Add Circleci project (#57)

* Add .circleci/config.yml

* Add circleci

* Add circleci

* Updated config.yml

* format code

* format code

* fix

.circleci/config.yml

@@ -0,0 +1,34 @@
+version: 2.1
+
+# this allows you to use CircleCI's dynamic configuration feature
+setup: true
+
+# the path-filtering orb is required to continue a pipeline based on
+# the path of an updated fileset
+orbs:
+  path-filtering: circleci/path-filtering@0.1.2
+
+workflows:
+  # the always-run workflow is always triggered, regardless of the pipeline parameters.
+  always-run:
+    jobs:
+      # the path-filtering/filter job determines which pipeline
+      # parameters to update.
+      - path-filtering/filter:
+          name: check-updated-files
+          # 3-column, whitespace-delimited mapping. One mapping per
+          # line:
+          # <regex path-to-test> <parameter-to-set> <value-of-pipeline-parameter>
+          mapping: |
+            mmyolo/.* lint_only false
+            requirements/.* lint_only false
+            tests/.* lint_only false
+            tools/.* lint_only false
+            configs/.* lint_only false
+            .circleci/.* lint_only false
+          base-revision: main
+          # this is the path of the configuration we should trigger once
+          # path filtering and pipeline parameter value updates are
+          # complete. In this case, we are using the parent dynamic
+          # configuration itself.
+          config-path: .circleci/test.yml

.circleci/docker/Dockerfile

@@ -0,0 +1,11 @@
+ARG PYTORCH="1.8.1"
+ARG CUDA="10.2"
+ARG CUDNN="7"
+
+FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
+
+# To fix GPG key error when running apt-get update
+RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
+RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
+
+RUN apt-get update && apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx

.circleci/test.yml

@@ -0,0 +1,186 @@
+version: 2.1
+
+# the default pipeline parameters, which will be updated according to
+# the results of the path-filtering orb
+parameters:
+  lint_only:
+    type: boolean
+    default: true
+
+jobs:
+  lint:
+    docker:
+      - image: cimg/python:3.7.4
+    steps:
+      - checkout
+      - run:
+          name: Install pre-commit hook
+          command: |
+            pip install pre-commit
+            pre-commit install
+      - run:
+          name: Linting
+          command: pre-commit run --all-files
+      - run:
+          name: Check docstring coverage
+          command: |
+            pip install interrogate
+            interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-magic --ignore-regex "__repr__" --fail-under 90 mmyolo
+  build_cpu:
+    parameters:
+      # The python version must match available image tags in
+      # https://circleci.com/developer/images/image/cimg/python
+      python:
+        type: string
+      torch:
+        type: string
+      torchvision:
+        type: string
+    docker:
+      - image: cimg/python:<< parameters.python >>
+    resource_class: large
+    steps:
+      - checkout
+      - run:
+          name: Install Libraries
+          command: |
+            sudo apt-get update
+            sudo apt-get install -y ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx libjpeg-dev zlib1g-dev libtinfo-dev libncurses5
+      - run:
+          name: Configure Python & pip
+          command: |
+            pip install --upgrade pip
+            pip install wheel
+      - run:
+          name: Install PyTorch
+          command: |
+            python -V
+            pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - run:
+          name: Install mmyolo dependencies
+          command: |
+            pip install git+https://github.com/open-mmlab/mmengine.git@main
+            pip install -U openmim
+            mim install 'mmcv >= 2.0.0rc1'
+            pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
+            pip install -r requirements/albu.txt
+            pip install -r requirements/tests.txt
+      - run:
+          name: Build and install
+          command: |
+            pip install -e .
+      - run:
+          name: Run unittests
+          command: |
+            coverage run --branch --source mmyolo -m pytest tests/
+            coverage xml
+            coverage report -m
+  build_cuda:
+    parameters:
+      torch:
+        type: string
+      cuda:
+        type: enum
+        enum: ["10.1", "10.2", "11.1","11.0"]
+      cudnn:
+        type: integer
+        default: 7
+    machine:
+      image: ubuntu-2004-cuda-11.4:202110-01
+      # docker_layer_caching: true
+    resource_class: gpu.nvidia.small
+    steps:
+      - checkout
+      - run:
+          # Cloning repos in VM since Docker doesn't have access to the private key
+          name: Clone Repos
+          command: |
+            git clone -b main --depth 1 https://github.com/open-mmlab/mmengine.git /home/circleci/mmengine
+            git clone -b dev-3.x --depth 1 https://github.com/open-mmlab/mmdetection.git /home/circleci/mmdetection
+      - run:
+          name: Build Docker image
+          command: |
+            docker build .circleci/docker -t mmyolo:gpu --build-arg PYTORCH=<< parameters.torch >> --build-arg CUDA=<< parameters.cuda >> --build-arg CUDNN=<< parameters.cudnn >>
+            docker run --gpus all -t -d -v /home/circleci/project:/mmyolo -v /home/circleci/mmengine:/mmengine -v /home/circleci/mmdetection:/mmdetection -w /mmyolo --name mmyolo mmyolo:gpu
+      - run:
+          name: Install mmyolo dependencies
+          command: |
+            docker exec mmyolo pip install -e /mmengine
+            docker exec mmyolo pip install -U openmim
+            docker exec mmyolo mim install 'mmcv >= 2.0.0rc1'
+            docker exec mmyolo pip install -e /mmdetection
+            docker exec mmyolo pip install -r requirements/albu.txt
+            docker exec mmyolo pip install -r requirements/tests.txt
+      - run:
+          name: Build and install
+          command: |
+            docker exec mmyolo pip install -e .
+      - run:
+          name: Run unittests
+          command: |
+            docker exec mmyolo pytest tests/
+
+workflows:
+  pr_stage_lint:
+    when: << pipeline.parameters.lint_only >>
+    jobs:
+      - lint:
+          name: lint
+          filters:
+            branches:
+              ignore:
+                - main
+
+  pr_stage_test:
+    when:
+      not:
+        << pipeline.parameters.lint_only >>
+    jobs:
+      - lint:
+          name: lint
+          filters:
+            branches:
+              ignore:
+                - main
+      - build_cpu:
+          name: minimum_version_cpu
+          torch: 1.7.0
+          torchvision: 0.8.1
+          python: 3.8.0  # The lowest python 3.6.x version available on CircleCI images
+          requires:
+            - lint
+      - build_cpu:
+          name: maximum_version_cpu
+          torch: 1.12.1
+          torchvision: 0.13.1
+          python: 3.9.0
+          requires:
+            - minimum_version_cpu
+      - hold:
+          type: approval
+          requires:
+            - maximum_version_cpu
+      - build_cuda:
+          name: mainstream_version_gpu
+          torch: 1.8.1
+          # Use double quotation mark to explicitly specify its type
+          # as string instead of number
+          cuda: "10.2"
+          requires:
+            - hold
+  merge_stage_test:
+    when:
+      not:
+        << pipeline.parameters.lint_only >>
+    jobs:
+      - build_cuda:
+          name: minimum_version_gpu
+          torch: 1.7.0
+          # Use double quotation mark to explicitly specify its type
+          # as string instead of number
+          cuda: "11.0"
+          cudnn: 8
+          filters:
+            branches:
+              only:
+                - main

configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py

@@ -10,7 +10,7 @@ deepen_factor = 0.33
 widen_factor = 0.5
 max_epochs = 300
 save_epoch_intervals = 10
-train_batch_size_per_gpu = 4
+train_batch_size_per_gpu = 16
 train_num_workers = 8
 val_batch_size_per_gpu = 1
 val_num_workers = 2

mmyolo/datasets/transforms/transforms.py

@@ -478,7 +478,8 @@ class YOLOv5RandomAffine(BaseTransform):
             width (int): Image width.
 
         Returns:
-            Tuple[np.ndarray, float]: The result of warp_matrix and scaling_ratio.
+            Tuple[np.ndarray, float]: The result of warp_matrix and
+            scaling_ratio.
         """
         # Rotation
         rotation_degree = random.uniform(-self.max_rotate_degree,