms_norm_lowering():CODE
LOWlightx2v_platform/ops/mm/template.py480 def load_state_dict_from_disk(self, block_index, adapter_block_index=None):CODE
1069 more matches not shown…
Unused Imports902 hits · 863 pts
SeverityFileLineSnippetContext
LOWtools/preprocess/dwpose_onnx.py13CODE
LOWtools/preprocess/sam_utils.py13CODE
LOWtools/preprocess/__init__.py2CODE
LOWtools/preprocess/__init__.py3CODE
LOWtools/profile/analyze_torch_trace_gap.py24CODE
LOWtools/postprocess/torchvision_fix.py9CODE
LOWtools/postprocess/paint_pipeline.py3CODE
LOWtools/postprocess/paint_pipeline.py67CODE
LOWtools/convert/quant_adapter.py15CODE
LOWtools/convert/converter.py27CODE
LOWtools/convert/quant/__init__.py1CODE
LOWlightx2v_platform/__init__.py1CODE
LOWlightx2v_platform/set_ai_device.py5CODE
LOWlightx2v_platform/set_ai_device.py52CODE
LOWlightx2v_platform/test/test_device.py8CODE
LOWlightx2v_platform/ops/__init__.py3CODE
LOWlightx2v_platform/ops/__init__.py7CODE
LOWlightx2v_platform/ops/__init__.py8CODE
LOWlightx2v_platform/ops/__init__.py9CODE
LOWlightx2v_platform/ops/__init__.py10CODE
LOWlightx2v_platform/ops/__init__.py12CODE
LOWlightx2v_platform/ops/__init__.py13CODE
LOWlightx2v_platform/ops/__init__.py15CODE
LOWlightx2v_platform/ops/__init__.py20CODE
LOWlightx2v_platform/ops/__init__.py21CODE
LOWlightx2v_platform/ops/__init__.py22CODE
LOWlightx2v_platform/ops/__init__.py23CODE
LOWlightx2v_platform/ops/__init__.py24CODE
LOWlightx2v_platform/ops/__init__.py30CODE
LOWlightx2v_platform/ops/__init__.py31CODE
LOWlightx2v_platform/ops/__init__.py32CODE
LOWlightx2v_platform/ops/__init__.py33CODE
LOWlightx2v_platform/ops/__init__.py36CODE
LOWlightx2v_platform/ops/__init__.py37CODE
LOWlightx2v_platform/ops/__init__.py38CODE
LOWlightx2v_platform/ops/__init__.py42CODE
LOWlightx2v_platform/ops/__init__.py43CODE
LOWlightx2v_platform/ops/__init__.py44CODE
LOWlightx2v_platform/ops/__init__.py45CODE
LOWlightx2v_platform/ops/__init__.py47CODE
LOWlightx2v_platform/ops/__init__.py48CODE
LOWlightx2v_platform/ops/__init__.py49CODE
LOWlightx2v_platform/ops/__init__.py50CODE
LOWlightx2v_platform/ops/__init__.py52CODE
LOWlightx2v_platform/ops/rope/intel_xpu/__init__.py1CODE
LOWlightx2v_platform/ops/rope/metax_cuda/__init__.py1CODE
LOWlightx2v_platform/ops/rope/ascend_npu/__init__.py1CODE
LOWlightx2v_platform/ops/rope/cambricon_mlu/__init__.py1CODE
LOWlightx2v_platform/ops/rope/iluvatar_cuda/__init__.py1CODE
LOWlightx2v_platform/ops/rope/enflame_gcu/__init__.py1CODE
LOWlightx2v_platform/ops/norm/intel_xpu/__init__.py1CODE
LOWlightx2v_platform/ops/norm/metax_cuda/__init__.py1CODE
LOWlightx2v_platform/ops/norm/ascend_npu/__init__.py1CODE
LOWlightx2v_platform/ops/norm/ascend_npu/__init__.py2CODE
LOWlightx2v_platform/ops/norm/cambricon_mlu/__init__.py1CODE
LOWlightx2v_platform/ops/norm/iluvatar_cuda/__init__.py1CODE
LOWlightx2v_platform/ops/norm/enflame_gcu/__init__.py1CODE
LOWlightx2v_platform/ops/attn/intel_xpu/__init__.py1CODE
LOWlightx2v_platform/ops/attn/intel_xpu/__init__.py2CODE
LOWlightx2v_platform/ops/attn/amd_rocm/__init__.py1CODE
842 more matches not shown…
Cross-File Repetition120 hits · 600 pts
SeverityFileLineSnippetContext
HIGHlightx2v/utils/ltx2_utils.py0protocol for model loader classes that instantiates models from a configuration dictionary.STRING
HIGH…htx2v/models/video_encoders/hf/ltx2/upsampler/model.py0protocol for model loader classes that instantiates models from a configuration dictionary.STRING
HIGHlightx2v/models/input_encoders/hf/ltx2/utils.py0protocol for model loader classes that instantiates models from a configuration dictionary.STRING
HIGH…video_encoders/hf/ltx2/video_vae/timestep_embedding.py0this matches the implementation in denoising diffusion probabilistic models: create sinusoidal timestep embeddings. argsSTRING
HIGHlightx2v/models/networks/ltx2/infer/utils.py0this matches the implementation in denoising diffusion probabilistic models: create sinusoidal timestep embeddings. argsSTRING
HIGHlightx2v/models/schedulers/qwen_image/scheduler.py0this matches the implementation in denoising diffusion probabilistic models: create sinusoidal timestep embeddings. argsSTRING
HIGHlightx2v/models/schedulers/z_image/scheduler.py0this matches the implementation in denoising diffusion probabilistic models: create sinusoidal timestep embeddings. argsSTRING
HIGHlightx2v/models/video_encoders/hf/wan/vae_2_2.py0fix bfloat16 support for nearest neighbor interpolation.STRING
HIGHlightx2v/models/video_encoders/hf/wan/vae.py0fix bfloat16 support for nearest neighbor interpolation.STRING
HIGH…ain/lightx2v_train/model_zoo/native/wan/modules/vae.py0fix bfloat16 support for nearest neighbor interpolation.STRING
HIGHlightx2v/models/networks/bagel/model.py0create sinusoidal timestep embeddings. :param t: a 1-d tensor of n indices, one per batch element. these may be fractionSTRING
HIGHlightx2v/models/networks/bagel/modeling_utils.py0create sinusoidal timestep embeddings. :param t: a 1-d tensor of n indices, one per batch element. these may be fractionSTRING
HIGHlightx2v/models/networks/neopp/infer/pre_infer.py0create sinusoidal timestep embeddings. :param t: a 1-d tensor of n indices, one per batch element. these may be fractionSTRING
HIGHlightx2v/models/networks/worldplay/model.py0initialize inference modules and connect action weights.STRING
HIGHlightx2v/models/networks/worldplay/ar_model.py0initialize inference modules and connect action weights.STRING
HIGHlightx2v/models/networks/worldplay/bi_model.py0initialize inference modules and connect action weights.STRING
HIGHlightx2v/models/networks/worldplay/model.py0run inference with action and camera pose conditioning. args: inputs: dict containing: - text_encoder_output: text encodSTRING
HIGHlightx2v/models/networks/worldplay/ar_model.py0run inference with action and camera pose conditioning. args: inputs: dict containing: - text_encoder_output: text encodSTRING
HIGHlightx2v/models/networks/worldplay/bi_model.py0run inference with action and camera pose conditioning. args: inputs: dict containing: - text_encoder_output: text encodSTRING
HIGH…odels/networks/worldplay/infer/ar_transformer_infer.py0modulate with per-token scale and shift (no unsqueeze). args: x: [l, c] tensor scale: [b, l, c] or [b, c] tensor shift: STRING
HIGH…v/models/networks/worldplay/infer/transformer_infer.py0modulate with per-token scale and shift (no unsqueeze). args: x: [l, c] tensor scale: [b, l, c] or [b, c] tensor shift: STRING
HIGH…odels/networks/worldplay/infer/bi_transformer_infer.py0modulate with per-token scale and shift (no unsqueeze). args: x: [l, c] tensor scale: [b, l, c] or [b, c] tensor shift: STRING
HIGH…odels/networks/worldplay/infer/ar_transformer_infer.py0apply projective positional encoding to q, k, v. args: q: query tensor [b, l, h, d] or [b, h, l, d] k: key tensor v: valSTRING
HIGH…v/models/networks/worldplay/infer/transformer_infer.py0apply projective positional encoding to q, k, v. args: q: query tensor [b, l, h, d] or [b, h, l, d] k: key tensor v: valSTRING
HIGH…odels/networks/worldplay/infer/bi_transformer_infer.py0apply projective positional encoding to q, k, v. args: q: query tensor [b, l, h, d] or [b, h, l, d] k: key tensor v: valSTRING
HIGH…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py0load worldplay transformer with action conditioning.STRING
HIGH…ghtx2v/models/runners/worldplay/worldplay_bi_runner.py0load worldplay transformer with action conditioning.STRING
HIGH…v/models/runners/worldplay/worldplay_distill_runner.py0load worldplay transformer with action conditioning.STRING
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HIGH…ghtx2v/models/runners/worldplay/worldplay_bi_runner.py0convert pose string/json to action tensors. args: pose_data: pose string (e.g., "w-3, right-0.5") or json path or dict lSTRING
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HIGHlightx2v/models/schedulers/worldplay/bi_scheduler.py0initialize latents and timesteps with optional pose conditioning. args: seed: random seed for latent initialization lateSTRING
HIGHlightx2v/models/schedulers/worldplay/scheduler.py0initialize latents and timesteps with optional pose conditioning. args: seed: random seed for latent initialization lateSTRING
HIGH…models/schedulers/hidream_o1_image/fm_solvers_unipc.py0`unipcmultistepscheduler` is a training-free framework designed for the fast sampling of diffusion models. this model inSTRING
HIGHlightx2v/models/schedulers/wan/s2v/fm_solvers_unipc.py0`unipcmultistepscheduler` is a training-free framework designed for the fast sampling of diffusion models. this model inSTRING
HIGH…odel_zoo/native/lingbot_video/scheduling_flow_unipc.py0`unipcmultistepscheduler` is a training-free framework designed for the fast sampling of diffusion models. this model inSTRING
HIGH…v_train/model_zoo/native/wan/utils/fm_solvers_unipc.py0`unipcmultistepscheduler` is a training-free framework designed for the fast sampling of diffusion models. this model inSTRING
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HIGH…ghtx2v/models/schedulers/hunyuan3d/flow_match_euler.py0the index counter for current timestep. it will increase 1 after each scheduler step.STRING
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HIGH…odel_zoo/native/lingbot_video/scheduling_flow_unipc.py0the index counter for current timestep. it will increase 1 after each scheduler step.STRING
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HIGH…v_train/model_zoo/native/wan/utils/fm_solvers_unipc.py0the index counter for current timestep. it will increase 1 after each scheduler step.STRING
HIGH…models/schedulers/hidream_o1_image/fm_solvers_unipc.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGH…ghtx2v/models/schedulers/hunyuan3d/flow_match_euler.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGHlightx2v/models/schedulers/wan/s2v/fm_solvers_unipc.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGH…odel_zoo/native/lingbot_video/scheduling_flow_unipc.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGH…ightx2v_train/model_zoo/native/wan/utils/fm_solvers.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGH…v_train/model_zoo/native/wan/utils/fm_solvers_unipc.py0the index for the first timestep. it should be set from pipeline with `set_begin_index` method.STRING
HIGH…models/schedulers/hidream_o1_image/fm_solvers_unipc.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGH…ghtx2v/models/schedulers/hunyuan3d/flow_match_euler.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGHlightx2v/models/schedulers/wan/s2v/fm_solvers_unipc.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGH…odel_zoo/native/lingbot_video/scheduling_flow_unipc.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGH…ightx2v_train/model_zoo/native/wan/utils/fm_solvers.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGH…v_train/model_zoo/native/wan/utils/fm_solvers_unipc.py0sets the begin index for the scheduler. this function should be run from pipeline before the inference. args: begin_indeSTRING
HIGH…models/schedulers/hidream_o1_image/fm_solvers_unipc.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGHlightx2v/models/schedulers/wan/s2v/fm_solvers_unipc.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGH…odel_zoo/native/lingbot_video/scheduling_flow_unipc.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
HIGH…ightx2v_train/model_zoo/native/wan/utils/fm_solvers.py0sets the discrete timesteps used for the diffusion chain (to be run before inference). args: num_inference_steps (`int`)STRING
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Excessive Try-Catch Wrapping382 hits · 434 pts
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LOWtools/download_rife.py99 except Exception as e:CODE
MEDIUMtools/download_rife.py100 print(f"Error: {e}")CODE
LOWtools/download_rife.py111 except Exception as e:CODE
MEDIUMtools/download_rife.py112 print(f"Error deleting zip file: {e}")CODE
LOWtools/download_rife.py120 except Exception as e:CODE
MEDIUMtools/download_rife.py121 print(f"Error deleting directory {item}: {e}")CODE
LOWtools/download_rife.py128 except Exception as e:CODE
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LOWtools/preprocess/pose2d_utils.py1052 except Exception as e:CODE
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LOWlightx2v/server/api/tasks/common.py131 except Exception as e:CODE
LOWlightx2v/server/api/tasks/common.py145 except Exception as e:CODE
MEDIUMlightx2v/server/api/tasks/common.py137def stop_all_running_tasks():CODE
LOWlightx2v/server/api/tasks/video.py37 except Exception as e:CODE
LOWlightx2v/server/api/tasks/video.py109 except Exception as e:CODE
LOWlightx2v/server/api/tasks/image.py118 except Exception as e:CODE
LOWlightx2v/server/api/tasks/image.py180 except Exception as e:CODE
LOWlightx2v/server/api/tasks/image.py239 except Exception as e:CODE
LOWlightx2v/server/services/file_service.py72 except Exception as e:CODE
LOWlightx2v/server/services/file_service.py123 except Exception as e:CODE
LOWlightx2v/server/services/file_service.py181 except Exception as e:CODE
LOWlightx2v/server/services/distributed_utils.py56 except Exception as e:CODE
LOWlightx2v/server/services/distributed_utils.py73 except Exception:CODE
MEDIUMlightx2v/server/services/distributed_utils.py33def init_process_group(self) -> bool:CODE
MEDIUMlightx2v/server/services/distributed_utils.py70def _destroy():CODE
LOWlightx2v/server/services/inference/worker.py64 except Exception as e:CODE
LOWlightx2v/server/services/inference/worker.py114 except Exception as e:CODE
LOWlightx2v/server/services/inference/worker.py188 except Exception as e:CODE
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Deep Nesting352 hits · 338 pts
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AI Structural Patterns222 hits · 219 pts
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LOWlightx2v/models/video_encoders/hf/wan/vae_2_2.py1050CODE
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Modern Structural Boilerplate193 hits · 194 pts
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LOWlightx2v/models/networks/flux2/infer/__init__.py6__all__ = [CODE
LOWlightx2v/models/networks/motus/__init__.py4__all__ = [CODE
LOWlightx2v/models/networks/motus/infer/__init__.py5__all__ = ["MotusPreInfer", "MotusTransformerInfer", "MotusPostInfer"]CODE
LOWlightx2v/models/networks/worldplay/__init__.py11__all__ = [CODE
133 more matches not shown…
Hallucination Indicators13 hits · 170 pts
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CRITICALlightx2v/server/services/generation/sensenova_vision.py184 source_path = self.inference_service.worker.runner.config.get(CODE
CRITICALlightx2v/server/services/generation/sensenova_vision.py275 source_path = self.inference_service.worker.runner.config.get(CODE
CRITICALlightx2v/server/services/generation/base.py31 task_type = self.inference_service.worker.runner.config.get("task", "t2v")CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py22 dst.conv1_local.conv.weight.data.copy_(src.conv1_local_weight.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py23 dst.conv1_local.conv.bias.data.copy_(src.conv1_local_bias.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py24 dst.conv2.conv.weight.data.copy_(src.conv2_weight.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py25 dst.conv2.conv.bias.data.copy_(src.conv2_bias.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py26 dst.conv3.conv.weight.data.copy_(src.conv3_weight.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py27 dst.conv3.conv.bias.data.copy_(src.conv3_bias.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py30 dst.conv1_global.conv.weight.data.copy_(src.conv1_global_weight.tensor)CODE
CRITICAL…/models/networks/wan/infer/s2v/causal_audio_encoder.py31 dst.conv1_global.conv.bias.data.copy_(src.conv1_global_bias.tensor)CODE
CRITICALlightx2v/models/runners/flux2/flux2_runner.py358 bn_mean = self.vae.vae.bn.running_mean.view(1, -1, 1, 1).to(latents.device, latents.dtype)CODE
CRITICALlightx2v/models/runners/flux2/flux2_runner.py359 bn_std = torch.sqrt(self.vae.vae.bn.running_var.view(1, -1, 1, 1) + self.vae.vae.config.batch_norm_eps).to(latenCODE
Over-Commented Block125 hits · 119 pts
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LOWtools/preprocess/human_visualization.py301 # kp2ds_body = kp2ds_body[:18]COMMENT
LOWtools/preprocess/human_visualization.py321 [15, 17],COMMENT
LOWtools/preprocess/human_visualization.py461 kp2ds = kp2ds.copy()COMMENT
LOWtools/preprocess/human_visualization.py481 # [12, 13],COMMENT
LOWtools/preprocess/human_visualization.py501 # [0, 255, 170],COMMENT
LOWtools/preprocess/human_visualization.py521 # keypoint2 = kp2ds_body[k2_index - 1]COMMENT
LOWtools/preprocess/ltx2.3_preprocess_data.py1# Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.COMMENT
LOWapp/run_gradio.sh1#!/bin/bashCOMMENT
LOWlightx2v/utils/set_config.py181 # only expose the resolved transformer path for logging.COMMENT
LOWlightx2v/utils/va_reader_omni.py601COMMENT
LOWlightx2v/utils/va_reader_omni.py621 # ...COMMENT
LOW…2v/models/video_encoders/hf/ltx2/audio_vae/upsample.py21 self.causality_axis = causality_axisCOMMENT
LOW…ders/hf/hunyuan3d/autoencoders/attention_processors.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…s/video_encoders/hf/hunyuan3d/autoencoders/__init__.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…encoders/hf/hunyuan3d/autoencoders/attention_blocks.py1# Open Source Model Licensed under the Apache License Version 2.0COMMENT
LOW…dels/video_encoders/hf/hunyuan3d/autoencoders/model.py1# Open Source Model Licensed under the Apache License Version 2.0COMMENT
LOW…coders/hf/hunyuan3d/autoencoders/surface_extractors.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…_encoders/hf/hunyuan3d/autoencoders/volume_decoders.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…htx2v/models/video_encoders/hf/minimax_h3/video_vae.py1# Copyright 2026 The MiniMax and HuggingFace Teams. All rights reserved.COMMENT
LOWlightx2v/models/video_encoders/hf/minimax_h3/weights.py1# Copyright 2026 The LightX2V Team.COMMENT
LOWlightx2v/models/networks/worldmirror/model.py221 config has no concept of quantization.COMMENT
LOWlightx2v/models/networks/worldmirror/model.py261 # per block per forward (cheap in practice for single-sceneCOMMENT
LOWlightx2v/models/networks/worldmirror/model.py461 if src is not None and src.shape == tensor.shape:COMMENT
LOW…ls/networks/worldmirror/weights/transformer_weights.py241 self.cam_trunk_depth = cam_trunk_depthCOMMENT
LOW…ls/networks/worldmirror/weights/transformer_weights.py521 # Quantized leaves own their storage dtype (fp8/int8/nvfp4/...).COMMENT
LOWlightx2v/models/networks/worldmirror/comm/padding.py21 # 计算需要填充的长度COMMENT
LOWlightx2v/models/networks/worldmirror/comm/padding.py41COMMENT
LOW…v/models/networks/worldmirror/models/utils/sh_utils.py1# Copyright 2021 The PlenOctree Authors.COMMENT
LOW…models/networks/worldmirror/models/heads/dense_head.py141COMMENT
LOWlightx2v/models/networks/bagel/modeling_utils.py1# Copyright (c) 2022 Facebook, Inc. and its affiliates.COMMENT
LOWlightx2v/models/networks/worldplay/prope/camera_rope.py1# MIT LicenseCOMMENT
LOW…x2v/models/networks/hunyuan3d/utils/hy3dshape/utils.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…/models/input_encoders/hf/hunyuan3d/image_processor.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…tx2v/models/input_encoders/hf/hunyuan3d/conditioner.py1# Open Source Model Licensed under the Apache License Version 2.0COMMENT
LOWlightx2v/models/input_encoders/hf/hunyuan3d/rembg.py1# Hunyuan 3D is licensed under the TENCENT HUNYUAN NON-COMMERCIAL LICENSE AGREEMENTCOMMENT
LOW…htx2v/models/audio_encoders/hf/minimax_h3/audio_vae.py1# Copyright 2025 The MiniMax authors and The HuggingFace Team. All rights reserved.COMMENT
LOW…htx2v/models/runners/worldmirror/worldmirror_runner.py261 model_cfg["enable_bf16"] = TrueCOMMENT
LOW…ghtx2v/models/schedulers/hunyuan3d/flow_match_euler.py1# Copyright 2024 Stability AI, Katherine Crowson and The HuggingFace Team. All rights reserved.COMMENT
LOWlightx2v/disagg/rdma_server.py281 # 单边写通常不需要接收方做额外操作,除非使用了带立即数或原子操作需要确认COMMENT
LOWlightx2v/disagg/rdma_server.py301# conn = srv.handshake(host=args.listen_host, port=args.listen_port)COMMENT
LOWlightx2v/disagg/rdma_client.py461# # msg = b"Hello RDMA!"COMMENT
LOWlightx2v/disagg/rdma_client.py481# print(f"FAA old value: {old_value}")COMMENT
LOWlightx2v/common/ops/attn/svg2_attn_utils.py1161 # --- End of loop over K blocks ---COMMENT
LOWlightx2v/common/ops/mm/mm_weight.py2481 # On-the-fly symmetric fp8 weight quantization. Used when theCOMMENT
LOW…d256/assets/rev256_onednn_v2_84tflops_pipelined_qk.cpp1#include <sycl/sycl.hpp>COMMENT
LOW…-hd256/assets/rev256_onednn_v2_83tflops_mad_fusion.cpp1#include <sycl/sycl.hpp>COMMENT
LOW…sdp-hd256/assets/rev256_onednn_v2_88tflops_s_scatter.h1// Approach 2: Eliminate S Register Transpose via lsc_slm_scatter Write + Block ReadCOMMENT
LOW…sdp-hd256/assets/rev256_onednn_v2_88tflops_s_scatter.h361 // Four scatter calls per qp: kv groups 0..3, 4..7, 8..11, 12..15.COMMENT
LOW…hd256/assets/rev256_onednn_v2_86tflops_qk_pipeline.cpp1#include <sycl/sycl.hpp>COMMENT
LOW…p-hd256/assets/rev256_onednn_v2_88tflops_s_scatter.cpp1#include <sycl/sycl.hpp>COMMENT
LOW…dp-hd256/assets/rev256_onednn_v2_83tflops_mad_fusion.h1// oneDNN-inspired Flash Attention v2 kernel for HD=256COMMENT
LOW…ls/xe2-sdp-hd256/assets/flash.attn.b.mha256.fp16.opt.h1// Optimized FP16 Flash Attention kernel for HD=256COMMENT
LOW…p-hd256/assets/rev256_onednn_v2_86tflops_qk_pipeline.h1// oneDNN-inspired Flash Attention v2 kernel for HD=256COMMENT
LOW…_skills/xe2-sdp-hd256/assets/test_rev256_onednn_v2.cpp1#include <sycl/sycl.hpp>COMMENT
LOW…-hd256/assets/rev256_onednn_v2_84tflops_pipelined_qk.h1// oneDNN-inspired Flash Attention v2 kernel for HD=256COMMENT
LOW…d256/assets/rev256_onednn_v2_82tflops_fp16_transpose.h1// oneDNN-inspired Flash Attention v2 kernel for HD=256COMMENT
LOW…skills/onednn-fp8-gemm/assets/fp16xfp8_per_n_scale.cpp1// =============================================================================COMMENT
LOW…specific_skills/onednn-fp8-gemm/assets/test_onednn.cpp1// Pure C++ ULT for oneDNN matmul primitives on Intel XPU (SYCL)COMMENT
LOW…pecific_skills/xe2-sdp-kernels/assets/decode_sdp_gqa.h1// decode_sdp_gqa.hCOMMENT
LOW…pecific_skills/xe2-sdp-kernels/assets/decode_sdp_gqa.h201 block_store<fp32, HD>(out + chunk_idx * headQ * HD + (q_head_idx + h) * HD,COMMENT
65 more matches not shown…
Structural Annotation Overuse48 hits · 93 pts
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LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py522 # Step 1: Crop first to avoid exceeding target dimensionsCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py525 # Step 2: Calculate padding needed for time and frequency dimensionsCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py529 # Step 3: Apply padding if neededCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py541 # Step 4: Final safety crop to ensure exact target shapeCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py53 # Step 1: RMSNormCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py68 # Step 2: Load scale and shift based on formatCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py87 # Step 3: Apply modulation: x_hat * (1 + scale) + shiftCOMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py257 # Step 1: Cache text KV (called once at generation start)COMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py283 # Step 2: For non-first chunks, cache context frame KVCOMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py288 # Step 3: Run denoising for this chunkCOMMENT
LOW…ic_skills/xe2-esimd-gemv/references/kernel-patterns.md109 // Step 1: init SLM — MUST be firstCOMMENT
LOW…ic_skills/xe2-esimd-gemv/references/kernel-patterns.md122 // Step 2: compute partial dot productCOMMENT
LOW…ic_skills/xe2-esimd-gemv/references/kernel-patterns.md137 // Step 3: store partial sum to SLMCOMMENT
LOW…ic_skills/xe2-esimd-gemv/references/kernel-patterns.md144 // Step 4: synchronizeCOMMENT
LOW…ic_skills/xe2-esimd-gemv/references/kernel-patterns.md147 // Step 5: reduce and write output (k_thread_id == 0 only)COMMENT
LOWdocs/EN/source/getting_started/quickstart.md68#### Step 1: Clone RepositoryCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md76#### Step 2: Create Conda Virtual EnvironmentCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md84#### Step 3: Install DependenciesCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md90#### Step 4: Install Attention OperatorsCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md109#### Step 4: Install Quantization Operators (Optional)COMMENT
LOWdocs/EN/source/getting_started/quickstart.md149#### Step 5: Verify InstallationCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md162#### Step 1: Check CUDA VersionCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md172#### Step 2: Create Python EnvironmentCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md184#### Step 3: Install PyTorch FrameworkCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md211#### Step 4: Install Windows Version vLLMCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md225#### Step 5: Install Attention Mechanism OperatorsCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md246#### Step 6: Clone RepositoryCOMMENT
LOWdocs/EN/source/getting_started/quickstart.md258#### Step 7: Install Quantization Operators (Optional)COMMENT
LOWexamples/BeginnerGuide/EN/02.Wan21-1.3B.md222# Step 1: Create LightX2VPipelineCOMMENT
LOWexamples/BeginnerGuide/EN/02.Wan21-1.3B.md229# Step 2: Set runtime parametersCOMMENT
LOWexamples/BeginnerGuide/EN/02.Wan21-1.3B.md250# Step 3: Start generating videos, can generate multiple timesCOMMENT
LOWscripts/server/post_multi_servers.py48 # Step 2: Monitor task status until completionCOMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py48 # Step 1: Send to Decoder first (sets up Phase2 receiver)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py54 # Step 2: Send to Transformer (Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py60 # Step 3: Send to Encoder (text encoding + Phase1 send)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py65 # Step 4: Poll Decoder for completion (image saved on Decoder node)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py57 # Step 1: Send to Decoder first (sets up Phase2 receiver)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py63 # Step 2: Send to Transformer (Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py69 # Step 3: Send to Encoder (text + image encoding + Phase1 send)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py74 # Step 4: Poll Decoder for completion (image saved on Decoder node)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py44 # Step 1: Send to Decoder first (sets up Phase2 receiver, starts blocking)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py50 # Step 2: Send to Transformer (sets up Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py56 # Step 3: Send to Encoder (triggers T5 encoding + Phase1 Mooncake send)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py61 # Step 4: Poll Decoder for final completion (video is saved on Decoder node)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py55 # Step 1: Send to Decoder first (sets up Phase2 receiver, starts blocking)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py61 # Step 2: Send to Transformer (sets up Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py67 # Step 3: Send to Encoder (triggers T5/CLIP/VAE encoding + Phase1 Mooncake send)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py72 # Step 4: Poll Decoder for final completion (video is saved on Decoder node)COMMENT
Cross-Language Confusion11 hits · 68 pts
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HIGHlightx2v/disagg/services/controller.py663 " kill -TERM ${pid} >/dev/null 2>&1 || true",CODE
HIGHlightx2v/disagg/services/controller.py667 " kill -KILL ${pid} >/dev/null 2>&1 || true",CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py174 let lastState = null;CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py232 const seedMatches = expected.seed === null || Number(statusData.seed) === expected.seed;CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py238 if (sawSwitching && statusData.state === "failure") {CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py256 if (configMatches && statusData.state === "ready" &&CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py260 if (sawSwitching && statusData.state === "failure") {CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py324 if (opt && typeof opt === "object") {CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py326 o.textContent = String(opt.label || opt.value);CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py333 if (current && Array.from(select.options).some(o => o.value === String(current))) {CODE
HIGH…ualization/visualization/image_web_viewer_node/page.py350 if (stats && stats.episodes > 0) {CODE
Verbosity Indicators27 hits · 56 pts
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LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py522 # Step 1: Crop first to avoid exceeding target dimensionsCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py525 # Step 2: Calculate padding needed for time and frequency dimensionsCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py529 # Step 3: Apply padding if neededCOMMENT
LOW…v/models/video_encoders/hf/ltx2/audio_vae/audio_vae.py541 # Step 4: Final safety crop to ensure exact target shapeCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py53 # Step 1: RMSNormCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py68 # Step 2: Load scale and shift based on formatCOMMENT
LOWlightx2v/models/networks/ltx2/infer/triton_ops.py87 # Step 3: Apply modulation: x_hat * (1 + scale) + shiftCOMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py257 # Step 1: Cache text KV (called once at generation start)COMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py283 # Step 2: For non-first chunks, cache context frame KVCOMMENT
LOW…ghtx2v/models/runners/worldplay/worldplay_ar_runner.py288 # Step 3: Run denoising for this chunkCOMMENT
LOWscripts/server/post_multi_servers.py48 # Step 2: Monitor task status until completionCOMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py48 # Step 1: Send to Decoder first (sets up Phase2 receiver)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py54 # Step 2: Send to Transformer (Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py60 # Step 3: Send to Encoder (text encoding + Phase1 send)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_t2i.py65 # Step 4: Poll Decoder for completion (image saved on Decoder node)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py57 # Step 1: Send to Decoder first (sets up Phase2 receiver)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py63 # Step 2: Send to Transformer (Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py69 # Step 3: Send to Encoder (text + image encoding + Phase1 send)COMMENT
LOWscripts/server/disagg/qwen/post_qwen_i2i.py74 # Step 4: Poll Decoder for completion (image saved on Decoder node)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py44 # Step 1: Send to Decoder first (sets up Phase2 receiver, starts blocking)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py50 # Step 2: Send to Transformer (sets up Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py56 # Step 3: Send to Encoder (triggers T5 encoding + Phase1 Mooncake send)COMMENT
LOWscripts/server/disagg/wan/post_wan_t2v.py61 # Step 4: Poll Decoder for final completion (video is saved on Decoder node)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py55 # Step 1: Send to Decoder first (sets up Phase2 receiver, starts blocking)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py61 # Step 2: Send to Transformer (sets up Phase1 receiver + Phase2 sender)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py67 # Step 3: Send to Encoder (triggers T5/CLIP/VAE encoding + Phase1 Mooncake send)COMMENT
LOWscripts/server/disagg/wan/post_wan_i2v.py72 # Step 4: Poll Decoder for final completion (video is saved on Decoder node)COMMENT
Docstring Block Structure11 hits · 55 pts
SeverityFileLineSnippetContext
HIGHtools/preprocess/pose2d.py348 Load images from various input types. Args: inputs (Union[str, np.ndarray, List[np.ndarraySTRING
HIGHlightx2v/utils/input_info.py564Calculate target_video_length from video duration using the formula: target_video_length = (fps * seconds + 3) // 4 STRING
HIGH…coders/hf/hunyuan3d/autoencoders/surface_extractors.py135 Extract surface mesh using Differentiable Marching Cubes (DMC) algorithm. Args: grid_logitSTRING
HIGHlightx2v/models/networks/worldmirror/utils/geometry.py124 Create a sliding window view of the input array along a specified axis. This function creates a memory-efficieSTRING
HIGH…htx2v/models/networks/worldmirror/utils/visual_util.py229 Converts model predictions to a 3D scene represented as a GLB file. Args: predictions (dict): DictionaSTRING
HIGH…tx2v/models/networks/worldmirror/models/layers/rope.py232Applies 2D rotary position embeddings to input tokens. Args: tokens: Input tensor of shape (batch_sSTRING
HIGH…odels/networks/wan/infer/matrix_game2/posemb_layers.py71 Reshape frequency tensor for broadcasting it with another tensor. This function reshapes the frequency tensor STRING
HIGH…ghtx2v/models/input_encoders/hf/vace/vace_processor.py28 Resize, center crop and normalize for decord loaded video (torch.Tensor type) Parameters: viSTRING
HIGHlightx2v_kernel/python/lightx2v_kernel/utils.py39 Compute SNR between y_pred(tensor) and y_real(tensor) SNR can be calcualted as following equation: SNSTRING
HIGH…ain/lightx2v_train/model_zoo/native/wan/utils/utils.py69 Convert a string to a boolean. Supported true values: 'yes', 'true', 't', 'y', '1' Supported false values:STRING
HIGH…tx2v_train/model_zoo/native/wan/utils/qwen_vl_utils.py129calculate the number of frames for video used for model inputs. Args: ele (dict): a dict contains the confiSTRING
Redundant / Tautological Comments17 hits · 27 pts
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LOWtools/extract/lora_extractor.py213 # Check if tensor shapes matchCOMMENT
LOWtools/extract/lora_extractor.py217 # Check if tensor data types matchCOMMENT
LOWtools/extract/lora_extractor.py224 # Check if there are actual changesCOMMENT
LOWtools/extract/lora_extractor.py250 # Check if rank is reasonableCOMMENT
LOWtools/convert/converter.py371 # Check if key matches target modulesCOMMENT
LOWapp/run_gradio.sh106# Check if model path existsCOMMENT
LOWapp/run_gradio.sh122# Check if demo file existsCOMMENT
LOWlightx2v/utils/lora_loader.py156 # Check if down weight existsCOMMENT
LOW…v/models/video_encoders/hf/ltx2/video_vae/video_vae.py798 # Check if current temporal slice overlaps with previous temporal sliceSTRING
LOW…2v/models/networks/ltx2/weights/transformer_weights.py183 # Check if tensor parallel is enabledCOMMENT
LOW…odels/networks/worldplay/infer/ar_transformer_infer.py751 # Check if ProPE is enabledCOMMENT
LOWlightx2v/models/networks/worldplay/infer/pre_infer.py63 # Check if we have per-frame timestep from BI runnerCOMMENT
LOWlightx2v/models/networks/longcat_image/model.py121 # Check if CFG parallel should be usedCOMMENT
LOW…v/models/runners/longcat_image/longcat_image_runner.py246 # Check if prompt rewrite is enabledCOMMENT
LOWlightx2v/common/ops/attn/svg2_attn_utils.py940 # Check if this block needs computationCOMMENT
LOWlightx2v/common/ops/attn/svg2_attn.py243 # Check if block_col_sz and block_row_sz are the same for each headCOMMENT
LOWlightx2v/common/ops/attn/kernels/sla_kernel.py240 # Increment pointersCOMMENT
Self-Referential Comments9 hits · 26 pts
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MEDIUMlightx2v/utils/generate_task_id.py22 # Create an independent random instanceCOMMENT
MEDIUM…models/video_encoders/hf/ltx2/video_vae/convolution.py124 # Define the size of the channels after the first convolutionCOMMENT
MEDIUM…tx2v/models/networks/worldmirror/models/layers/rope.py3# This module provides a clean implementation of 2D Rotary Position Embeddings,COMMENT
MEDIUM…models/networks/worldmirror/models/heads/dense_head.py142 # This module implements the DPT (Dense Prediction Transformer) head as proposed inSTRING
MEDIUMlightx2v/models/networks/neopp/infer/pre_infer.py34 # Create the batch index for each patch (B x patch count)COMMENT
MEDIUM…x2v/models/networks/hunyuan3d/utils/torchvision_fix.py20 # Create a mock functional_tensor module with the required functionsCOMMENT
MEDIUM…x2v/models/networks/hunyuan3d/utils/torchvision_fix.py82 # Create the mock module instanceCOMMENT
MEDIUM…x2v/models/input_encoders/hf/hunyuan15/qwen25/model.py324 # Create a deep copy to avoid modifying the original templateCOMMENT
MEDIUM…htx2v_train/lightx2v_train/schedulers/flow_matching.py103 # The following methods are for inference onlyCOMMENT
Fake / Example Data16 hits · 16 pts
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LOWscripts/platforms/mlu/openai_image/post_i2i_openai.sh9--api_key "dummy-key" \CODE
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LOWscripts/server/openai_image/post_t2i_openai.sh9--api_key "dummy-key" \CODE
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MEDIUMtools/preprocess/human_visualization.py1263CODE
MEDIUM…tx2v/models/input_encoders/hf/hunyuan3d/conditioner.py269CODE
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MEDIUMlightx2v/models/runners/wan/wan_dancer_runner.py45 # two-stage orchestration in run_pipeline and never calls the binding.COMMENT
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Example Usage Blocks1 hit · 2 pts
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LOW…pts/server/disagg/qwen/start_qwen_t2i_decentralized.sh9# Usage:COMMENT
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MEDIUMlightx2v/models/networks/base_model.py573 This is a basic implementation. Subclasses may override for moreSTRING