mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-13 17:48:22 +06:00
64c05eecd6
* higgs init * working with crunches * per-model workspaces * style * style 2 * tests and style * higgs tests passing * protecting torch import * removed torch.Tensor type annotations * torch.nn.Module inheritance fix maybe * hide inputs inside quantizer calls * style structure something * Update src/transformers/quantizers/quantizer_higgs.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * reworked num_sms * Update src/transformers/integrations/higgs.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * revamped device checks * docstring upd * Update src/transformers/quantizers/quantizer_higgs.py Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> * edited tests and device map assertions * minor edits * updated flute cuda version in docker * Added p=1 and 2,3bit HIGGS * flute version check update * incorporated `modules_to_not_convert` * less hardcoding * Fixed comment * Added docs * Fixed gemma support * example in docs * fixed torch_dtype for HIGGS * Update docs/source/en/quantization/higgs.md Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Collection link * dequantize interface * newer flute version, torch.compile support * unittest message fix * docs update compile * isort * ValueError instead of assert --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
79 lines
3.4 KiB
Docker
Executable File
79 lines
3.4 KiB
Docker
Executable File
FROM nvidia/cuda:11.8.0-cudnn8-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='2.5.1'
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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 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 -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, installed from source for pytorch==2.5.1 compatibility
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# TORCH_CUDA_ARCH_LIST="7.5+PTX" is added to make the package compile for Tesla T4 gpus available for the CI.
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RUN pip install gekko
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RUN git clone https://github.com/PanQiWei/AutoGPTQ.git && cd AutoGPTQ && TORCH_CUDA_ARCH_LIST="7.5+PTX" python3 setup.py install
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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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# 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 python3 -m pip install --no-cache-dir vptq
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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 autoawq for quantization testing
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# >=v0.2.7 needed for compatibility with transformers > 4.46
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RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.7.post2/autoawq-0.2.7.post2-py3-none-any.whl
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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 eetq for quantization testing
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RUN python3 -m pip install git+https://github.com/NetEase-FuXi/EETQ.git
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# Add flute-kernel and fast_hadamard_transform for quantization testing
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RUN python3 -m pip install --no-cache-dir flute-kernel==0.3.0 -i https://flute-ai.github.io/whl/cu118
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RUN python3 -m pip install --no-cache-dir fast_hadamard_transform==1.0.4.post1
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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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