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Use nvidia/cuda:CUDA_VERSION-devel-ubuntu22.04 as base for official Docker release (#125770)
We don't need to install cudnn system wide. We already install it with pytorch install during this step: ``` [conda-installs 2/3] RUN case linux/amd64 in "linux/arm64") pip install --extra-index-url https://download.pytorch.org/whl/cpu/ torch torchvision torchaudio ;; *) /opt/conda/bin/conda install -c "pytorch-nightly" -c "nvidia" -y "python=3.10" pytorch torchvision torchaudio "pytorch-cuda=$(echo 12.1.1 | cut -d'.' -f 1-2)" ;; esac && /opt/conda/bin/conda clean -ya ``` Ref: https://github.com/pytorch/pytorch/actions/runs/8998055687/job/24717424912 Validate via: https://github.com/pytorch/builder/actions/workflows/validate_docker_images.yml Pull Request resolved: https://github.com/pytorch/pytorch/pull/125770 Approved by: https://github.com/nWEIdia, https://github.com/seemethere
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@ -12,7 +12,7 @@ CUDA_VERSION_SHORT ?= 12.1
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CUDA_VERSION ?= 12.1.1
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CUDNN_VERSION ?= 8
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BASE_RUNTIME = ubuntu:22.04
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BASE_DEVEL = nvidia/cuda:$(CUDA_VERSION)-cudnn$(CUDNN_VERSION)-devel-ubuntu22.04
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BASE_DEVEL = nvidia/cuda:$(CUDA_VERSION)-devel-ubuntu22.04
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CMAKE_VARS ?=
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# The conda channel to use to install cudatoolkit
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