CI fixes

Summary: Update `main` build to latest CircleCI image - Ubuntu 2020.04. Avoid torch.logical_or and logical_and for PyTorch 1.4 compatibility. Also speed up the test run with Pytorch 1.4.0 (which has no ninja) by not setting NVCC_FLAGS for it. Reviewed By: theschnitz Differential Revision: D27262327 fbshipit-source-id: ddc359d134b1dc755f8b20bd3f33bb080cb3a0e1
facebookresearch · Mar 23, 2021 · cc08c6b · cc08c6b
1 parent 6c4151a
commit cc08c6b
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Showing 7 changed files with 40 additions and 23 deletions.
diff --git a/.circleci/check.sh b/.circleci/check.sh
@@ -3,4 +3,7 @@
 
 # Run this script before committing config.yml to verify it is valid yaml.
 
-python -c 'import yaml; yaml.safe_load(open("config.yml"))' && echo OK
+python -c 'import yaml; yaml.safe_load(open("config.yml"))' && echo OK - valid yaml
+
+msg="circleci not installed so can't check schema"
+command -v circleci > /dev/null && (cd ..; circleci config validate) || echo "$msg"
diff --git a/.circleci/config.in.yml b/.circleci/config.in.yml
@@ -18,12 +18,12 @@ setupcuda: &setupcuda
     working_directory: ~/
     command: |
       # download and install nvidia drivers, cuda, etc
-      wget --no-verbose --no-clobber -P ~/nvidia-downloads http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda_10.2.89_440.33.01_linux.run
-      sudo sh ~/nvidia-downloads/cuda_10.2.89_440.33.01_linux.run --silent
+      wget --no-verbose --no-clobber -P ~/nvidia-downloads https://developer.download.nvidia.com/compute/cuda/11.2.2/local_installers/cuda_11.2.2_460.32.03_linux.run
+      sudo sh ~/nvidia-downloads/cuda_11.2.2_460.32.03_linux.run --silent
       echo "Done installing CUDA."
       pyenv versions
       nvidia-smi
-      pyenv global 3.7.0
+      pyenv global 3.9.1
 
 gpu: &gpu
   environment:
@@ -64,7 +64,7 @@ jobs:
   main:
     <<: *gpu
     machine:
-      image: ubuntu-1604:201903-01
+      image: ubuntu-2004:202101-01
     steps:
       - checkout
       - <<: *setupcuda
@@ -86,10 +86,10 @@ jobs:
       - run:
           name: build
           command: |
-            export LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-10.2/lib64
+            export LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-11.2/lib64
             export CUB_HOME=$(realpath ../cub-1.10.0)
             python3 setup.py build_ext --inplace
-      - run: LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-10.2/lib64 python -m unittest discover -v -s tests
+      - run: LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-11.2/lib64 python -m unittest discover -v -s tests
       - run: python3 setup.py bdist_wheel
 
   binary_linux_wheel:
@@ -186,7 +186,7 @@ jobs:
 
           { docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
 
-          export DOCKER_IMAGE=pytorch/conda-cuda
+          DOCKER_IMAGE=pytorch/conda-cuda
           echo Pulling docker image $DOCKER_IMAGE
           docker pull $DOCKER_IMAGE
     - run:
@@ -196,8 +196,9 @@ jobs:
 
           cd ${HOME}/project/
 
-          export DOCKER_IMAGE=pytorch/conda-cuda
-          export VARS_TO_PASS="-e PYTHON_VERSION -e BUILD_VERSION -e PYTORCH_VERSION -e CU_VERSION"
+          DOCKER_IMAGE=pytorch/conda-cuda
+          export JUST_TESTRUN=1
+          VARS_TO_PASS="-e PYTHON_VERSION -e BUILD_VERSION -e PYTORCH_VERSION -e CU_VERSION -e JUST_TESTRUN"
 
           docker run --gpus all  --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${DOCKER_IMAGE} ./packaging/build_conda.sh
 

diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -18,12 +18,12 @@ setupcuda: &setupcuda
     working_directory: ~/
     command: |
       # download and install nvidia drivers, cuda, etc
-      wget --no-verbose --no-clobber -P ~/nvidia-downloads http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda_10.2.89_440.33.01_linux.run
-      sudo sh ~/nvidia-downloads/cuda_10.2.89_440.33.01_linux.run --silent
+      wget --no-verbose --no-clobber -P ~/nvidia-downloads https://developer.download.nvidia.com/compute/cuda/11.2.2/local_installers/cuda_11.2.2_460.32.03_linux.run
+      sudo sh ~/nvidia-downloads/cuda_11.2.2_460.32.03_linux.run --silent
       echo "Done installing CUDA."
       pyenv versions
       nvidia-smi
-      pyenv global 3.7.0
+      pyenv global 3.9.1
 
 gpu: &gpu
   environment:
@@ -64,7 +64,7 @@ jobs:
   main:
     <<: *gpu
     machine:
-      image: ubuntu-1604:201903-01
+      image: ubuntu-2004:202101-01
     steps:
       - checkout
       - <<: *setupcuda
@@ -86,10 +86,10 @@ jobs:
       - run:
           name: build
           command: |
-            export LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-10.2/lib64
+            export LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-11.2/lib64
             export CUB_HOME=$(realpath ../cub-1.10.0)
             python3 setup.py build_ext --inplace
-      - run: LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-10.2/lib64 python -m unittest discover -v -s tests
+      - run: LD_LIBRARY_PATH=$LD_LIBARY_PATH:/usr/local/cuda-11.2/lib64 python -m unittest discover -v -s tests
       - run: python3 setup.py bdist_wheel
 
   binary_linux_wheel:
@@ -186,7 +186,7 @@ jobs:
 
           { docker login -u="$DOCKERHUB_USERNAME" -p="$DOCKERHUB_TOKEN" ; } 2> /dev/null
 
-          export DOCKER_IMAGE=pytorch/conda-cuda
+          DOCKER_IMAGE=pytorch/conda-cuda
           echo Pulling docker image $DOCKER_IMAGE
           docker pull $DOCKER_IMAGE
     - run:
@@ -196,8 +196,9 @@ jobs:
 
           cd ${HOME}/project/
 
-          export DOCKER_IMAGE=pytorch/conda-cuda
-          export VARS_TO_PASS="-e PYTHON_VERSION -e BUILD_VERSION -e PYTORCH_VERSION -e CU_VERSION"
+          DOCKER_IMAGE=pytorch/conda-cuda
+          export JUST_TESTRUN=1
+          VARS_TO_PASS="-e PYTHON_VERSION -e BUILD_VERSION -e PYTORCH_VERSION -e CU_VERSION -e JUST_TESTRUN"
 
           docker run --gpus all  --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${DOCKER_IMAGE} ./packaging/build_conda.sh
 

diff --git a/.circleci/regenerate.py b/.circleci/regenerate.py
@@ -131,6 +131,8 @@ def generate_upload_workflow(*, base_workflow_name, btype, cu_version, filter_br
 
 
 def indent(indentation, data_list):
+    if len(data_list) == 0:
+        return ""
     return ("\n" + " " * indentation).join(
         yaml.dump(data_list, default_flow_style=False).splitlines()
     )

diff --git a/packaging/build_conda.sh b/packaging/build_conda.sh
@@ -16,5 +16,14 @@ export SOURCE_ROOT_DIR="$PWD"
 setup_conda_pytorch_constraint
 setup_conda_cudatoolkit_constraint
 setup_visual_studio_constraint
+
+if [[ "$JUST_TESTRUN" == "1" ]]
+then
+    # We are not building for other users, we
+    # are only trying to see if the tests pass.
+    # So save time by only building for our own GPU.
+    unset NVCC_FLAGS
+fi
+
 # shellcheck disable=SC2086
 conda build $CONDA_CHANNEL_FLAGS ${TEST_FLAG:-} -c bottler -c defaults -c conda-forge -c fvcore -c iopath --no-anaconda-upload --python "$PYTHON_VERSION" packaging/pytorch3d
diff --git a/pytorch3d/renderer/mesh/clip.py b/pytorch3d/renderer/mesh/clip.py
@@ -397,15 +397,15 @@ def clip_faces(
     # pyre-ignore[16]:
     faces_unculled = ~faces_culled
     # Case 1:  no clipped verts or culled faces
-    cases1_unclipped = torch.logical_and(faces_num_clipped_verts == 0, faces_unculled)
+    cases1_unclipped = (faces_num_clipped_verts == 0) & faces_unculled
     case1_unclipped_idx = cases1_unclipped.nonzero(as_tuple=True)[0]
     # Case 2: all verts clipped
-    case2_unclipped = torch.logical_or(faces_num_clipped_verts == 3, faces_culled)
+    case2_unclipped = (faces_num_clipped_verts == 3) | faces_culled
     # Case 3: two verts clipped
-    case3_unclipped = torch.logical_and(faces_num_clipped_verts == 2, faces_unculled)
+    case3_unclipped = (faces_num_clipped_verts == 2) & faces_unculled
     case3_unclipped_idx = case3_unclipped.nonzero(as_tuple=True)[0]
     # Case 4: one vert clipped
-    case4_unclipped = torch.logical_and(faces_num_clipped_verts == 1, faces_unculled)
+    case4_unclipped = (faces_num_clipped_verts == 1) & faces_unculled
     case4_unclipped_idx = case4_unclipped.nonzero(as_tuple=True)[0]
 
     # faces_unclipped_to_clipped_idx is an (F) dim tensor storing the index of each

diff --git a/tests/test_io_ply.py b/tests/test_io_ply.py
@@ -158,6 +158,7 @@ def test_load_simple_ascii(self):
     def test_pluggable_load_cube(self):
         """
         This won't work on Windows due to NamedTemporaryFile being reopened.
+        Use the testpath package instead?
         """
         ply_file = "\n".join(CUBE_PLY_LINES)
         io = IO()