CI fixes (#1676)

Summary:
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1676

Remove CUDA 10.2 build, remove sm35 from cuda12.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D50790929

fbshipit-source-id: 2b8cd34493b633a97b4066e0fd61aff077f7ce0c

.circleci/config.in.yml

@@ -64,7 +64,7 @@ jobs:
       CUDA_VERSION: "11.3"
     resource_class: gpu.nvidia.small.multi
     machine:
-      image: ubuntu-2004:202101-01
+      image: linux-cuda-11:default
     steps:
       - checkout
       - <<: *setupcuda
@@ -116,7 +116,7 @@ jobs:
       # so we aren't running the tests.
       - run:
           name: build
-          no_output_timeout: 20m
+          no_output_timeout: 40m
           command: MAX_JOBS=15 TEST_FLAG=--no-test python3 packaging/build_conda.py
       - store_artifacts:
           path: /opt/conda/conda-bld/linux-64
@@ -128,7 +128,7 @@ jobs:
   binary_linux_conda_cuda:
     <<: *binary_common
     machine:
-      image: ubuntu-1604-cuda-10.2:202012-01
+      image: linux-cuda-11:default
     resource_class: gpu.nvidia.small.multi
     steps:
     - checkout
@@ -145,7 +145,7 @@ jobs:
           docker pull $TESTRUN_DOCKER_IMAGE
     - run:
         name: Build and run tests
-        no_output_timeout: 20m
+        no_output_timeout: 40m
         command: |
           set -e
 
@@ -164,8 +164,8 @@ workflows:
       #     context: DOCKERHUB_TOKEN
       {{workflows()}}
       - binary_linux_conda_cuda:
-          name: testrun_conda_cuda_py38_cu102_pyt190
+          name: testrun_conda_cuda_py310_cu117_pyt201
           context: DOCKERHUB_TOKEN
-          python_version: "3.8"
-          pytorch_version: '1.9.0'
-          cu_version: "cu102"
+          python_version: "3.10"
+          pytorch_version: '2.0.1'
+          cu_version: "cu117"

.circleci/config.yml

@@ -64,7 +64,7 @@ jobs:
       CUDA_VERSION: "11.3"
     resource_class: gpu.nvidia.small.multi
     machine:
-      image: ubuntu-2004:202101-01
+      image: linux-cuda-11:default
     steps:
       - checkout
       - <<: *setupcuda
@@ -116,7 +116,7 @@ jobs:
       # so we aren't running the tests.
       - run:
           name: build
-          no_output_timeout: 20m
+          no_output_timeout: 40m
           command: MAX_JOBS=15 TEST_FLAG=--no-test python3 packaging/build_conda.py
       - store_artifacts:
           path: /opt/conda/conda-bld/linux-64
@@ -128,7 +128,7 @@ jobs:
   binary_linux_conda_cuda:
     <<: *binary_common
     machine:
-      image: ubuntu-1604-cuda-10.2:202012-01
+      image: linux-cuda-11:default
     resource_class: gpu.nvidia.small.multi
     steps:
     - checkout
@@ -145,7 +145,7 @@ jobs:
           docker pull $TESTRUN_DOCKER_IMAGE
     - run:
         name: Build and run tests
-        no_output_timeout: 20m
+        no_output_timeout: 40m
         command: |
           set -e
 
@@ -162,12 +162,6 @@ workflows:
     jobs:
       # - main:
       #     context: DOCKERHUB_TOKEN
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1120
-          python_version: '3.8'
-          pytorch_version: 1.12.0
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -182,12 +176,6 @@ workflows:
           name: linux_conda_py38_cu116_pyt1120
           python_version: '3.8'
           pytorch_version: 1.12.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py38_cu102_pyt1121
-          python_version: '3.8'
-          pytorch_version: 1.12.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -272,12 +260,6 @@ workflows:
           name: linux_conda_py38_cu121_pyt210
           python_version: '3.8'
           pytorch_version: 2.1.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py39_cu102_pyt1120
-          python_version: '3.9'
-          pytorch_version: 1.12.0
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -292,12 +274,6 @@ workflows:
           name: linux_conda_py39_cu116_pyt1120
           python_version: '3.9'
           pytorch_version: 1.12.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py39_cu102_pyt1121
-          python_version: '3.9'
-          pytorch_version: 1.12.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -382,12 +358,6 @@ workflows:
           name: linux_conda_py39_cu121_pyt210
           python_version: '3.9'
           pytorch_version: 2.1.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py310_cu102_pyt1120
-          python_version: '3.10'
-          pytorch_version: 1.12.0
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -402,12 +372,6 @@ workflows:
           name: linux_conda_py310_cu116_pyt1120
           python_version: '3.10'
           pytorch_version: 1.12.0
-      - binary_linux_conda:
-          context: DOCKERHUB_TOKEN
-          cu_version: cu102
-          name: linux_conda_py310_cu102_pyt1121
-          python_version: '3.10'
-          pytorch_version: 1.12.1
       - binary_linux_conda:
           conda_docker_image: pytorch/conda-builder:cuda113
           context: DOCKERHUB_TOKEN
@@ -507,8 +471,8 @@ workflows:
           python_version: '3.11'
           pytorch_version: 2.1.0
       - binary_linux_conda_cuda:
-          name: testrun_conda_cuda_py38_cu102_pyt190
+          name: testrun_conda_cuda_py310_cu117_pyt201
           context: DOCKERHUB_TOKEN
-          python_version: "3.8"
-          pytorch_version: '1.9.0'
-          cu_version: "cu102"
+          python_version: "3.10"
+          pytorch_version: '2.0.1'
+          cu_version: "cu117"

.circleci/regenerate.py

@@ -18,10 +18,9 @@ from packaging import version
 
 # The CUDA versions which have pytorch conda packages available for linux for each
 # version of pytorch.
-# Pytorch 1.4 also supports cuda 10.0 but we no longer build for cuda 10.0 at all.
 CONDA_CUDA_VERSIONS = {
-    "1.12.0": ["cu102", "cu113", "cu116"],
-    "1.12.1": ["cu102", "cu113", "cu116"],
+    "1.12.0": ["cu113", "cu116"],
+    "1.12.1": ["cu113", "cu116"],
     "1.13.0": ["cu116", "cu117"],
     "1.13.1": ["cu116", "cu117"],
     "2.0.0": ["cu117", "cu118"],

packaging/build_conda.py

@@ -50,7 +50,6 @@ def setup_cuda():
     os.environ["FORCE_CUDA"] = "1"
 
     basic_nvcc_flags = (
-        "-gencode=arch=compute_35,code=sm_35 "
         "-gencode=arch=compute_50,code=sm_50 "
         "-gencode=arch=compute_60,code=sm_60 "
         "-gencode=arch=compute_70,code=sm_70 "
@@ -58,10 +57,11 @@ def setup_cuda():
         "-gencode=arch=compute_50,code=compute_50"
     )
     if CU_VERSION == "cu102":
-        nvcc_flags = basic_nvcc_flags
+        nvcc_flags = "-gencode=arch=compute_35,code=sm_35 " + basic_nvcc_flags
     elif CU_VERSION < ("cu118"):
         nvcc_flags = (
-            "-gencode=arch=compute_80,code=sm_80 "
+            "-gencode=arch=compute_35,code=sm_35 "
+            + "-gencode=arch=compute_80,code=sm_80 "
             + "-gencode=arch=compute_86,code=sm_86 "
             + basic_nvcc_flags
         )