Add unittest to CI

pytorch · Jun 22, 2020 · 68583dd · 68583dd
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commit 68583dd
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diff --git a/.circleci/config.yml b/.circleci/config.yml
diff --git a/.circleci/config.yml.in b/.circleci/config.yml.in
@@ -225,36 +225,6 @@ jobs:
           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 +249,7 @@ jobs:
       - store_test_results:
           path: build_results/
 
-  binary_win_wheel_release:
+  binary_win_wheel:
     <<: *binary_common
     executor: windows-cpu
     steps:
@@ -385,34 +355,182 @@ 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) }}
+      {{ build_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"
       - python_lint
       - python_type_check
       - clang_format
 
+  unittest:
+    jobs:
+      {{ unittest_workflows() }}
   nightly:
 {%- endif %}
     jobs:
       - circleci_consistency
       - python_lint
       - python_type_check
       - clang_format
-      {{ workflows(prefix="nightly_", filter_branch="nightly", upload=True) }}
+      {{ build_workflows(prefix="nightly_", filter_branch="nightly", upload=True) }}
diff --git a/.circleci/regenerate.py b/.circleci/regenerate.py
@@ -19,11 +19,14 @@
 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:
@@ -88,10 +91,14 @@ def generate_base_workflow(base_workflow_name, python_version, cu_version,
     if filter_branch is not None:
         d["filters"] = {"branches": {"only": filter_branch}}
 
-    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",
@@ -122,6 +129,26 @@ 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':
+                    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(
@@ -131,4 +158,7 @@ def indent(indentation, data_list):
     )
 
     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,
+        ))
diff --git a/.circleci/unittest/linux/scripts/environment.yml b/.circleci/unittest/linux/scripts/environment.yml
@@ -0,0 +1,14 @@
+channels:
+  - defaults
+dependencies:
+  - numpy
+  - pytest
+  - pytest-cov
+  - codecov
+  - pip
+  - ca-certificates
+  - pip:
+    - future
+    - pillow>=4.1.1
+    - scipy
+    - av
diff --git a/.circleci/unittest/linux/scripts/install.sh b/.circleci/unittest/linux/scripts/install.sh
@@ -0,0 +1,23 @@
+#!/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 "${cudatoolkit}"
+
+printf "* Installing torchvision\n"
+python setup.py develop
diff --git a/.circleci/unittest/linux/scripts/post_process.sh b/.circleci/unittest/linux/scripts/post_process.sh
@@ -0,0 +1,8 @@
+#!/usr/bin/env bash
+
+set -e
+
+eval "$(./conda/bin/conda shell.bash hook)"
+conda activate ./env
+
+codecov
diff --git a/.circleci/unittest/linux/scripts/run_test.sh b/.circleci/unittest/linux/scripts/run_test.sh
@@ -0,0 +1,9 @@
+#!/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