mirror of
https://github.com/saymrwulf/transformers.git
synced 2026-05-14 20:58:08 +00:00
58a939c6b7
* revert back to torch 2.1.1 * run test * switch to torch 2.2.1 * udapte dockerfile * fix awq tests * fix test * run quanto tests * update tests * split quantization tests * fix * fix again * final fix * fix report artifact * build docker again * Revert "build docker again" This reverts commit 399a5f9d9308da071d79034f238c719de0f3532e. * debug * revert * style * new notification system * testing notfication * rebuild docker * fix_prev_ci_results * typo * remove warning * fix typo * fix artifact name * debug * issue fixed * debug again * fix * fix time * test notif with faling test * typo * issues again * final fix ? * run all quantization tests again * remove name to clear space * revert modfiication done on workflow * fix * build docker * build only quant docker * fix quantization ci * fix * fix report * better quantization_matrix * add print * revert to the basic one
57 lines
No EOL
2.5 KiB
Docker
57 lines
No EOL
2.5 KiB
Docker
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
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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='2.2.1'
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# Example: `cu102`, `cu113`, etc.
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ARG CUDA='cu118'
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RUN apt update
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RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python 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 -e ./transformers[dev-torch]
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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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# needed in bnb and awq
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RUN python3 -m pip install --no-cache-dir einops
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# Add bitsandbytes for mixed int8 testing
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RUN python3 -m pip install --no-cache-dir bitsandbytes
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# Add auto-gptq for gtpq quantization testing
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RUN python3 -m pip install --no-cache-dir auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
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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 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 autoawq for quantization testing
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# >=v0.2.3 needed for compatibility with torch 2.2.1
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RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp38-cp38-linux_x86_64.whl
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# Add quanto for quantization testing
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RUN python3 -m pip install --no-cache-dir quanto
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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 |