From c639198c97467a88008ce71a4a641cb63d92f701 Mon Sep 17 00:00:00 2001 From: Jeremy Reizenstein Date: Tue, 22 Jun 2021 12:38:36 -0700 Subject: [PATCH] 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 --- .circleci/config.in.yml | 16 ++++---- .circleci/config.yml | 64 ++++++++++++++++++++++++++++---- .circleci/regenerate.py | 1 + packaging/linux_wheels/inside.sh | 9 +++-- 4 files changed, 71 insertions(+), 19 deletions(-) diff --git a/.circleci/config.in.yml b/.circleci/config.in.yml index 5458de3a..1616d277 100644 --- a/.circleci/config.in.yml +++ b/.circleci/config.in.yml @@ -177,8 +177,8 @@ jobs: sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION} sudo systemctl restart docker - DRIVER_FN="NVIDIA-Linux-x86_64-450.80.02.run" - wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/450.80.02/$DRIVER_FN" + DRIVER_FN="NVIDIA-Linux-x86_64-460.84.run" + wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/460.84/$DRIVER_FN" sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false) nvidia-smi @@ -238,10 +238,10 @@ workflows: pytorch_version: "1.4" cu_version: "cu101" - binary_linux_conda_cuda: - name: testrun_conda_cuda_py37_cu102_pyt160 + name: testrun_conda_cuda_py37_cu102_pyt190 context: DOCKERHUB_TOKEN python_version: "3.7" - pytorch_version: '1.6.0' + pytorch_version: '1.9.0' cu_version: "cu102" - binary_linux_conda_cuda: name: testrun_conda_cuda_py37_cu110_pyt170 @@ -259,19 +259,19 @@ workflows: cu_version: cpu name: macos_wheel_py36_cpu python_version: '3.6' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py37_cpu python_version: '3.7' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py38_cpu python_version: '3.8' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py39_cpu python_version: '3.9' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' diff --git a/.circleci/config.yml b/.circleci/config.yml index 085ebcf3..956922e6 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -177,8 +177,8 @@ jobs: sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION} sudo systemctl restart docker - DRIVER_FN="NVIDIA-Linux-x86_64-450.80.02.run" - wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/450.80.02/$DRIVER_FN" + DRIVER_FN="NVIDIA-Linux-x86_64-460.84.run" + wget "https://us.download.nvidia.com/XFree86/Linux-x86_64/460.84/$DRIVER_FN" sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false) nvidia-smi @@ -368,6 +368,18 @@ workflows: name: linux_conda_py36_cu111_pyt181 python_version: '3.6' pytorch_version: 1.8.1 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu102 + name: linux_conda_py36_cu102_pyt190 + python_version: '3.6' + pytorch_version: 1.9.0 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu111 + name: linux_conda_py36_cu111_pyt190 + python_version: '3.6' + pytorch_version: 1.9.0 - binary_linux_conda: context: DOCKERHUB_TOKEN cu_version: cu92 @@ -506,6 +518,18 @@ workflows: name: linux_conda_py37_cu111_pyt181 python_version: '3.7' pytorch_version: 1.8.1 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu102 + name: linux_conda_py37_cu102_pyt190 + python_version: '3.7' + pytorch_version: 1.9.0 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu111 + name: linux_conda_py37_cu111_pyt190 + python_version: '3.7' + pytorch_version: 1.9.0 - binary_linux_conda: context: DOCKERHUB_TOKEN cu_version: cu92 @@ -644,6 +668,18 @@ workflows: name: linux_conda_py38_cu111_pyt181 python_version: '3.8' pytorch_version: 1.8.1 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu102 + name: linux_conda_py38_cu102_pyt190 + python_version: '3.8' + pytorch_version: 1.9.0 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu111 + name: linux_conda_py38_cu111_pyt190 + python_version: '3.8' + pytorch_version: 1.9.0 - binary_linux_conda: context: DOCKERHUB_TOKEN cu_version: cu101 @@ -698,6 +734,18 @@ workflows: name: linux_conda_py39_cu111_pyt181 python_version: '3.9' pytorch_version: 1.8.1 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu102 + name: linux_conda_py39_cu102_pyt190 + python_version: '3.9' + pytorch_version: 1.9.0 + - binary_linux_conda: + context: DOCKERHUB_TOKEN + cu_version: cu111 + name: linux_conda_py39_cu111_pyt190 + python_version: '3.9' + pytorch_version: 1.9.0 - binary_linux_conda_cuda: name: testrun_conda_cuda_py36_cu101_pyt14 context: DOCKERHUB_TOKEN @@ -705,10 +753,10 @@ workflows: pytorch_version: "1.4" cu_version: "cu101" - binary_linux_conda_cuda: - name: testrun_conda_cuda_py37_cu102_pyt160 + name: testrun_conda_cuda_py37_cu102_pyt190 context: DOCKERHUB_TOKEN python_version: "3.7" - pytorch_version: '1.6.0' + pytorch_version: '1.9.0' cu_version: "cu102" - binary_linux_conda_cuda: name: testrun_conda_cuda_py37_cu110_pyt170 @@ -726,19 +774,19 @@ workflows: cu_version: cpu name: macos_wheel_py36_cpu python_version: '3.6' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py37_cpu python_version: '3.7' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py38_cpu python_version: '3.8' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' - binary_macos_wheel: cu_version: cpu name: macos_wheel_py39_cpu python_version: '3.9' - pytorch_version: '1.7.1' + pytorch_version: '1.9.0' diff --git a/.circleci/regenerate.py b/.circleci/regenerate.py index 7781ba0b..d313ccef 100755 --- a/.circleci/regenerate.py +++ b/.circleci/regenerate.py @@ -27,6 +27,7 @@ CONDA_CUDA_VERSIONS = { "1.7.1": ["cu101", "cu102", "cu110"], "1.8.0": ["cu101", "cu102", "cu111"], "1.8.1": ["cu101", "cu102", "cu111"], + "1.9.0": ["cu102", "cu111"], } diff --git a/packaging/linux_wheels/inside.sh b/packaging/linux_wheels/inside.sh index 47c54c9b..ba8a16b6 100644 --- a/packaging/linux_wheels/inside.sh +++ b/packaging/linux_wheels/inside.sh @@ -23,8 +23,10 @@ CUB_HOME=$(realpath ./cub-1.10.0) export CUB_HOME echo "CUB_HOME is now $CUB_HOME" +# As a rule, we want to build for any combination of dependencies which is supported by +# PyTorch3D and not older than the current Google Colab set up. -PYTHON_VERSIONS="3.6 3.7 3.8 3.9" +PYTHON_VERSIONS="3.7 3.8 3.9" # the keys are pytorch versions declare -A CONDA_CUDA_VERSIONS=( # ["1.4.0"]="cu101" @@ -33,8 +35,9 @@ declare -A CONDA_CUDA_VERSIONS=( # ["1.6.0"]="cu101 cu102" # ["1.7.0"]="cu101 cu102 cu110" # ["1.7.1"]="cu101 cu102 cu110" - ["1.8.0"]="cu101 cu102 cu111" - ["1.8.1"]="cu101 cu102 cu111" +# ["1.8.0"]="cu101 cu102 cu111" +# ["1.8.1"]="cu101 cu102 cu111" + ["1.9.0"]="cu102 cu111" )