Use CUDA installation scripts from pytorch/builder

pytorch · Jan 28, 2024 · 9c1f91d · 9c1f91d
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diff --git a/.github/workflows/build-gcp-docker.yml b/.github/workflows/build-gcp-docker.yml
@@ -28,7 +28,7 @@ jobs:
       - name: Build TorchBench Nightly GCP Base Docker
         run: |
           cd benchmark/docker
-          docker buildx build . \
+          docker build . \
               -f gcp-a100-runner-dind.dockerfile -t xzhao9/gcp-a100-runner-dind:latest
       - name: Push docker to remote
         if: ${{ env.WITH_PUSH == 'true' }}

diff --git a/docker/gcp-a100-runner-dind.dockerfile b/docker/gcp-a100-runner-dind.dockerfile
@@ -25,7 +25,7 @@ RUN sudo mkdir -p /workspace; sudo chown runner:runner /workspace
 # NVIDIA drivers list available at gs://ubuntu_nvidia_packages/
 # We assume that the host NVIDIA driver binaries and libraries are mapped to the docker filesystem
 
-# Source of the CUDA installation scripts:
+# Use the CUDA installation scripts from pytorch/builder
 RUN cd /workspace; git clone https://github.com/pytorch/builder.git
 RUN sudo bash -c 'source /workspace/builder/common/install_cuda.sh; install_118'
 RUN sudo bash -c 'source /workspace/builder/common/install_cuda.sh; install_121'