chore: import upstream snapshot with attribution
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FROM nvidia/cuda:12.6.0-cudnn-devel-ubuntu22.04
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LABEL maintainer="Hugging Face"
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ARG DEBIAN_FRONTEND=noninteractive
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# Use login shell to read variables from `~/.profile` (to pass dynamic created variables between RUN commands)
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SHELL ["sh", "-lc"]
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# The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
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# to be used as arguments for docker build (so far).
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ARG PYTORCH='2.8.0'
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# Example: `cu102`, `cu113`, etc.
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ARG CUDA='cu126'
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RUN apt update
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RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
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RUN python3 -m pip install --no-cache-dir --upgrade pip
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ARG REF=main
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RUN git clone https://github.com/huggingface/transformers && cd transformers && git checkout $REF
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RUN [ ${#PYTORCH} -gt 0 ] && VERSION='torch=='$PYTORCH'.*' || VERSION='torch'; echo "export VERSION='$VERSION'" >> ~/.profile
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RUN echo torch=$VERSION
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# `torchvision` and `torchaudio` should be installed along with `torch`, especially for nightly build.
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# Currently, let's just use their latest releases (when `torch` is installed with a release version)
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RUN python3 -m pip install --no-cache-dir -U $VERSION torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/$CUDA
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RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
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# Add optimum for gptq quantization testing
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RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/optimum@main#egg=optimum
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# Add PEFT
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RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/peft@main#egg=peft
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# needed in bnb and awq
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RUN python3 -m pip install --no-cache-dir einops
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# Add bitsandbytes
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RUN python3 -m pip install --no-cache-dir bitsandbytes
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# # Add gptqmodel
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# RUN python3 -m pip install --no-cache-dir gptqmodel
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# Add hqq for quantization testing
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RUN python3 -m pip install --no-cache-dir hqq
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# For GGUF tests
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RUN python3 -m pip install --no-cache-dir gguf
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# Add quanto for quantization testing
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RUN python3 -m pip install --no-cache-dir optimum-quanto
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# Add compressed-tensors for quantization testing
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RUN python3 -m pip install --no-cache-dir compressed-tensors
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# Add AMD Quark for quantization testing
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RUN python3 -m pip install --no-cache-dir amd-quark
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# Add AutoRound for quantization testing
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RUN python3 -m pip install --no-cache-dir auto-round
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# Add torchao for quantization testing
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RUN python3 -m pip install --no-cache-dir torchao
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# Add transformers in editable mode
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RUN python3 -m pip install --no-cache-dir -e ./transformers[dev]
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# `kernels` may give different outputs (within 1e-5 range) even with the same model (weights) and the same inputs
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RUN python3 -m pip uninstall -y kernels
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# Uninstall flash-attn installed by autoawq, it causes issues here : https://github.com/huggingface/transformers/actions/runs/15915442841/job/44892146131
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RUN python3 -m pip uninstall -y flash-attn
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# When installing in editable mode, `transformers` is not recognized as a package.
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# this line must be added in order for python to be aware of transformers.
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RUN cd transformers && python3 setup.py develop
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# Add fouroversix for quantization testing
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RUN python3 -m pip install --no-cache-dir --upgrade setuptools wheel
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RUN python3 -m pip install --no-cache-dir "fouroversix>=1.0.2" --no-build-isolation
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# Add fp-quant for quantization testing
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RUN python3 -m pip install --no-cache-dir "fp-quant>=0.3.2"
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# Low usage or incompatible lib, will enable later on
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# # Add aqlm for quantization testing
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# RUN python3 -m pip install --no-cache-dir aqlm[gpu]==1.0.2
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# # Add vptq for quantization testing
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# RUN pip install vptq
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# Add spqr for quantization testing
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# Commented for now as No matching distribution found we need to reach out to the authors
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# RUN python3 -m pip install --no-cache-dir spqr_quant[gpu]
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# # Add eetq for quantization testing
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# RUN git clone https://github.com/NetEase-FuXi/EETQ.git && cd EETQ/ && git submodule update --init --recursive && pip install .
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# # Add flute-kernel and fast_hadamard_transform for quantization testing
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# # Commented for now as they cause issues with the build
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# # TODO: create a new workflow to test them
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# RUN python3 -m pip install --no-cache-dir flute-kernel==0.4.1
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# RUN python3 -m pip install --no-cache-dir git+https://github.com/Dao-AILab/fast-hadamard-transform.git
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