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builds for PyTorch 1.9
Summary: Build for pytorch 1.9, and make it the only mac build. Not testing on cuda 11.1, because of annoying failures which are restricted to certain hardware. Also update cuda driver in CI tests. Reviewed By: patricklabatut Differential Revision: D29302314 fbshipit-source-id: 78def378adb9d7aa287abdc5ac0af269e3ba3625
This commit is contained in:
Jeremy Reizenstein
Facebook GitHub Bot
parent
bbc12e70c4
commit
c639198c97
@ -177,8 +177,8 @@ jobs:
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sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION}
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sudo systemctl restart docker
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DRIVER_FN="NVIDIA-Linux-x86_64-450.80.02.run"
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wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/450.80.02/$DRIVER_FN"
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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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@ -238,10 +238,10 @@ workflows:
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pytorch_version: "1.4"
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cu_version: "cu101"
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- binary_linux_conda_cuda:
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name: testrun_conda_cuda_py37_cu102_pyt160
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name: testrun_conda_cuda_py37_cu102_pyt190
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context: DOCKERHUB_TOKEN
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python_version: "3.7"
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pytorch_version: '1.6.0'
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pytorch_version: '1.9.0'
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cu_version: "cu102"
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- binary_linux_conda_cuda:
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name: testrun_conda_cuda_py37_cu110_pyt170
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@ -259,19 +259,19 @@ workflows:
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cu_version: cpu
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name: macos_wheel_py36_cpu
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python_version: '3.6'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py37_cpu
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python_version: '3.7'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py38_cpu
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python_version: '3.8'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py39_cpu
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python_version: '3.9'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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@ -177,8 +177,8 @@ jobs:
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sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION}
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sudo systemctl restart docker
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DRIVER_FN="NVIDIA-Linux-x86_64-450.80.02.run"
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wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/450.80.02/$DRIVER_FN"
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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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@ -368,6 +368,18 @@ workflows:
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name: linux_conda_py36_cu111_pyt181
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python_version: '3.6'
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pytorch_version: 1.8.1
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu102
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name: linux_conda_py36_cu102_pyt190
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python_version: '3.6'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu111
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name: linux_conda_py36_cu111_pyt190
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python_version: '3.6'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu92
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@ -506,6 +518,18 @@ workflows:
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name: linux_conda_py37_cu111_pyt181
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python_version: '3.7'
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pytorch_version: 1.8.1
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu102
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name: linux_conda_py37_cu102_pyt190
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python_version: '3.7'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu111
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name: linux_conda_py37_cu111_pyt190
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python_version: '3.7'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu92
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@ -644,6 +668,18 @@ workflows:
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name: linux_conda_py38_cu111_pyt181
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python_version: '3.8'
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pytorch_version: 1.8.1
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu102
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name: linux_conda_py38_cu102_pyt190
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python_version: '3.8'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu111
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name: linux_conda_py38_cu111_pyt190
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python_version: '3.8'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu101
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@ -698,6 +734,18 @@ workflows:
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name: linux_conda_py39_cu111_pyt181
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python_version: '3.9'
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pytorch_version: 1.8.1
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu102
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name: linux_conda_py39_cu102_pyt190
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python_version: '3.9'
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pytorch_version: 1.9.0
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- binary_linux_conda:
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context: DOCKERHUB_TOKEN
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cu_version: cu111
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name: linux_conda_py39_cu111_pyt190
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python_version: '3.9'
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pytorch_version: 1.9.0
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- binary_linux_conda_cuda:
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name: testrun_conda_cuda_py36_cu101_pyt14
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context: DOCKERHUB_TOKEN
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@ -705,10 +753,10 @@ workflows:
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pytorch_version: "1.4"
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cu_version: "cu101"
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- binary_linux_conda_cuda:
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name: testrun_conda_cuda_py37_cu102_pyt160
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name: testrun_conda_cuda_py37_cu102_pyt190
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context: DOCKERHUB_TOKEN
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python_version: "3.7"
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pytorch_version: '1.6.0'
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pytorch_version: '1.9.0'
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cu_version: "cu102"
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- binary_linux_conda_cuda:
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name: testrun_conda_cuda_py37_cu110_pyt170
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@ -726,19 +774,19 @@ workflows:
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cu_version: cpu
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name: macos_wheel_py36_cpu
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python_version: '3.6'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py37_cpu
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python_version: '3.7'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py38_cpu
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python_version: '3.8'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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- binary_macos_wheel:
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cu_version: cpu
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name: macos_wheel_py39_cpu
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python_version: '3.9'
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pytorch_version: '1.7.1'
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pytorch_version: '1.9.0'
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@ -27,6 +27,7 @@ CONDA_CUDA_VERSIONS = {
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"1.7.1": ["cu101", "cu102", "cu110"],
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"1.8.0": ["cu101", "cu102", "cu111"],
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"1.8.1": ["cu101", "cu102", "cu111"],
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"1.9.0": ["cu102", "cu111"],
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}
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@ -23,8 +23,10 @@ CUB_HOME=$(realpath ./cub-1.10.0)
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export CUB_HOME
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echo "CUB_HOME is now $CUB_HOME"
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# As a rule, we want to build for any combination of dependencies which is supported by
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# PyTorch3D and not older than the current Google Colab set up.
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PYTHON_VERSIONS="3.6 3.7 3.8 3.9"
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PYTHON_VERSIONS="3.7 3.8 3.9"
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# the keys are pytorch versions
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declare -A CONDA_CUDA_VERSIONS=(
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# ["1.4.0"]="cu101"
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@ -33,8 +35,9 @@ declare -A CONDA_CUDA_VERSIONS=(
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# ["1.6.0"]="cu101 cu102"
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# ["1.7.0"]="cu101 cu102 cu110"
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# ["1.7.1"]="cu101 cu102 cu110"
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["1.8.0"]="cu101 cu102 cu111"
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["1.8.1"]="cu101 cu102 cu111"
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# ["1.8.0"]="cu101 cu102 cu111"
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# ["1.8.1"]="cu101 cu102 cu111"
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["1.9.0"]="cu102 cu111"
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)
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