Will Lin
91bf3f2752
Namespace-package auto-discovery (the default for packages.find in
pyproject.toml) treats any directory as a package, so local artifact
dirs like outputs/ at the repo root get picked up as packages. Combined
with the second search root apps/dreamverse (whose empty outputs/ dir
maps the 'outputs' package there), the editable build fails with:
error: package directory 'apps/dreamverse/outputs/ltx2_overfit' does not exist
Switch to an explicit include list so only the two real packages are
discovered, making the build immune to whatever run artifacts happen to
sit in the working tree. This also stops fastvideo-kernel/ (separate
build) and comfyui/docs/etc. from being swept into the wheel.
304 lines
8.6 KiB
TOML
304 lines
8.6 KiB
TOML
[build-system]
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requires = ["setuptools>=61.0"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "fastvideo"
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version = "0.2.0"
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description = "FastVideo"
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readme = "README.md"
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requires-python = ">=3.10"
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classifiers = [
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: Apache Software License",
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]
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dependencies = [
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# Core Libraries
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"scipy>=1.14.1",
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"six>=1.16.0",
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"h5py>=3.12.1",
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"requests>=2.32.2",
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# Machine Learning & Transformers
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# GLM-Image's AR encoder (GlmImageForConditionalGeneration) first ships in
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# transformers 5.0.0; floor bumped from >=4.57.3 to >=5.0.0 (stable, not rc).
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"transformers>=5.0.0",
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# <0.23: tokenizers 0.23 renamed RobertaProcessing's binding args, so
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# transformers' CLIP-style tokenizer loading dies with
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# "RobertaProcessing.__new__() got an unexpected keyword argument 'cls'".
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"tokenizers>=0.20.1,<0.23",
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"sentencepiece>=0.2.0",
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"timm>=1.0.11",
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"peft>=0.15.0",
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"diffusers>=0.38.0",
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"torch==2.12.0",
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"torchvision",
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"torchaudio",
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# CUDA-only: no wheels for non-Linux platforms, and the sdist build shells
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# out to nvcc unconditionally. Gate on sys_platform so installs on macOS
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# (MPS) and other non-Linux platforms don't try to build it from source.
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"flashinfer-python; sys_platform == 'linux'",
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# Acceleration & Optimization
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"accelerate==1.0.1",
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# Computer Vision & Image Processing
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"opencv-python>=4.10.0.84",
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"pillow>=10.3.0",
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"imageio>=2.36.0",
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"imageio-ffmpeg>=0.5.1",
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"einops",
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# Experiment Tracking & Logging
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"wandb>=0.21.0",
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"loguru",
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"test-tube>=0.7.5",
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# Miscellaneous Utilities
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"tqdm",
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"pytest",
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"PyYAML>=6.0.1",
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"protobuf>=5.28.3",
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"gradio==5.32.0",
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"moviepy>=2.0.0",
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"flask",
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"flask_restful",
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"aiohttp",
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"aiofiles",
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"huggingface_hub",
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"cloudpickle",
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"omegaconf",
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# System & Monitoring Tools
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"gpustat",
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"watch",
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"remote-pdb",
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# Kernel & Packaging
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# CUDA-only: PyPI only publishes manylinux wheels, and the sdist build
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# requires nvcc via CMake. Gate on sys_platform so installs on macOS
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# (MPS) and other non-Linux platforms don't try to build it from source;
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# every fastvideo_kernel import elsewhere is already guarded to degrade
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# gracefully when the package is absent.
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"fastvideo-kernel==0.3.2; sys_platform == 'linux'",
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"wheel",
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# Training Dependencies
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"torchdata",
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"pyarrow",
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"datasets>=4.0.0",
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"av",
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# Preprocessing Dependencies
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"torchcodec",
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"ray>=2.49.1",
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"ftfy>=6.3.1",
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# Job Runner
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"fastapi>=0.129.0",
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"uvicorn>=0.41.0"
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]
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[tool.uv]
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prerelease = "allow"
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[tool.uv.workspace]
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members = ["apps/dreamverse"]
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[tool.uv.sources]
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# PyPI's aarch64 fastvideo-kernel wheels do not cover the NVIDIA DGX Spark /
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# GB10 (sm_121), so on ARM build from the in-tree source instead; x86_64 keeps
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# the published PyPI wheel. This table is uv-only: plain pip ignores it. Pass
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# --no-sources to bypass it (e.g. when the kernel is already installed, as in
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# the Spark install guide).
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fastvideo-kernel = [
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{ path = "fastvideo-kernel", marker = "platform_machine == 'aarch64'" },
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]
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# torch / torchvision / torchaudio are intentionally NOT pinned to a PyTorch
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# index here. Pick the supported build explicitly at install time:
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# UV_TORCH_BACKEND=cu126 uv pip install -e ".[dev]" # CUDA 12
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# UV_TORCH_BACKEND=cu130 uv pip install -e ".[dev]" # CUDA 13
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# uv reads UV_TORCH_BACKEND / --torch-backend (not a pyproject setting). The
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# supported backends (cu126, cu130) both provide torch 2.12.0.
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imagebind = { git = "https://github.com/facebookresearch/ImageBind.git", rev = "53680b02d7e37b19b124fa37bae4b6c98c38f5be" }
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# FA4 cute, pinned to a cutlass-4.5-compatible revision. torch.compile support
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# comes from FastVideo's own custom_op wrappers.
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flash-attn-4 = { git = "https://github.com/Dao-AILab/flash-attention.git", rev = "82d6441eec5d4dfec120153db2c0145ae855a083", subdirectory = "flash_attn/cute" }
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[project.optional-dependencies]
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# flash-attn: uv pip install flash-attn==2.8.1 --no-cache-dir --no-build-isolation
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swanlab = [
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"swanlab>=0.6.7",
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]
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lint = [
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"pre-commit==4.0.1",
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"types-aiofiles",
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"types-requests",
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]
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test = [
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"av",
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"pytorch-msssim>=1.0.0",
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"pytest",
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"pandas",
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"plotly",
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]
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# Eval extras. See fastvideo/eval/README.md for which install path
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# covers which metrics. detectron2 (vbench color/object_class/etc.) is
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# CUDA-version-pinned and not cleanly pip-installable — install it
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# separately as documented in the README. decord has no aarch64 wheels
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# (upstream effectively unmaintained); it's split into its own extra so
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# the main eval extras install on ARM systems too. eval/io/video.py has
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# a PyAV fallback that covers the video-decode path without decord. The
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# judge.* metrics (eval-judge) call a remote API and need a key, so they
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# are opt-in and intentionally kept out of the default [eval] set.
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eval-vbench = ["openai-clip", "pyiqa", "easydict"]
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eval-physics-iq = []
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eval-audio = ["jiwer", "librosa", "pyloudnorm", "hear21passt", "audiobox_aesthetics", "imagebind", "pytorchvideo"]
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eval-judge = ["google-genai"]
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eval = [
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# ptlflow>=0.4: get_model() takes ckpt_path (0.3 called it
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# pretrained_ckpt); unpinned, the resolver backtracked to 0.2.5.
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"lpips", "ptlflow>=0.4", "qwen-vl-utils",
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"fastvideo[eval-vbench]", "fastvideo[eval-physics-iq]",
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]
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eval-fast-decode = ["decord"]
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eval-full = ["fastvideo[eval]", "fastvideo[eval-audio]", "qwen-omni-utils"]
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dev = [ "fastvideo[lint]", "fastvideo[test]", ]
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prompt-safety = [
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"fasttext",
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]
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prompt-enhancer = [
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"httpx",
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]
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streaming = [
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"fastvideo[prompt-enhancer]",
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"fastvideo[prompt-safety]",
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"websockets",
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]
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dreamverse = [
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"uvicorn[standard]>=0.41.0",
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"cerebras-cloud-sdk",
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# PyPI forbids direct URL deps in published metadata; pin upstream cute via
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# [tool.uv.sources] above (same pattern as imagebind) so the wheel stays
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# publishable while uv workspace installs still get it.
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"flash-attn-4",
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"flashinfer-python",
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"openai>=1.40",
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]
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rocm = [
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"amdsmi",
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]
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[project.scripts]
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fastvideo = "fastvideo.entrypoints.cli.main:main"
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dreamverse-server = "dreamverse.server_entry:cli"
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dreamverse-mock-server = "dreamverse.mock_server:cli"
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[tool.setuptools.packages.find]
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where = [".", "apps/dreamverse"]
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include = ["fastvideo", "fastvideo.*", "dreamverse", "dreamverse.*"]
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exclude = ["dreamverse.tests*"]
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[tool.setuptools.package-data]
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dreamverse = ["prompts/*.md"]
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[tool.wheel]
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exclude = ["assets*", "docker*", "docs", "scripts*", "apps*"]
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[tool.pytest.ini_options]
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markers = [
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"gpu: requires real GPU + model weights; skip in CI",
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]
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[tool.mypy]
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warn_unused_configs = true
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ignore_missing_imports = true
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disallow_untyped_calls = true
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check_untyped_defs = true
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follow_imports = "silent"
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[tool.codespell]
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# ``*/_vendored/*`` matches upstream-provenance files vendored under any
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# ``_vendored/`` subdir (project-wide convention; mirrors the
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# ``_``-prefixed auto-discovery skip).
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skip = "./data,./wandb,apps/fastvideo_studio/package-lock.json,apps/performance_dashboard/frontend/package-lock.json,*/_vendored/*"
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# "tread" matches daVinci-MagiHuman's acronym "TReAD" (Token Routing and
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# Early Drop). codespell lowercases ignore-words entries, so the single
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# lowercase form silences all case variants.
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ignore-words-list = "tread,passt,dout"
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[tool.ruff]
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# Allow lines to be as long as 120.
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line-length = 120
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extend-exclude = [
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# Upstream submodules under fastvideo/third_party/ are not our style
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# territory; modern-dep compat lives as runtime shims in our metric
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# __init__.py files.
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"fastvideo/third_party/**",
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]
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[tool.ruff.lint]
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select = [
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# pycodestyle
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"E",
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# Pyflakes
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"F",
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# pyupgrade
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"UP",
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# flake8-bugbear
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"B",
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# flake8-simplify
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"SIM",
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# isort
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# "I",
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"G",
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]
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ignore = [
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# star imports
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"F405", "F403",
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# lambda expression assignment
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"E731",
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# Loop control variable not used within loop body
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"B007",
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# f-string format
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"UP032",
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# line too long
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"E501",
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]
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[tool.ruff.lint.per-file-ignores]
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# Ignore all files that end in `_test.py`.
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"fastvideo/models/hunyuan/diffusion/pipelines/pipeline_hunyuan_video.py" = ["E741"]
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[tool.yapf]
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column_limit = 120
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[tool.isort]
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line_length = 120
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use_parentheses = true
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skip_gitignore = true
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[project.urls]
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Repository = "https://github.com/hao-ai-lab/FastVideo"
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# Used by Comfy Registry https://comfyregistry.org
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[tool.comfy]
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PublisherId = "fastvideo"
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DisplayName = "FastVideo"
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Icon = "https://raw.githubusercontent.com/hao-ai-lab/FastVideo/main/comfyui/assets/icon_simple.svg"
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