Add unittest job to CircleCI (#2328)

.circleci/config.yml.in

@@ -155,106 +155,7 @@ jobs:
       - store_test_results:
           path: build_results/
 
-  binary_linux_conda_cuda:
-    <<: *binary_common
-    machine:
-      image: ubuntu-1604:201903-01
-    resource_class: gpu.medium
-    steps:
-    - checkout_merge
-    - run:
-        name: Setup environment
-        command: |
-          set -ex
-
-          curl -L https://packagecloud.io/circleci/trusty/gpgkey | sudo apt-key add -
-          curl -L https://dl.google.com/linux/linux_signing_key.pub | sudo apt-key add -
-
-          sudo apt-get update
-
-          sudo apt-get install \
-              apt-transport-https \
-              ca-certificates \
-              curl \
-              gnupg-agent \
-              software-properties-common
-
-          curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
-
-          sudo add-apt-repository \
-             "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
-             $(lsb_release -cs) \
-             stable"
-
-          sudo apt-get update
-          export DOCKER_VERSION="5:19.03.2~3-0~ubuntu-xenial"
-          sudo apt-get install docker-ce=${DOCKER_VERSION} docker-ce-cli=${DOCKER_VERSION} containerd.io=1.2.6-3
-
-          # Add the package repositories
-          distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
-          curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
-          curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
-
-          export NVIDIA_CONTAINER_VERSION="1.0.3-1"
-          sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit=${NVIDIA_CONTAINER_VERSION}
-          sudo systemctl restart docker
-
-          DRIVER_FN="NVIDIA-Linux-x86_64-440.59.run"
-          wget "https://s3.amazonaws.com/ossci-linux/nvidia_driver/$DRIVER_FN"
-          sudo /bin/bash "$DRIVER_FN" -s --no-drm || (sudo cat /var/log/nvidia-installer.log && false)
-          nvidia-smi
-
-    - run:
-        name: Pull docker image
-        command: |
-          set -ex
-          export DOCKER_IMAGE=pytorch/conda-cuda
-          echo Pulling docker image $DOCKER_IMAGE
-          docker pull $DOCKER_IMAGE >/dev/null
-
-    - run:
-        name: Build and run tests
-        command: |
-          set -ex
-
-          cd ${HOME}/project/
-
-          export DOCKER_IMAGE=pytorch/conda-cuda
-          export VARS_TO_PASS="-e PYTHON_VERSION -e BUILD_VERSION -e PYTORCH_VERSION -e UNICODE_ABI -e CU_VERSION"
-
-          docker run --gpus all  --ipc=host -v $(pwd):/remote -w /remote ${VARS_TO_PASS} ${DOCKER_IMAGE} ./packaging/build_conda.sh
-
   binary_win_conda:
-    <<: *binary_common
-    executor: windows-cpu
-    steps:
-      - checkout_merge
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate base
-            conda install -yq conda-build "conda-package-handling!=1.5.0"
-            packaging/build_conda.sh
-      - store_test_results:
-          path: build_results/
-
-  binary_win_conda_cuda:
-    <<: *binary_common
-    executor: windows-gpu
-    steps:
-      - checkout_merge
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate base
-            conda install -yq conda-build "conda-package-handling!=1.5.0"
-            packaging/build_conda.sh
-
-  binary_win_conda_release:
     <<: *binary_common
     executor: windows-cpu
     steps:
@@ -279,7 +180,7 @@ jobs:
       - store_test_results:
           path: build_results/
 
-  binary_win_wheel_release:
+  binary_win_wheel:
     <<: *binary_common
     executor: windows-cpu
     steps:
@@ -385,29 +286,173 @@ jobs:
               aws s3 cp "$pkg" "s3://pytorch/whl/${UPLOAD_CHANNEL}/<< parameters.subfolder >>" --acl public-read
             done
 
+  unittest_linux_cpu:
+    <<: *binary_common
+    docker:
+      - image: "pytorch/manylinux-cuda102"
+    resource_class: 2xlarge+
+    steps:
+      - checkout
+      - run:
+          name: Generate cache key
+          # This will refresh cache on Sundays, nightly build should generate new cache.
+          command: echo "$(date +"%Y-%U")" > .circleci-weekly
+      - restore_cache:
+          {% raw %}
+          keys:
+            - env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+      - run:
+          name: Setup
+          command: .circleci/unittest/linux/scripts/setup_env.sh
+      - save_cache:
+          {% raw %}
+          key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+          paths:
+            - conda
+            - env
+      - run:
+          name: Install torchvision
+          command: .circleci/unittest/linux/scripts/install.sh
+      - run:
+          name: Run tests
+          command: .circleci/unittest/linux/scripts/run_test.sh
+      - run:
+          name: Post process
+          command: .circleci/unittest/linux/scripts/post_process.sh
+      - store_test_results:
+          path: test-results
+
+  unittest_linux_gpu:
+    <<: *binary_common
+    machine:
+      image: ubuntu-1604-cuda-10.1:201909-23
+    resource_class: gpu.small
+    environment:
+      image_name: "pytorch/manylinux-cuda101"
+    steps:
+      - checkout
+      - run:
+          name: Generate cache key
+          # This will refresh cache on Sundays, nightly build should generate new cache.
+          command: echo "$(date +"%Y-%U")" > .circleci-weekly
+      - restore_cache:
+          {% raw %}
+          keys:
+            - env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+      - run:
+          name: Setup
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/setup_env.sh
+      - save_cache:
+          {% raw %}
+          key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+          paths:
+            - conda
+            - env
+      - run:
+          name: Install torchvision
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/install.sh
+      - run:
+          name: Run tests
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
+      - run:
+          name: Post Process
+          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/post_process.sh
+      - store_test_results:
+          path: test-results
+
+  unittest_windows_cpu:
+    <<: *binary_common
+    executor:
+      name: windows-cpu
+    steps:
+      - checkout
+      - run:
+          name: Generate cache key
+          # This will refresh cache on Sundays, nightly build should generate new cache.
+          command: echo "$(date +"%Y-%U")" > .circleci-weekly
+      - restore_cache:
+          {% raw %}
+          keys:
+            - env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+      - run:
+          name: Setup
+          command: .circleci/unittest/windows/scripts/setup_env.sh
+      - save_cache:
+          {% raw %}
+          key: env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+          paths:
+            - conda
+            - env
+      - run:
+          name: Install torchvision
+          command: .circleci/unittest/windows/scripts/install.sh
+      - run:
+          name: Run tests
+          command: .circleci/unittest/windows/scripts/run_test.sh
+      - run:
+          name: Post process
+          command: .circleci/unittest/windows/scripts/post_process.sh
+      - store_test_results:
+          path: test-results
+
+  unittest_windows_gpu:
+    <<: *binary_common
+    executor:
+      name: windows-gpu
+    environment:
+      CUDA_VERSION: "10.1"
+    steps:
+      - checkout
+      - run:
+          name: Generate cache key
+          # This will refresh cache on Sundays, nightly build should generate new cache.
+          command: echo "$(date +"%Y-%U")" > .circleci-weekly
+      - restore_cache:
+          {% raw %}
+          keys:
+            - env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+      - run:
+          name: Setup
+          command: .circleci/unittest/windows/scripts/setup_env.sh
+      - save_cache:
+          {% raw %}
+          key: env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
+          {% endraw %}
+          paths:
+            - conda
+            - env
+      - run:
+          name: Install torchvision
+          command: .circleci/unittest/windows/scripts/install.sh
+      - run:
+          name: Run tests
+          command: .circleci/unittest/windows/scripts/run_test.sh
+      - run:
+          name: Post process
+          command: .circleci/unittest/windows/scripts/post_process.sh
+      - store_test_results:
+          path: test-results
 
 workflows:
   build:
 {%- if True %}
     jobs:
       - circleci_consistency
-      {{ workflows(windows_latest_only=True) }}
-      - binary_linux_conda_cuda:
-          name: torchvision_linux_py3.8_cu102_cuda
-          python_version: "3.8"
-          cu_version: "cu102"
-      - binary_win_conda:
-          name: torchvision_win_py3.6_cpu
-          python_version: "3.6"
-          cu_version: "cpu"
-      - binary_win_conda_cuda:
-          name: torchvision_win_py3.6_cu101
-          python_version: "3.6"
-          cu_version: "cu101"
+      {{ build_workflows(windows_latest_only=True) }}
       - python_lint
       - python_type_check
       - clang_format
 
+  unittest:
+    jobs:
+      {{ unittest_workflows() }}
   nightly:
 {%- endif %}
     jobs:
@@ -415,4 +460,4 @@ workflows:
       - python_lint
       - python_type_check
       - clang_format
-      {{ workflows(prefix="nightly_", filter_branch="nightly", upload=True) }}
+      {{ build_workflows(prefix="nightly_", filter_branch="nightly", upload=True) }}

.circleci/regenerate.py

@@ -19,11 +19,14 @@ import yaml
 import os.path
 
 
-def workflows(prefix='', filter_branch=None, upload=False, indentation=6, windows_latest_only=False):
+PYTHON_VERSIONS = ["3.6", "3.7", "3.8"]
+
+
+def build_workflows(prefix='', filter_branch=None, upload=False, indentation=6, windows_latest_only=False):
     w = []
     for btype in ["wheel", "conda"]:
         for os_type in ["linux", "macos", "win"]:
-            python_versions = ["3.6", "3.7", "3.8"]
+            python_versions = PYTHON_VERSIONS
             cu_versions = (["cpu", "cu92", "cu101", "cu102"] if os_type == "linux" or os_type == "win" else ["cpu"])
             for python_version in python_versions:
                 for cu_version in cu_versions:
@@ -97,10 +100,14 @@ def generate_base_workflow(base_workflow_name, python_version, cu_version,
             }
         }
 
-    w = f"binary_{os_type}_{btype}_release" if os_type == "win" else f"binary_{os_type}_{btype}"
+    w = f"binary_{os_type}_{btype}"
     return {w: d}
 
 
+def gen_filter_branch_tree(*branches):
+    return {"branches": {"only": [b for b in branches]}}
+
+
 def generate_upload_workflow(base_workflow_name, os_type, btype, cu_version, *, filter_branch=None):
     d = {
         "name": f"{base_workflow_name}_upload",
@@ -131,6 +138,28 @@ def indent(indentation, data_list):
         yaml.dump(data_list, default_flow_style=False).splitlines())
 
 
+def unittest_workflows(indentation=6):
+    jobs = []
+    for os_type in ["linux", "windows"]:
+        for device_type in ["cpu", "gpu"]:
+            for i, python_version in enumerate(PYTHON_VERSIONS):
+                job = {
+                    "name": f"unittest_{os_type}_{device_type}_py{python_version}",
+                    "python_version": python_version,
+                }
+
+                if device_type == 'gpu':
+                    if python_version != "3.8":
+                        job['filters'] = gen_filter_branch_tree('master', 'nightly')
+                    job['cu_version'] = 'cu101'
+                else:
+                    job['cu_version'] = 'cpu'
+
+                jobs.append({f"unittest_{os_type}_{device_type}": job})
+
+    return indent(indentation, jobs)
+
+
 if __name__ == "__main__":
     d = os.path.dirname(__file__)
     env = jinja2.Environment(
@@ -140,4 +169,7 @@ if __name__ == "__main__":
     )
 
     with open(os.path.join(d, 'config.yml'), 'w') as f:
-        f.write(env.get_template('config.yml.in').render(workflows=workflows))
+        f.write(env.get_template('config.yml.in').render(
+            build_workflows=build_workflows,
+            unittest_workflows=unittest_workflows,
+        ))

.circleci/unittest/linux/scripts/environment.yml

+channels:
+  - defaults
+dependencies:
+  - numpy
+  - pytest
+  - pytest-cov
+  - codecov
+  - pip
+  - ca-certificates
+  - pip:
+    - future
+    - pillow>=4.1.1
+    - scipy
+    - av
\ No newline at end of file

.circleci/unittest/linux/scripts/install.sh

+#!/usr/bin/env bash
+
+unset PYTORCH_VERSION
+# For unittest, nightly PyTorch is used as the following section,
+# so no need to set PYTORCH_VERSION.
+# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.
+
+set -e
+
+eval "$(./conda/bin/conda shell.bash hook)"
+conda activate ./env
+
+if [ -z "${CUDA_VERSION:-}" ] ; then
+    cudatoolkit="cpuonly"
+else
+    version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
+    cudatoolkit="cudatoolkit=${version}"
+fi
+printf "Installing PyTorch with %s\n" "${cudatoolkit}"
+conda install -y -c pytorch-nightly pytorch "${cudatoolkit}"
+
+printf "* Installing torchvision\n"
+python setup.py develop
\ No newline at end of file

.circleci/unittest/linux/scripts/post_process.sh

+#!/usr/bin/env bash
+
+set -e
+
+eval "$(./conda/bin/conda shell.bash hook)"
+conda activate ./env
+
+codecov
\ No newline at end of file

.circleci/unittest/linux/scripts/run_test.sh

+#!/usr/bin/env bash
+
+set -e
+
+eval "$(./conda/bin/conda shell.bash hook)"
+conda activate ./env
+
+python -m torch.utils.collect_env
+pytest --cov=torchvision --junitxml=test-results/junit.xml -v --durations 20 test
\ No newline at end of file

.circleci/unittest/linux/scripts/setup_env.sh

+#!/usr/bin/env bash
+
+# This script is for setting up environment in which unit test is ran.
+# To speed up the CI time, the resulting environment is cached.
+#
+# Do not install PyTorch and torchvision here, otherwise they also get cached.
+
+set -e
+
+this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+root_dir="$(git rev-parse --show-toplevel)"
+conda_dir="${root_dir}/conda"
+env_dir="${root_dir}/env"
+
+cd "${root_dir}"
+
+# 1. Install conda at ./conda
+if [ ! -d "${conda_dir}" ]; then
+    printf "* Installing conda\n"
+    wget -O miniconda.sh http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
+    bash ./miniconda.sh -b -f -p "${conda_dir}"
+fi
+eval "$(${conda_dir}/bin/conda shell.bash hook)"
+
+# 2. Create test environment at ./env
+if [ ! -d "${env_dir}" ]; then
+    printf "* Creating a test environment\n"
+    conda create --prefix "${env_dir}" -y python="$PYTHON_VERSION"
+fi
+conda activate "${env_dir}"
+
+# 3. Install Conda dependencies
+printf "* Installing dependencies (except PyTorch)\n"
+conda env update --file "${this_dir}/environment.yml" --prune

.circleci/unittest/windows/scripts/environment.yml

+channels:
+  - defaults
+dependencies:
+  - numpy
+  - pytest
+  - pytest-cov
+  - codecov
+  - pip
+  - ca-certificates
+  - pip:
+    - future
+    - pillow>=4.1.1
+    - scipy==1.4.1
+    - av
\ No newline at end of file

.circleci/unittest/windows/scripts/install.sh

+#!/usr/bin/env bash
+
+unset PYTORCH_VERSION
+# For unittest, nightly PyTorch is used as the following section,
+# so no need to set PYTORCH_VERSION.
+# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.
+
+set -e
+
+this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+
+eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
+conda activate ./env
+
+if [ -z "${CUDA_VERSION:-}" ] ; then
+    cudatoolkit="cpuonly"
+else
+    version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
+    cudatoolkit="cudatoolkit=${version}"
+fi
+printf "Installing PyTorch with %s\n" "${cudatoolkit}"
+conda install -y -c pytorch-nightly pytorch "${cudatoolkit}"
+
+printf "* Installing torchvision\n"
+"$this_dir/vc_env_helper.bat" python setup.py develop
\ No newline at end of file

.circleci/unittest/windows/scripts/install_conda.bat

+start /wait "" "%miniconda_exe%" /S /InstallationType=JustMe /RegisterPython=0 /AddToPath=0 /D=%tmp_conda%
\ No newline at end of file

.circleci/unittest/windows/scripts/post_process.sh

+#!/usr/bin/env bash
+
+set -e
+
+eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
+conda activate ./env
+
+codecov

.circleci/unittest/windows/scripts/run_test.sh

+#!/usr/bin/env bash
+
+set -e
+
+eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
+conda activate ./env
+
+python -m torch.utils.collect_env
+pytest --cov=torchvision --junitxml=test-results/junit.xml -v --durations 20 test
\ No newline at end of file

.circleci/unittest/windows/scripts/setup_env.sh

+#!/usr/bin/env bash
+
+# This script is for setting up environment in which unit test is ran.
+# To speed up the CI time, the resulting environment is cached.
+#
+# Do not install PyTorch and torchvision here, otherwise they also get cached.
+
+set -e
+
+this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
+root_dir="$(git rev-parse --show-toplevel)"
+conda_dir="${root_dir}/conda"
+env_dir="${root_dir}/env"
+
+cd "${root_dir}"
+
+# 1. Install conda at ./conda
+if [ ! -d "${conda_dir}" ]; then
+    printf "* Installing conda\n"
+    export tmp_conda="$(echo $conda_dir | tr '/' '\\')"
+    export miniconda_exe="$(echo $root_dir | tr '/' '\\')\\miniconda.exe"
+    curl --output miniconda.exe https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe -O
+    "$this_dir/install_conda.bat"
+    unset tmp_conda
+    unset miniconda_exe
+fi
+
+eval "$(${conda_dir}/Scripts/conda.exe 'shell.bash' 'hook')"
+
+# 2. Create test environment at ./env
+if [ ! -d "${env_dir}" ]; then
+    printf "* Creating a test environment\n"
+    conda create --prefix "${env_dir}" -y python="$PYTHON_VERSION"
+fi
+conda activate "${env_dir}"
+
+# 3. Install Conda dependencies
+printf "* Installing dependencies (except PyTorch)\n"
+conda env update --file "${this_dir}/environment.yml" --prune
\ No newline at end of file

.circleci/unittest/windows/scripts/vc_env_helper.bat

+@echo on
+
+set VC_VERSION_LOWER=16
+set VC_VERSION_UPPER=17
+
+for /f "usebackq tokens=*" %%i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe" -legacy -products * -version [%VC_VERSION_LOWER%^,%VC_VERSION_UPPER%^) -property installationPath`) do (
+    if exist "%%i" if exist "%%i\VC\Auxiliary\Build\vcvarsall.bat" (
+        set "VS15INSTALLDIR=%%i"
+        set "VS15VCVARSALL=%%i\VC\Auxiliary\Build\vcvarsall.bat"
+        goto vswhere
+    )
+)
+
+:vswhere
+if "%VSDEVCMD_ARGS%" == "" (
+    call "%VS15VCVARSALL%" x64 || exit /b 1
+) else (
+    call "%VS15VCVARSALL%" x64 %VSDEVCMD_ARGS% || exit /b 1
+)
+
+@echo on
+
+set DISTUTILS_USE_SDK=1
+
+set args=%1
+shift
+:start
+if [%1] == [] goto done
+set args=%args% %1
+shift
+goto start
+
+:done
+if "%args%" == "" (
+    echo Usage: vc_env_helper.bat [command] [args]
+    echo e.g. vc_env_helper.bat cl /c test.cpp
+)
+
+%args% || exit /b 1

packaging/torchvision/meta.yaml

@@ -47,8 +47,6 @@ test:
     - av
     - ca-certificates
     {{ environ.get('CONDA_TYPING_CONSTRAINT') }}
-  commands:
-    pytest . --verbose --junitxml={{ environ.get("CONDA_PYTORCH_BUILD_RESULTS_DIRECTORY", "build/test_results.xml" )}}
 
 
 about: