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Upgrading torch version and cuda version in quantization docker (#36264)

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* update

* small update

* no spqr quant

* testing

* testing

* test nightly

* gptqmodel

* flute

* fix hadamard

* running tests

* new docker

* fix docker

* run tests

* testing new docker

* new docker

* run tests

* new docker

* run tests

* final test

* update

* update

* run tests

* new docker

* launch tests

* test_docker

* running tests

* add comments

* fixing yml

* revert
This commit is contained in:
Mohamed Mekkouri 2025-03-13 12:39:16 +01:00 committed by GitHub
parent 87b30c3589
commit 65b8e38aac
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1 changed files with 20 additions and 17 deletions
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37
docker/transformers-quantization-latest-gpu/Dockerfile
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@ -1,4 +1,4 @@
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
FROM nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -9,9 +9,9 @@ SHELL ["sh", "-lc"]
# The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
# to be used as arguments for docker build (so far).
ARG PYTORCH='2.5.1'
ARG PYTORCH='2.6.0'
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu118'
ARG CUDA='cu121'
RUN apt update
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
@ -26,8 +26,6 @@ RUN echo torch=$VERSION
# Currently, let's just use their latest releases (when `torch` is installed with a release version)
RUN python3 -m pip install --no-cache-dir -U $VERSION torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/$CUDA
RUN python3 -m pip install --no-cache-dir -e ./transformers[dev-torch]
RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
# needed in bnb and awq
@ -36,10 +34,9 @@ RUN python3 -m pip install --no-cache-dir einops
# Add bitsandbytes for mixed int8 testing
RUN python3 -m pip install --no-cache-dir bitsandbytes
# Add auto-gptq for gtpq quantization testing, installed from source for pytorch==2.5.1 compatibility
# TORCH_CUDA_ARCH_LIST="7.5+PTX" is added to make the package compile for Tesla T4 gpus available for the CI.
RUN pip install gekko
RUN git clone https://github.com/PanQiWei/AutoGPTQ.git && cd AutoGPTQ && TORCH_CUDA_ARCH_LIST="7.5+PTX" python3 setup.py install
# Add gptqmodel for gtpq quantization testing, installed from source for pytorch==2.6.0 compatibility
RUN python3 -m pip install lm_eval
RUN git clone https://github.com/ModelCloud/GPTQModel.git && cd GPTQModel && pip install -v . --no-build-isolation
# Add optimum for gptq quantization testing
RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/optimum@main#egg=optimum
@ -51,10 +48,11 @@ RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/pef
RUN python3 -m pip install --no-cache-dir aqlm[gpu]==1.0.2
# Add vptq for quantization testing
RUN python3 -m pip install --no-cache-dir vptq
RUN pip install vptq
# Add spqr for quantization testing
RUN python3 -m pip install --no-cache-dir spqr_quant[gpu]
# Commented for now as No matching distribution found we need to reach out to the authors
# RUN python3 -m pip install --no-cache-dir spqr_quant[gpu]
# Add hqq for quantization testing
RUN python3 -m pip install --no-cache-dir hqq
@ -63,22 +61,27 @@ RUN python3 -m pip install --no-cache-dir hqq
RUN python3 -m pip install --no-cache-dir gguf
# Add autoawq for quantization testing
# >=v0.2.7 needed for compatibility with transformers > 4.46
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
# New release v0.2.8
RUN python3 -m pip install --no-cache-dir autoawq[kernels]
# Add quanto for quantization testing
RUN python3 -m pip install --no-cache-dir optimum-quanto
# Add eetq for quantization testing
RUN python3 -m pip install git+https://github.com/NetEase-FuXi/EETQ.git
RUN git clone https://github.com/NetEase-FuXi/EETQ.git && cd EETQ/ && git submodule update --init --recursive && pip install .
# Add flute-kernel and fast_hadamard_transform for quantization testing
RUN python3 -m pip install --no-cache-dir flute-kernel==0.3.0 -i https://flute-ai.github.io/whl/cu118
RUN python3 -m pip install --no-cache-dir fast_hadamard_transform==1.0.4.post1
# # Add flute-kernel and fast_hadamard_transform for quantization testing
# # Commented for now as they cause issues with the build
# # TODO: create a new workflow to test them
# RUN python3 -m pip install --no-cache-dir flute-kernel==0.4.1
# RUN python3 -m pip install --no-cache-dir git+https://github.com/Dao-AILab/fast-hadamard-transform.git
# Add compressed-tensors for quantization testing
RUN python3 -m pip install --no-cache-dir compressed-tensors
# Add transformers in editable mode
RUN python3 -m pip install --no-cache-dir -e ./transformers[dev-torch]
# When installing in editable mode, `transformers` is not recognized as a package.
# this line must be added in order for python to be aware of transformers.
RUN cd transformers && python3 setup.py develop