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[WIP] Update project dependencies
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‎pyproject.toml‎

Lines changed: 122 additions & 3 deletions
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@@ -3,24 +3,142 @@ requires = [
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"setuptools>=77.0",
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"wheel>=0.45.1",
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"pip>=25.3",
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"pybind11==2.13.6",
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]
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build-backend = "setuptools.build_meta"
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[project]
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name = "flag_scale"
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version = "1.0.0"
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description = "FlagScale is a comprehensive toolkit designed to support the entire lifecycle of large models, developed with the backing of the Beijing Academy of Artificial Intelligence (BAAI)."
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description = "FlagScale is a comprehensive toolkit designed to support the entire lifecycle of large models."
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readme = "README.md"
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license = {text = "Apache-2.0"}
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license = { text = "Apache-2.0" }
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requires-python = ">=3.10"
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dynamic = ["dependencies"]
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dependencies = [
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"aiohttp==3.13.3", # Apache-2.0, MIT. Async HTTP framework.
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"click==8.3.1", # BSD-3. Command line processing.
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"compressed-tensors==0.13.0", # Apache-2.0. For compress tasks.
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"hydra-core==1.3.2", # MIT. Configuration management
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"llmcompressor==0.9.0", # Apache-2.0. LLM compressor for (post-)training.
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"numpy==2.4.1", # BSD-3. Array computing.
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"omegaconf==2.3.0", # BSD. Configuration library.
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"openai==2.15.0", # Apache-2.0. Official lib for OpenAI API.
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"Pillow==12.1.0", # MIT-CMU. Aka. 'PIL'. Image library.
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"PyYAML==6.0.3", # MIT. YAML processor. Aka. 'yaml'.
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"packaging==25.0", # Apache-2.0, BSD. Version parsing/comparison util.
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"psutil==7.2.1", # BSD-3. Process and system monitoring.
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"pydantic==2.12.5", # MIT. Data validation.
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"torch==2.9.1", # BSD-3. Tensor & DNN framework.
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"torchvision==0.24.1", # BSD. Image and video for Torch deep learning.
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"tqdm==4.67.1", # MIT. Progress meter.
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"transformers==4.57.6", # Apache-2.0.
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"webdataset==1.0.2", # BSD-3. Data storage and I/O.
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]
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[project.urls]
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Homepage = "https://github.com/flagos-ai/FlagScale"
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[project.scripts]
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flagscale = "flag_scale.flagscale.cli:flagscale"
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[project.optional-dependencies]
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training = [
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"accelerate==1.12.0", # Apache-2.0. PyTorch util for training loops.
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"av==16.1.0", # BSD-3. Video training.
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"datasets==4.5.0", # Apache-2.0. HuggingFace library for datasets.
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"deepspeed=0.18.4", # Apache-2.0. LLava-OneVision and checkpoint.
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"einops==0.8.1", # MIT. Deep learning operations.
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"fsspec==2026.1.0", # BSD-3. Filesystem specification used in video training tools.
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"huggingface-hub==1.3.2", # Apache-2.0. Client library for huggingface.co hub.
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"llava-torch==1.2.2.post1", # Apache-2.0. Visual instruction tuning.
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"nvidia-resiliency-ext==0.5.0", # Apache-2.0. NVIDIA resiliency extension.
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"pandas==2.3.3", # BSD. Data analysis package.
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"pyarrow==23.0.0", # Apache-2.0. Library for Apache Arrow.
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"pytorch_lightning==2.6.0", # Apache-2.0. PyTorch wrapper.
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"regex==2026.1.15", # Apache-2.0. Regular expression.
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"safetensors==0.7.0", # Apache-2.0. Model file processing.
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"sentencepiece==0.2.1", # Apache-2.0. Text tokenizer and detokenizer.
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"tiktoken==0.12.0", # MIT. BPE tokenizer for OpenAI models.
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"timm==1.0.24", # Apache-2.0. Image model, used in legacy training.
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"tokenizers==0.22.2", # Apache-2.0.
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"torchcodec==0.9.1", # BSD-3. Video decoder for PyTorch.
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"transformer-engine==2.11.0", # Apache-2.0.
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"wandb==0.24.0", # MIT. Weights & biases library.
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]
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training_addon = [
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# TODO(Qiming): Confirm that `accimage` is outdated and can be removed.
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# "accimage",
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"faiss==1.5.3", # BSD. Search and clustering of dense vectors, for megatron legacy.
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"flag_gems==4.2.0", # Apache-2.0.
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"flagcx==0.8.0", # Apache-2.0.
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"flash_attn==2.8.3", # BSD. Fast and memory-efficient exact attention.
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"flash_mla==1.0.0.dev0", # Unknown. Megatron qwen3 vision.
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"nvidia-modelopt=0.41.0", # Apache-2.0. Nvidia model optimizer.
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"peft==0.18.1", # Apache-2.0. Parameter-efficient fine-tuning lib.
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# TODO(Qiming): handle the `apex` dependency.
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# https://github.com/NVIDIA/apex # BSD-3. Mixed precision and distributed training.
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# TODO(Qiming): Check the 'flashattn_hopper' package referenced in
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# `flagscale/models/megatron/qwen3_vl/vision_attention.py`.
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]
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inference = [
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"diffusers==0.36.0", # Apache-2.0. Diffusion models for inference & training.
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"fastapi==0.128.0", # MIT. Web framework for serve mode run.
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"jsonlines==4.0.0", # BSD. Used by Aquila model only.
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"matplotlib==3.10.8", # Python Software Foundation License. Visualization for serving.
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"msgpack==1.1.2", # Apache-2.0. MessagePack serializer. Used for serving.
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"pynvml==13.0.1", # BSD-3. Utility for NVIDIA management library.
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"pyzmq==27.1.0", # BSD-3. Python binding for ZeroMQ. Aka. 'zmq'.
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"quart==0.20.0", # MIT. ASGI web framework.
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"ray==2.53.0", # Apache-2.0. Framework for distributed apps.
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"scikit_learn==1.8.0", # BSD-3. Aka. 'sklearn'. Machine learing and data mining, for visual serving.
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"scipy==1.17.0", # BSD. Fundamental algorithms, used in serve mode.
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"sglang==0.5.7", # Apache-2.0. Serving framework for LLM and VLM.
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"six==1.17.0", # MIT. Python 2 and 3 compatibility, used in tokernizer.
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"vllm==0.13.0", # Apache-2.0.
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]
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robotics = [
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"draccus==0.11.5", # MIT. Configuration management framework, for pi0, pi05.
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"epath==0.7", # MIT. Dynamic import partent files, used in robotrain.
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"Flask==3.1.2", # BSD-3. Web framework.
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"flask-cors==6.0.2", # MIT. Flask extension.
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"qwen_vl_utils==0.0.14", # Apache-2.0. Qwen vision language model utils - PyTorch.
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"redis==7.1.0", # MIT. Client library for Redis.
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"Requests==2.32.5", # Apache-2.0. HTTP library.
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"sentence-transformers==5.2.0", # Apache-2.0. Embedding, retrieval, reranking.
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"typing-extensions==4.15.0", # PSF-2.0. Type hints for Python 3.9+.
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# TODO(Qiming): handle the following case.
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# git+https://github.com/huggingface/transformers.git@fix/lerobot_openpi
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]
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lint = [
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"pre-commit>=4.2.0", # MIT. Pre-commit hook.
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# TODO(Qiming): Check if `black` is actually used.
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# "black==24.4.2", # MIT. Code formatter.
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# TODO(Qiming): Check if `black` is actually used.
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# "flake8==7.1.0", # MIT. Modular source code checker.
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"isort==5.13.2", # MIT. Sorting Python imports. Referenced by pre-commit.
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# TODO(Qiming): Determine if `pylint` should be removed.
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# "pylint==4.0.4", # GPL-2.0. Static checker.
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"ruff==0.14.13", # MIT. Linter and code formatter. Referenced by pre-commit.
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"typos==1.42.1", # MIT. Source code spelling checker.
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]
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test = [
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"pytest==9.0.2", # MIT. Testing framework.
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"pytest-mock==3.15.1", # MIT. Mock wrapper for pytest.
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# "pytest-asyncio==1.3.0", # Apache-2.0, usage pattern "@pytest.mark.asyncio"
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# "pytest-cov==7.0.0", # MIT, usage pattern "pytest --cov=foo dir/"
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# "coverage==7.13.1", #
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]
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util = [
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"modelscope==1.34.0", # Apache-2.0. ModelScope client, also used in pi0 example as library.
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]
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[tool.ruff]
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line-length = 100
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@@ -83,6 +201,7 @@ select = [
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"Q003",
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"Q004",
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]
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ignore = [
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"E402", # Module level import not at top of file
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"E501", # Line too long

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