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Unverified Commit e3da44bb authored by Philip Meier's avatar Philip Meier Committed by GitHub
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remove Linux GPU unittest from CircleCI (#7354)

parent 8499bc49
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.circleci/config.yml
View file @ e3da44bb
......@@ -722,96 +722,6 @@ jobs:
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
unittest_linux_cpu:
<<: *binary_common
docker:
- image: "pytorch/manylinux-cpu"
resource_class: 2xlarge+
steps:
- checkout
- designate_upload_channel
- run:
name: Generate cache key
# This will refresh cache on Sundays, nightly build should generate new cache.
command: echo "$(date +"%Y-%U")" > .circleci-weekly
- restore_cache:
keys:
- env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
- run:
name: Setup
command: .circleci/unittest/linux/scripts/setup_env.sh
- save_cache:
key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
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-2004-cuda-11.4:202110-01
resource_class: gpu.nvidia.medium
environment:
image_name: "pytorch/manylinux-cuda117"
CU_VERSION: << parameters.cu_version >>
PYTHON_VERSION: << parameters.python_version >>
steps:
- checkout
- designate_upload_channel
- 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:
keys:
- env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
- run:
name: Setup
command: docker run -e PYTHON_VERSION -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/setup_env.sh
- save_cache:
key: env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
paths:
- conda
- env
- run:
# Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
# Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
# They're avaiable in all the other workflows (OSX and Windows).
# But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
# So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
name: export CIRCLECI env var
command: echo "CIRCLECI=true" >> ./env.list
- run:
name: Install torchvision
command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
- run:
name: Run tests
command: docker run --env-file ./env.list -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:
......@@ -1350,28 +1260,6 @@ workflows:
- unittest_torchhub
- unittest_onnx
- unittest_extended
- unittest_linux_gpu:
cu_version: cu117
name: unittest_linux_gpu_py3.8
python_version: '3.8'
- unittest_linux_gpu:
cu_version: cu117
filters:
branches:
only:
- main
- nightly
name: unittest_linux_gpu_py3.9
python_version: '3.9'
- unittest_linux_gpu:
cu_version: cu117
filters:
branches:
only:
- main
- nightly
name: unittest_linux_gpu_py3.10
python_version: '3.10'
- unittest_windows_cpu:
cu_version: cpu
name: unittest_windows_cpu_py3.8
......
.circleci/config.yml.in
View file @ e3da44bb
......@@ -722,96 +722,6 @@ jobs:
conda activate python${PYTHON_VERSION}
python -c "import torchvision"
unittest_linux_cpu:
<<: *binary_common
docker:
- image: "pytorch/manylinux-cpu"
resource_class: 2xlarge+
steps:
- checkout
- designate_upload_channel
- run:
name: Generate cache key
# This will refresh cache on Sundays, nightly build should generate new cache.
command: echo "$(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-2004-cuda-11.4:202110-01
resource_class: gpu.nvidia.medium
environment:
image_name: "pytorch/manylinux-cuda117"
CU_VERSION: << parameters.cu_version >>
PYTHON_VERSION: << parameters.python_version >>
steps:
- checkout
- designate_upload_channel
- 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-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
{% endraw %}
- run:
name: Setup
command: docker run -e PYTHON_VERSION -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/setup_env.sh
- save_cache:
{% raw %}
key: env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
{% endraw %}
paths:
- conda
- env
- run:
# Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
# Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
# They're avaiable in all the other workflows (OSX and Windows).
# But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
# So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
name: export CIRCLECI env var
command: echo "CIRCLECI=true" >> ./env.list
- run:
name: Install torchvision
command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
- run:
name: Run tests
command: docker run --env-file ./env.list -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:
......
.circleci/regenerate.py
View file @ e3da44bb
......@@ -255,12 +255,11 @@ def indent(indentation, data_list):
def unittest_workflows(indentation=6):
jobs = []
for os_type in ["linux", "windows", "macos"]:
for os_type in ["windows", "macos"]:
for device_type in ["cpu", "gpu"]:
if os_type == "macos" and device_type == "gpu":
continue
if os_type == "linux" and device_type == "cpu":
continue
for i, python_version in enumerate(PYTHON_VERSIONS):
# Turn off unit tests for 3.11, unit test are not setup properly
......
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