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Use newer circleci image
Summary: Run the circleci tests with a non depracated circleci image. Small fix for PyTorch 1.7. We no longer need to manually install nvidia-docker or the CUDA driver. Reviewed By: patricklabatut Differential Revision: D34426816 fbshipit-source-id: d6c67bfb0ff86dff8d8f7fe7b8801657c2e80030
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@ -128,55 +128,15 @@ jobs:
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binary_linux_conda_cuda:
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binary_linux_conda_cuda:
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<<: *binary_common
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<<: *binary_common
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machine:
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machine:
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image: ubuntu-1604:201903-01
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image: ubuntu-1604-cuda-10.2:202012-01
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resource_class: gpu.nvidia.small.multi
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resource_class: gpu.nvidia.small.multi
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steps:
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steps:
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- checkout
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- checkout
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- run:
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name: Setup environment
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command: |
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set -e
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curl -L https://packagecloud.io/circleci/trusty/gpgkey | sudo apt-key add -
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curl -L https://dl.google.com/linux/linux_signing_key.pub | sudo apt-key add -
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sudo apt-get update
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sudo apt-get install \
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apt-transport-https \
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ca-certificates \
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curl \
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gnupg-agent \
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software-properties-common
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curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
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sudo add-apt-repository \
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"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
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$(lsb_release -cs) \
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stable"
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sudo apt-get update
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export DOCKER_VERSION="5:19.03.2~3-0~ubuntu-xenial"
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sudo apt-get install docker-ce=${DOCKER_VERSION} docker-ce-cli=${DOCKER_VERSION} containerd.io=1.2.6-3
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# Add the package repositories
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distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
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curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
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curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
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export NVIDIA_CONTAINER_VERSION="1.0.3-1"
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sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION}
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sudo systemctl restart docker
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DRIVER_FN="NVIDIA-Linux-x86_64-460.84.run"
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wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/460.84/$DRIVER_FN"
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sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
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nvidia-smi
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- run:
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- run:
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name: Pull docker image
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name: Pull docker image
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command: |
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command: |
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nvidia-smi
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set -e
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set -e
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{ docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
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{ docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
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@ -128,55 +128,15 @@ jobs:
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binary_linux_conda_cuda:
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binary_linux_conda_cuda:
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<<: *binary_common
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<<: *binary_common
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machine:
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machine:
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image: ubuntu-1604:201903-01
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image: ubuntu-1604-cuda-10.2:202012-01
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resource_class: gpu.nvidia.small.multi
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resource_class: gpu.nvidia.small.multi
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steps:
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steps:
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- checkout
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- checkout
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- run:
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name: Setup environment
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command: |
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set -e
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curl -L https://packagecloud.io/circleci/trusty/gpgkey | sudo apt-key add -
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curl -L https://dl.google.com/linux/linux_signing_key.pub | sudo apt-key add -
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sudo apt-get update
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sudo apt-get install \
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apt-transport-https \
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ca-certificates \
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curl \
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gnupg-agent \
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software-properties-common
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curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
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sudo add-apt-repository \
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"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
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$(lsb_release -cs) \
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stable"
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sudo apt-get update
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export DOCKER_VERSION="5:19.03.2~3-0~ubuntu-xenial"
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sudo apt-get install docker-ce=${DOCKER_VERSION} docker-ce-cli=${DOCKER_VERSION} containerd.io=1.2.6-3
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# Add the package repositories
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distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
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curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
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curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
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export NVIDIA_CONTAINER_VERSION="1.0.3-1"
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sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION}
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sudo systemctl restart docker
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DRIVER_FN="NVIDIA-Linux-x86_64-460.84.run"
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wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/460.84/$DRIVER_FN"
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sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
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nvidia-smi
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- run:
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- run:
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name: Pull docker image
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name: Pull docker image
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command: |
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command: |
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nvidia-smi
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set -e
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set -e
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{ docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
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{ docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
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