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

@@ -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'

.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'

.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"],
 }
 
 

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"
 )