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Unverified Commit 0387b882 authored by Philip Meier's avatar Philip Meier Committed by GitHub
Browse files

cleanup CircleCI config (#7470)

parent ad9ee8b1
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.circleci/config.yml
View file @ 0387b882
......@@ -2,8 +2,8 @@ version: 2.1
# How to test the Linux jobs:
# - Install CircleCI local CLI: https://circleci.com/docs/2.0/local-cli/
# - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_linux_wheel_py3.8
# - Replace binary_linux_wheel_py3.8 with the name of the job you want to test.
# - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_win_wheel_py3.8
# - Replace binary_win_wheel_py3.8 with the name of the job you want to test.
# Job names are 'name:' key.
executors:
......@@ -99,25 +99,6 @@ commands:
- brew_install:
formulae: libtool
apt_install:
parameters:
args:
type: string
descr:
type: string
default: ""
update:
type: boolean
default: true
steps:
- run:
name: >
<<^ parameters.descr >> apt install << parameters.args >> <</ parameters.descr >>
<<# parameters.descr >> << parameters.descr >> <</ parameters.descr >>
command: |
<<# parameters.update >> sudo apt update -qy <</ parameters.update >>
sudo apt install << parameters.args >>
pip_install:
parameters:
args:
......@@ -139,55 +120,6 @@ commands:
--progress-bar=off
<< parameters.args >>
install_torchvision:
parameters:
editable:
type: boolean
default: true
steps:
- pip_install:
args: --pre torch --extra-index-url https://download.pytorch.org/whl/nightly/cpu
descr: Install PyTorch from nightly releases
- pip_install:
args: --no-build-isolation <<# parameters.editable >> --editable <</ parameters.editable >> .
descr: Install torchvision <<# parameters.editable >> in editable mode <</ parameters.editable >>
# Most of the test suite is handled by the `unittest` jobs, with completely different workflow and setup.
# This command can be used if only a selection of tests need to be run, for ad-hoc files.
run_tests_selective:
parameters:
file_or_dir:
type: string
steps:
- run:
name: Install test utilities
command: pip install --progress-bar=off pytest pytest-mock
- run:
name: Run tests
command: pytest --junitxml=test-results/junit.xml -v --durations 20 <<parameters.file_or_dir>>
- store_test_results:
path: test-results
download_model_weights:
parameters:
extract_roots:
type: string
default: "torchvision/models"
background:
type: boolean
default: true
steps:
- apt_install:
args: parallel wget
descr: Install download utilitites
- run:
name: Download model weights
background: << parameters.background >>
command: |
mkdir -p ~/.cache/torch/hub/checkpoints
python scripts/collect_model_urls.py << parameters.extract_roots >> \
| parallel -j0 'wget --no-verbose -O ~/.cache/torch/hub/checkpoints/`basename {}` {}\?source=ci'
binary_common: &binary_common
parameters:
# Edit these defaults to do a release
......@@ -269,50 +201,6 @@ jobs:
python .circleci/regenerate.py
git diff --exit-code || (echo ".circleci/config.yml not in sync with config.yml.in! Run .circleci/regenerate.py to update config"; exit 1)
binary_linux_wheel:
<<: *binary_common
docker:
- image: << parameters.wheel_docker_image >>
resource_class: 2xlarge+
steps:
- checkout_merge
- designate_upload_channel
- run:
name: Build conda packages
no_output_timeout: 30m
command: |
set -ex
packaging/build_wheel.sh
- store_artifacts:
path: dist
- persist_to_workspace:
root: dist
paths:
- "*"
binary_linux_conda:
<<: *binary_common
docker:
- image: "<< parameters.conda_docker_image >>"
resource_class: 2xlarge+
steps:
- checkout_merge
- designate_upload_channel
- run:
name: Build conda packages
no_output_timeout: 30m
command: |
set -ex
packaging/build_conda.sh
- store_artifacts:
path: /opt/conda/conda-bld/linux-64
- persist_to_workspace:
root: /opt/conda/conda-bld/linux-64
paths:
- "*"
- store_test_results:
path: build_results/
binary_win_conda:
<<: *binary_common
executor: windows-cpu
......@@ -524,44 +412,6 @@ jobs:
aws s3 cp "$pkg" "s3://pytorch/whl/${UPLOAD_CHANNEL}/<< parameters.subfolder >>" --acl public-read
done
smoke_test_linux_conda:
<<: *smoke_test_common
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
conda install -v -y -c pytorch-nightly pytorch
conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
- run:
name: smoke test
command: |
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_linux_pip:
<<: *smoke_test_common
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
- pip_install:
args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/nightly/torch_nightly.html
- run:
name: smoke test
command: |
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_docker_image_build:
machine:
image: ubuntu-2004:202104-01
......@@ -583,55 +433,6 @@ jobs:
docker push ${image_name}:${CIRCLE_WORKFLOW_ID}
docker push ${image_name}:latest
smoke_test_win_conda:
<<: *binary_common
executor:
name: windows-cpu
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda env remove -n python${PYTHON_VERSION} || true
conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
conda activate python${PYTHON_VERSION}
conda install -v -y -c pytorch-nightly pytorch
conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
- run:
name: smoke test
command: |
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_win_pip:
<<: *binary_common
executor:
name: windows-cpu
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
conda activate python${PYTHON_VERSION}
- pip_install:
args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/nightly/torch_nightly.html
- run:
name: smoke test
command: |
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
unittest_windows_cpu:
<<: *binary_common
executor:
......
.circleci/config.yml.in
View file @ 0387b882
......@@ -2,8 +2,8 @@ version: 2.1
# How to test the Linux jobs:
# - Install CircleCI local CLI: https://circleci.com/docs/2.0/local-cli/
# - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_linux_wheel_py3.8
# - Replace binary_linux_wheel_py3.8 with the name of the job you want to test.
# - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_win_wheel_py3.8
# - Replace binary_win_wheel_py3.8 with the name of the job you want to test.
# Job names are 'name:' key.
executors:
......@@ -99,25 +99,6 @@ commands:
- brew_install:
formulae: libtool
apt_install:
parameters:
args:
type: string
descr:
type: string
default: ""
update:
type: boolean
default: true
steps:
- run:
name: >
<<^ parameters.descr >> apt install << parameters.args >> <</ parameters.descr >>
<<# parameters.descr >> << parameters.descr >> <</ parameters.descr >>
command: |
<<# parameters.update >> sudo apt update -qy <</ parameters.update >>
sudo apt install << parameters.args >>
pip_install:
parameters:
args:
......@@ -139,55 +120,6 @@ commands:
--progress-bar=off
<< parameters.args >>
install_torchvision:
parameters:
editable:
type: boolean
default: true
steps:
- pip_install:
args: --pre torch --extra-index-url https://download.pytorch.org/whl/nightly/cpu
descr: Install PyTorch from nightly releases
- pip_install:
args: --no-build-isolation <<# parameters.editable >> --editable <</ parameters.editable >> .
descr: Install torchvision <<# parameters.editable >> in editable mode <</ parameters.editable >>
# Most of the test suite is handled by the `unittest` jobs, with completely different workflow and setup.
# This command can be used if only a selection of tests need to be run, for ad-hoc files.
run_tests_selective:
parameters:
file_or_dir:
type: string
steps:
- run:
name: Install test utilities
command: pip install --progress-bar=off pytest pytest-mock
- run:
name: Run tests
command: pytest --junitxml=test-results/junit.xml -v --durations 20 <<parameters.file_or_dir>>
- store_test_results:
path: test-results
download_model_weights:
parameters:
extract_roots:
type: string
default: "torchvision/models"
background:
type: boolean
default: true
steps:
- apt_install:
args: parallel wget
descr: Install download utilitites
- run:
name: Download model weights
background: << parameters.background >>
command: |
mkdir -p ~/.cache/torch/hub/checkpoints
python scripts/collect_model_urls.py << parameters.extract_roots >> \
| parallel -j0 'wget --no-verbose -O ~/.cache/torch/hub/checkpoints/`basename {}` {}\?source=ci'
binary_common: &binary_common
parameters:
# Edit these defaults to do a release
......@@ -269,50 +201,6 @@ jobs:
python .circleci/regenerate.py
git diff --exit-code || (echo ".circleci/config.yml not in sync with config.yml.in! Run .circleci/regenerate.py to update config"; exit 1)
binary_linux_wheel:
<<: *binary_common
docker:
- image: << parameters.wheel_docker_image >>
resource_class: 2xlarge+
steps:
- checkout_merge
- designate_upload_channel
- run:
name: Build conda packages
no_output_timeout: 30m
command: |
set -ex
packaging/build_wheel.sh
- store_artifacts:
path: dist
- persist_to_workspace:
root: dist
paths:
- "*"
binary_linux_conda:
<<: *binary_common
docker:
- image: "<< parameters.conda_docker_image >>"
resource_class: 2xlarge+
steps:
- checkout_merge
- designate_upload_channel
- run:
name: Build conda packages
no_output_timeout: 30m
command: |
set -ex
packaging/build_conda.sh
- store_artifacts:
path: /opt/conda/conda-bld/linux-64
- persist_to_workspace:
root: /opt/conda/conda-bld/linux-64
paths:
- "*"
- store_test_results:
path: build_results/
binary_win_conda:
<<: *binary_common
executor: windows-cpu
......@@ -524,44 +412,6 @@ jobs:
aws s3 cp "$pkg" "s3://pytorch/whl/${UPLOAD_CHANNEL}/<< parameters.subfolder >>" --acl public-read
done
smoke_test_linux_conda:
<<: *smoke_test_common
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
conda install -v -y -c pytorch-nightly pytorch
conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
- run:
name: smoke test
command: |
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_linux_pip:
<<: *smoke_test_common
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
- pip_install:
args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/nightly/torch_nightly.html
- run:
name: smoke test
command: |
source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_docker_image_build:
machine:
image: ubuntu-2004:202104-01
......@@ -583,55 +433,6 @@ jobs:
docker push ${image_name}:${CIRCLE_WORKFLOW_ID}
docker push ${image_name}:latest
smoke_test_win_conda:
<<: *binary_common
executor:
name: windows-cpu
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda env remove -n python${PYTHON_VERSION} || true
conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
conda activate python${PYTHON_VERSION}
conda install -v -y -c pytorch-nightly pytorch
conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
- run:
name: smoke test
command: |
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
smoke_test_win_pip:
<<: *binary_common
executor:
name: windows-cpu
steps:
- attach_workspace:
at: ~/workspace
- designate_upload_channel
- run:
name: install binaries
command: |
set -x
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
conda activate python${PYTHON_VERSION}
- pip_install:
args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/nightly/torch_nightly.html
- run:
name: smoke test
command: |
eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
unittest_windows_cpu:
<<: *binary_common
executor:
......
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