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config.yml
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config.yml
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# WARNING: DO NOT EDIT THIS FILE DIRECTLY!!!
# See the README.md in this directory.
# IMPORTANT: To update Docker image version, please follow
# the instructions at
# https://github.com/pytorch/pytorch/wiki/Docker-image-build-on-CircleCI
version: 2.1
parameters:
run_binary_tests:
type: boolean
default: false
docker_config_defaults: &docker_config_defaults
user: jenkins
aws_auth:
# This IAM user only allows read-write access to ECR
aws_access_key_id: ${CIRCLECI_AWS_ACCESS_KEY_FOR_ECR_READ_WRITE_V4}
aws_secret_access_key: ${CIRCLECI_AWS_SECRET_KEY_FOR_ECR_READ_WRITE_V4}
executors:
windows-with-nvidia-gpu:
machine:
resource_class: windows.gpu.nvidia.medium
image: windows-server-2019-nvidia:canary
shell: bash.exe
windows-xlarge-cpu-with-nvidia-cuda:
machine:
resource_class: windows.xlarge
image: windows-server-2019-vs2019:canary
shell: bash.exe
windows-medium-cpu-with-nvidia-cuda:
machine:
resource_class: windows.medium
image: windows-server-2019-vs2019:canary
shell: bash.exe
commands:
calculate_docker_image_tag:
description: "Calculates the docker image tag"
steps:
- run:
name: "Calculate docker image hash"
command: |
DOCKER_TAG=$(git rev-parse HEAD:.circleci/docker)
echo "DOCKER_TAG=${DOCKER_TAG}" >> "${BASH_ENV}"
designate_upload_channel:
description: "inserts the correct upload channel into ${BASH_ENV}"
steps:
- run:
name: adding UPLOAD_CHANNEL to BASH_ENV
command: |
our_upload_channel=nightly
# On tags upload to test instead
if [[ -n "${CIRCLE_TAG}" ]]; then
our_upload_channel=test
fi
echo "export UPLOAD_CHANNEL=${our_upload_channel}" >> ${BASH_ENV}
# This system setup script is meant to run before the CI-related scripts, e.g.,
# installing Git client, checking out code, setting up CI env, and
# building/testing.
setup_linux_system_environment:
steps:
- run:
name: Set Up System Environment
no_output_timeout: "1h"
command: .circleci/scripts/setup_linux_system_environment.sh
setup_ci_environment:
steps:
- run:
name: Set Up CI Environment After attach_workspace
no_output_timeout: "1h"
command: .circleci/scripts/setup_ci_environment.sh
brew_update:
description: "Update Homebrew and install base formulae"
steps:
- run:
name: Update Homebrew
no_output_timeout: "10m"
command: |
set -ex
# Update repositories manually.
# Running `brew update` produces a comparison between the
# current checkout and the updated checkout, which takes a
# very long time because the existing checkout is 2y old.
for path in $(find /usr/local/Homebrew -type d -name .git)
do
cd $path/..
git fetch --depth=1 origin
git reset --hard origin/master
done
export HOMEBREW_NO_AUTO_UPDATE=1
# Install expect and moreutils so that we can call `unbuffer` and `ts`.
# moreutils installs a `parallel` executable by default, which conflicts
# with the executable from the GNU `parallel`, so we must unlink GNU
# `parallel` first, and relink it afterwards.
brew unlink parallel
brew install moreutils
brew link parallel --overwrite
brew install expect
brew_install:
description: "Install Homebrew formulae"
parameters:
formulae:
type: string
default: ""
steps:
- run:
name: Install << parameters.formulae >>
no_output_timeout: "10m"
command: |
set -ex
export HOMEBREW_NO_AUTO_UPDATE=1
brew install << parameters.formulae >>
run_brew_for_macos_build:
steps:
- brew_update
- brew_install:
formulae: libomp
run_brew_for_ios_build:
steps:
- brew_update
- brew_install:
formulae: libtool
optional_merge_target_branch:
steps:
- run:
name: (Optional) Merge target branch
no_output_timeout: "10m"
command: |
if [ -n "$CIRCLE_PULL_REQUEST" ]; then
PR_NUM=$(basename $CIRCLE_PULL_REQUEST)
CIRCLE_PR_BASE_BRANCH=$(curl -s https://api.github.com/repos/$CIRCLE_PROJECT_USERNAME/$CIRCLE_PROJECT_REPONAME/pulls/$PR_NUM | jq -r '.base.ref')
if [[ "${BUILD_ENVIRONMENT}" == *"xla"* || "${BUILD_ENVIRONMENT}" == *"gcc5"* ]] ; then
set -x
git config --global user.email "[email protected]"
git config --global user.name "CircleCI"
git config remote.origin.url https://github.com/pytorch/pytorch.git
git config --add remote.origin.fetch +refs/heads/master:refs/remotes/origin/master
git fetch --tags --progress https://github.com/pytorch/pytorch.git +refs/heads/master:refs/remotes/origin/master --depth=100 --quiet
# PRs generated from ghstack has format CIRCLE_PR_BASE_BRANCH=gh/xxx/1234/base
if [[ "${CIRCLE_PR_BASE_BRANCH}" == "gh/"* ]]; then
CIRCLE_PR_BASE_BRANCH=master
fi
export GIT_MERGE_TARGET=`git log -n 1 --pretty=format:"%H" origin/$CIRCLE_PR_BASE_BRANCH`
echo "GIT_MERGE_TARGET: " ${GIT_MERGE_TARGET}
export GIT_COMMIT=${CIRCLE_SHA1}
echo "GIT_COMMIT: " ${GIT_COMMIT}
git checkout -f ${GIT_COMMIT}
git reset --hard ${GIT_COMMIT}
git merge --allow-unrelated-histories --no-edit --no-ff ${GIT_MERGE_TARGET}
echo "Merged $CIRCLE_PR_BASE_BRANCH branch before building in environment $BUILD_ENVIRONMENT"
set +x
else
echo "No need to merge with $CIRCLE_PR_BASE_BRANCH, skipping..."
fi
else
echo "This is not a pull request, skipping..."
fi
upload_binary_size_for_android_build:
description: "Upload binary size data for Android build"
parameters:
build_type:
type: string
default: ""
artifacts:
type: string
default: ""
steps:
- run:
name: "Binary Size - Install Dependencies"
no_output_timeout: "5m"
command: |
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
retry pip3 install requests
- run:
name: "Binary Size - Untar Artifacts"
no_output_timeout: "5m"
command: |
# The artifact file is created inside docker container, which contains the result binaries.
# Now unpackage it into the project folder. The subsequent script will scan project folder
# to locate result binaries and report their sizes.
# If artifact file is not provided it assumes that the project folder has been mounted in
# the docker during build and already contains the result binaries, so this step can be skipped.
export ARTIFACTS="<< parameters.artifacts >>"
if [ -n "${ARTIFACTS}" ]; then
tar xf "${ARTIFACTS}" -C ~/project
fi
- run:
name: "Binary Size - Upload << parameters.build_type >>"
no_output_timeout: "5m"
command: |
cd ~/project
export ANDROID_BUILD_TYPE="<< parameters.build_type >>"
export COMMIT_TIME=$(git log --max-count=1 --format=%ct || echo 0)
python3 .circleci/scripts/upload_binary_size_to_scuba.py android
##############################################################################
# Binary build (nightlies nightly build) defaults
# The binary builds use the docker executor b/c at time of writing the machine
# executor is limited to only two cores and is painfully slow (4.5+ hours per
# GPU build). But the docker executor cannot be run with --runtime=nvidia, and
# so the binary test/upload jobs must run on a machine executor. The package
# built in the build job is persisted to the workspace, which the test jobs
# expect. The test jobs just run a few quick smoke tests (very similar to the
# second-round-user-facing smoke tests above) and then upload the binaries to
# their final locations. The upload part requires credentials that should only
# be available to org-members.
#
# binary_checkout MUST be run before other commands here. This is because the
# other commands are written in .circleci/scripts/*.sh , so the pytorch source
# code must be downloaded on the machine before they can be run. We cannot
# inline all the code into this file, since that would cause the yaml size to
# explode past 4 MB (all the code in the command section is just copy-pasted to
# everywhere in the .circleci/config.yml file where it appears).
##############################################################################
# Checks out the Pytorch and Builder repos (always both of them), and places
# them in the right place depending on what executor we're running on. We curl
# our .sh file from the interweb to avoid yaml size bloat. Note that many jobs
# do not need both the pytorch and builder repos, so this is a little wasteful
# (smoke tests and upload jobs do not need the pytorch repo).
binary_checkout: &binary_checkout
name: Checkout pytorch/builder repo
command: .circleci/scripts/binary_checkout.sh
# Parses circleci arguments in a consistent way, essentially routing to the
# correct pythonXgccXcudaXos build we want
binary_populate_env: &binary_populate_env
name: Set up binary env variables
command: .circleci/scripts/binary_populate_env.sh
binary_install_miniconda: &binary_install_miniconda
name: Install miniconda
no_output_timeout: "1h"
command: .circleci/scripts/binary_install_miniconda.sh
# This section is used in the binary_test and smoke_test jobs. It expects
# 'binary_populate_env' to have populated /home/circleci/project/env and it
# expects another section to populate /home/circleci/project/ci_test_script.sh
# with the code to run in the docker
binary_run_in_docker: &binary_run_in_docker
name: Run in docker
# This step only runs on circleci linux machine executors that themselves
# need to start docker images
command: .circleci/scripts/binary_run_in_docker.sh
##############################################################################
# Build parameters
##############################################################################
pytorch_params: &pytorch_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
resource_class:
type: string
default: "large"
use_cuda_docker_runtime:
type: string
default: ""
build_only:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
DOCKER_IMAGE: << parameters.docker_image >>
USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
BUILD_ONLY: << parameters.build_only >>
resource_class: << parameters.resource_class >>
pytorch_ios_params: &pytorch_ios_params
parameters:
build_environment:
type: string
default: ""
ios_arch:
type: string
default: ""
ios_platform:
type: string
default: ""
op_list:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
IOS_ARCH: << parameters.ios_arch >>
IOS_PLATFORM: << parameters.ios_platform >>
SELECTED_OP_LIST: << parameters.op_list >>
pytorch_windows_params: &pytorch_windows_params
parameters:
executor:
type: string
default: "windows-xlarge-cpu-with-nvidia-cuda"
build_environment:
type: string
default: ""
test_name:
type: string
default: ""
cuda_version:
type: string
default: "10"
python_version:
type: string
default: "3.6"
vc_version:
type: string
default: "14.16"
vc_year:
type: string
default: "2019"
vc_product:
type: string
default: "BuildTools"
use_cuda:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: <<parameters.build_environment>>
SCCACHE_BUCKET: "ossci-compiler-cache"
CUDA_VERSION: <<parameters.cuda_version>>
PYTHON_VERSION: <<parameters.python_version>>
VC_VERSION: <<parameters.vc_version>>
VC_YEAR: <<parameters.vc_year>>
VC_PRODUCT: <<parameters.vc_product>>
USE_CUDA: <<parameters.use_cuda>>
TORCH_CUDA_ARCH_LIST: "7.5"
JOB_BASE_NAME: <<parameters.test_name>>
JOB_EXECUTOR: <<parameters.executor>>
caffe2_params: &caffe2_params
parameters:
build_environment:
type: string
default: ""
build_ios:
type: string
default: ""
docker_image:
type: string
default: ""
use_cuda_docker_runtime:
type: string
default: ""
build_only:
type: string
default: ""
resource_class:
type: string
default: "large"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
BUILD_IOS: << parameters.build_ios >>
USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
DOCKER_IMAGE: << parameters.docker_image >>
BUILD_ONLY: << parameters.build_only >>
resource_class: << parameters.resource_class >>
binary_linux_build_params: &binary_linux_build_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
libtorch_variant:
type: string
default: ""
resource_class:
type: string
default: "2xlarge+"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
LIBTORCH_VARIANT: << parameters.libtorch_variant >>
ANACONDA_USER: pytorch
resource_class: << parameters.resource_class >>
docker:
- image: << parameters.docker_image >>
binary_linux_test_upload_params: &binary_linux_test_upload_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
libtorch_variant:
type: string
default: ""
resource_class:
type: string
default: "medium"
use_cuda_docker_runtime:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
DOCKER_IMAGE: << parameters.docker_image >>
USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
LIBTORCH_VARIANT: << parameters.libtorch_variant >>
resource_class: << parameters.resource_class >>
binary_mac_params: &binary_mac_params
parameters:
build_environment:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
binary_windows_params: &binary_windows_params
parameters:
build_environment:
type: string
default: ""
executor:
type: string
default: "windows-xlarge-cpu-with-nvidia-cuda"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
BUILD_FOR_SYSTEM: windows
JOB_EXECUTOR: <<parameters.executor>>
promote_common: &promote_common
docker:
- image: pytorch/release
parameters:
package_name:
description: "package name to promote"
type: string
default: ""
environment:
PACKAGE_NAME: << parameters.package_name >>
ANACONDA_API_TOKEN: ${CONDA_PYTORCHBOT_TOKEN}
AWS_ACCESS_KEY_ID: ${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}
AWS_SECRET_ACCESS_KEY: ${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}
##############################################################################
# Job specs
##############################################################################
jobs:
pytorch_linux_build:
<<: *pytorch_params
machine:
image: ubuntu-1604:202007-01
steps:
# See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- optional_merge_target_branch
- setup_ci_environment
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
# TODO: Remove this after we figure out why rocm tests are failing
if [[ "${DOCKER_IMAGE}" == *rocm* ]]; then
export DOCKER_TAG="ab1632df-fa59-40e6-8c23-98e004f61148"
fi
if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
echo 'ATEN_THREADING=TBB' >> "${BASH_ENV}"
echo 'USE_TBB=1' >> "${BASH_ENV}"
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
echo 'ATEN_THREADING=NATIVE' >> "${BASH_ENV}"
fi
echo "Parallel backend flags: "${PARALLEL_FLAGS}
# Pull Docker image and run build
echo "DOCKER_IMAGE: "${DOCKER_IMAGE}:${DOCKER_TAG}
time docker pull ${DOCKER_IMAGE}:${DOCKER_TAG} >/dev/null
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE}:${DOCKER_TAG})
git submodule sync && git submodule update -q --init --recursive
docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && .jenkins/pytorch/build.sh && find ${BUILD_ROOT} -type f -name "*.a" -or -name "*.o" -delete") | docker exec -u jenkins -i "$id" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
# Push intermediate Docker image for next phase to use
if [ -z "${BUILD_ONLY}" ]; then
# Note [Special build images]
# The xla build uses the same docker image as
# pytorch-linux-trusty-py3.6-gcc5.4-build. In the push step, we have to
# distinguish between them so the test can pick up the correct image.
output_image=${DOCKER_IMAGE}:${DOCKER_TAG}-${CIRCLE_SHA1}
if [[ ${BUILD_ENVIRONMENT} == *"xla"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-xla
elif [[ ${BUILD_ENVIRONMENT} == *"libtorch"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-libtorch
elif [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-paralleltbb
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-parallelnative
elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-x86_64"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-android-x86_64
elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-arm-v7a"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-android-arm-v7a
elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-arm-v8a"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-android-arm-v8a
elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-x86_32"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-android-x86_32
elif [[ ${BUILD_ENVIRONMENT} == *"android-ndk-r19c-vulkan-x86_32"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-android-vulkan-x86_32
elif [[ ${BUILD_ENVIRONMENT} == *"vulkan-linux"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-vulkan
else
export COMMIT_DOCKER_IMAGE=$output_image
fi
docker commit "$id" ${COMMIT_DOCKER_IMAGE}
time docker push ${COMMIT_DOCKER_IMAGE}
fi
pytorch_linux_test:
<<: *pytorch_params
machine:
image: ubuntu-1604:202007-01
steps:
# See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: Download Docker image
no_output_timeout: "90m"
command: |
set -e
export PYTHONUNBUFFERED=1
# TODO: Remove this after we figure out why rocm tests are failing
if [[ "${DOCKER_IMAGE}" == *rocm* ]]; then
export DOCKER_TAG="ab1632df-fa59-40e6-8c23-98e004f61148"
fi
# See Note [Special build images]
output_image=${DOCKER_IMAGE}:${DOCKER_TAG}-${CIRCLE_SHA1}
if [[ ${BUILD_ENVIRONMENT} == *"xla"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-xla
elif [[ ${BUILD_ENVIRONMENT} == *"libtorch"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-libtorch
elif [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-paralleltbb
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-parallelnative
elif [[ ${BUILD_ENVIRONMENT} == *"vulkan-linux"* ]]; then
export COMMIT_DOCKER_IMAGE=$output_image-vulkan
else
export COMMIT_DOCKER_IMAGE=$output_image
fi
echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
echo 'ATEN_THREADING=TBB' >> "${BASH_ENV}"
echo 'USE_TBB=1' >> "${BASH_ENV}"
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
echo 'ATEN_THREADING=NATIVE' >> "${BASH_ENV}"
fi
echo "Parallel backend flags: "${PARALLEL_FLAGS}
time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
# TODO: Make this less painful
if [ -n "${USE_CUDA_DOCKER_RUNTIME}" ]; then
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --gpus all --shm-size=2g -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
elif [[ ${BUILD_ENVIRONMENT} == *"rocm"* ]]; then
hostname
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --shm-size=8g --ipc=host --device /dev/kfd --device /dev/dri --group-add video -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
else
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
fi
echo "id=${id}" >> "${BASH_ENV}"
- run:
name: Check for no AVX instruction by default
no_output_timeout: "20m"
command: |
set -e
is_vanilla_build() {
if [ "${BUILD_ENVIRONMENT}" == "pytorch-linux-bionic-py3.6-clang9-test" ]; then
return 0
fi
if [ "${BUILD_ENVIRONMENT}" == "pytorch-linux-xenial-py3.6-gcc5.4-test" ]; then
return 0
fi
return 1
}
if is_vanilla_build; then
echo "apt-get update && apt-get install -y qemu-user gdb" | docker exec -u root -i "$id" bash
echo "cd workspace/build; qemu-x86_64 -g 2345 -cpu Broadwell -E ATEN_CPU_CAPABILITY=default ./bin/basic --gtest_filter=BasicTest.BasicTestCPU & gdb ./bin/basic -ex 'set pagination off' -ex 'target remote :2345' -ex 'continue' -ex 'bt' -ex='set confirm off' -ex 'quit \$_isvoid(\$_exitcode)'" | docker exec -u jenkins -i "$id" bash
else
echo "Skipping for ${BUILD_ENVIRONMENT}"
fi
- run:
name: Run tests
no_output_timeout: "90m"
command: |
set -e
cat >docker_commands.sh \<<EOL
# =================== The following code will be executed inside Docker container ===================
set -ex
export SCRIBE_GRAPHQL_ACCESS_TOKEN="${SCRIBE_GRAPHQL_ACCESS_TOKEN}"
${PARALLEL_FLAGS}
cd workspace
EOL
if [[ ${BUILD_ENVIRONMENT} == *"multigpu"* ]]; then
echo ".jenkins/pytorch/multigpu-test.sh" >> docker_commands.sh
elif [[ ${BUILD_ENVIRONMENT} == *caffe2* ]]; then
echo "pip -q install --user -b /tmp/pip_install_onnx \"file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx\"" >> docker_commands.sh
echo ".jenkins/caffe2/test.sh" >> docker_commands.sh
else
echo ".jenkins/pytorch/test.sh" >> docker_commands.sh
fi
echo "(cat docker_commands.sh | docker exec -u jenkins -i "$id" bash) 2>&1" > command.sh
unbuffer bash command.sh | ts
- run:
name: Report results
no_output_timeout: "5m"
command: |
set -e
docker stats --all --no-stream
cat >docker_commands.sh \<<EOL
# =================== The following code will be executed inside Docker container ===================
set -ex
export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}
export SCRIBE_GRAPHQL_ACCESS_TOKEN="${SCRIBE_GRAPHQL_ACCESS_TOKEN}"
export CIRCLE_TAG="${CIRCLE_TAG:-}"
export CIRCLE_SHA1="$CIRCLE_SHA1"
export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
export CIRCLE_BRANCH="$CIRCLE_BRANCH"
cd workspace
python test/print_test_stats.py test
EOL
echo "(cat docker_commands.sh | docker exec -u jenkins -i "$id" bash) 2>&1" > command.sh
unbuffer bash command.sh | ts
echo "Retrieving test reports"
docker cp $id:/var/lib/jenkins/workspace/test/test-reports ./ || echo 'No test reports found!'
when: always
- store_test_results:
path: test-reports
pytorch_windows_build:
<<: *pytorch_windows_params
parameters:
executor:
type: string
default: "windows-xlarge-cpu-with-nvidia-cuda"
build_environment:
type: string
default: ""
test_name:
type: string
default: ""
cuda_version:
type: string
default: "10"
python_version:
type: string
default: "3.6"
vc_version:
type: string
default: "14.16"
vc_year:
type: string
default: "2019"
vc_product:
type: string
default: "BuildTools"
use_cuda:
type: string
default: ""
executor: <<parameters.executor>>
steps:
- checkout
- run:
name: Install Cuda
no_output_timeout: 30m
command: |
if [[ "${USE_CUDA}" == "1" ]]; then
.circleci/scripts/windows_cuda_install.sh
fi
- run:
name: Install Cudnn
command : |
if [[ "${USE_CUDA}" == "1" ]]; then
.circleci/scripts/windows_cudnn_install.sh
fi
- run:
name: Build
no_output_timeout: "90m"
command: |
set -e
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_WIN_BUILD_V1}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
set -x
.jenkins/pytorch/win-build.sh
- persist_to_workspace:
root: "C:/w"
paths: build-results
- store_artifacts:
path: C:/w/build-results
pytorch_windows_test:
<<: *pytorch_windows_params
parameters:
executor:
type: string
default: "windows-medium-cpu-with-nvidia-cuda"
build_environment:
type: string
default: ""
test_name:
type: string
default: ""
cuda_version:
type: string
default: "10"
python_version:
type: string
default: "3.6"
vc_version:
type: string
default: "14.16"
vc_year:
type: string
default: "2019"
vc_product:
type: string
default: "BuildTools"
use_cuda:
type: string
default: ""
executor: <<parameters.executor>>
steps:
- checkout
- attach_workspace:
at: c:/users/circleci/workspace
- run:
name: Install Cuda
no_output_timeout: 30m
command: |
if [[ "${CUDA_VERSION}" != "cpu" ]]; then
if [[ "${CUDA_VERSION}" != "10" || "${JOB_EXECUTOR}" != "windows-with-nvidia-gpu" ]]; then
.circleci/scripts/windows_cuda_install.sh
fi
if [[ "${CUDA_VERSION}" != "10" && "${JOB_EXECUTOR}" == "windows-with-nvidia-gpu" ]]; then
.circleci/scripts/driver_update.bat
fi
fi
- run:
name: Install Cudnn
command : |
if [[ "${CUDA_VERSION}" != "cpu" ]]; then
.circleci/scripts/windows_cudnn_install.sh
fi
- run:
name: Test
no_output_timeout: "30m"
command: |
set -e
export IN_CIRCLECI=1
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_WIN_BUILD_V1}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_WIN_BUILD_V1}
set -x
.jenkins/pytorch/win-test.sh
- store_test_results:
path: test/test-reports
caffe2_linux_build:
<<: *caffe2_params
machine:
image: ubuntu-1604:202007-01
steps:
# See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
cat >/home/circleci/project/ci_build_script.sh \<<EOL
# =================== The following code will be executed inside Docker container ===================
set -ex
export BUILD_ENVIRONMENT="$BUILD_ENVIRONMENT"
# Reinitialize submodules
git submodule sync && git submodule update -q --init --recursive
# conda must be added to the path for Anaconda builds (this location must be
# the same as that in install_anaconda.sh used to build the docker image)
if [[ "${BUILD_ENVIRONMENT}" == conda* ]]; then
export PATH=/opt/conda/bin:$PATH
sudo chown -R jenkins:jenkins '/opt/conda'
fi
# Build
./.jenkins/caffe2/build.sh
# Show sccache stats if it is running
if pgrep sccache > /dev/null; then
sccache --show-stats
fi
# =================== The above code will be executed inside Docker container ===================
EOL
chmod +x /home/circleci/project/ci_build_script.sh
echo "DOCKER_IMAGE: "${DOCKER_IMAGE}
time docker pull ${DOCKER_IMAGE} >/dev/null
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE})
docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && ./ci_build_script.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
# Push intermediate Docker image for next phase to use
if [ -z "${BUILD_ONLY}" ]; then
if [[ "$BUILD_ENVIRONMENT" == *cmake* ]]; then
export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-cmake-${CIRCLE_SHA1}
else
export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-${CIRCLE_SHA1}
fi
docker commit "$id" ${COMMIT_DOCKER_IMAGE}
time docker push ${COMMIT_DOCKER_IMAGE}
fi
caffe2_linux_test:
<<: *caffe2_params
machine:
image: ubuntu-1604:202007-01
steps:
# See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: Test
no_output_timeout: "1h"
command: |
set -e
# TODO: merge this into Caffe2 test.sh
cat >/home/circleci/project/ci_test_script.sh \<<EOL
# =================== The following code will be executed inside Docker container ===================
set -ex
export BUILD_ENVIRONMENT="$BUILD_ENVIRONMENT"
# libdc1394 (dependency of OpenCV) expects /dev/raw1394 to exist...
sudo ln /dev/null /dev/raw1394
# conda must be added to the path for Anaconda builds (this location must be
# the same as that in install_anaconda.sh used to build the docker image)
if [[ "${BUILD_ENVIRONMENT}" == conda* ]]; then
export PATH=/opt/conda/bin:$PATH
fi
# Upgrade SSL module to avoid old SSL warnings
pip -q install --user --upgrade pyOpenSSL ndg-httpsclient pyasn1
pip -q install --user -b /tmp/pip_install_onnx "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
# Build
./.jenkins/caffe2/test.sh
# Remove benign core dumps.
# These are tests for signal handling (including SIGABRT).
rm -f ./crash/core.fatal_signal_as.*
rm -f ./crash/core.logging_test.*
# =================== The above code will be executed inside Docker container ===================
EOL
chmod +x /home/circleci/project/ci_test_script.sh
if [[ "$BUILD_ENVIRONMENT" == *cmake* ]]; then
export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-cmake-${CIRCLE_SHA1}
else
export COMMIT_DOCKER_IMAGE=${DOCKER_IMAGE}-${CIRCLE_SHA1}
fi
echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
if [ -n "${USE_CUDA_DOCKER_RUNTIME}" ]; then
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --gpus all -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
else
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
fi
docker cp /home/circleci/project/. "$id:/var/lib/jenkins/workspace"
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && ./ci_test_script.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
caffe2_macos_build:
<<: *caffe2_params
macos:
xcode: "9.4.1"
steps:
# See Note [Workspace for CircleCI scripts] in job-specs-setup.yml
- checkout
- run_brew_for_macos_build
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
export IN_CIRCLECI=1
brew install cmake
# Reinitialize submodules
git submodule sync && git submodule update -q --init --recursive
# Reinitialize path (see man page for path_helper(8))
eval `/usr/libexec/path_helper -s`
export PATH=/usr/local/opt/python/libexec/bin:/usr/local/bin:$PATH
# Install Anaconda if we need to
if [ -n "${CAFFE2_USE_ANACONDA}" ]; then
rm -rf ${TMPDIR}/anaconda
curl --retry 3 -o ${TMPDIR}/conda.sh https://repo.anaconda.com/miniconda/Miniconda${ANACONDA_VERSION}-latest-MacOSX-x86_64.sh
chmod +x ${TMPDIR}/conda.sh
/bin/bash ${TMPDIR}/conda.sh -b -p ${TMPDIR}/anaconda
rm -f ${TMPDIR}/conda.sh
export PATH="${TMPDIR}/anaconda/bin:${PATH}"
source ${TMPDIR}/anaconda/bin/activate
fi
pip -q install numpy
# Install sccache
sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache --output /usr/local/bin/sccache
sudo chmod +x /usr/local/bin/sccache
export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
# This IAM user allows write access to S3 bucket for sccache
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}
set -x
export SCCACHE_BIN=${PWD}/sccache_bin
mkdir -p ${SCCACHE_BIN}
if which sccache > /dev/null; then
printf "#!/bin/sh\nexec sccache $(which clang++) \$*" > "${SCCACHE_BIN}/clang++"
chmod a+x "${SCCACHE_BIN}/clang++"
printf "#!/bin/sh\nexec sccache $(which clang) \$*" > "${SCCACHE_BIN}/clang"
chmod a+x "${SCCACHE_BIN}/clang"
export PATH="${SCCACHE_BIN}:$PATH"
fi
# Build
if [ "${BUILD_IOS:-0}" -eq 1 ]; then
unbuffer scripts/build_ios.sh 2>&1 | ts
elif [ -n "${CAFFE2_USE_ANACONDA}" ]; then
# All conda build logic should be in scripts/build_anaconda.sh
unbuffer scripts/build_anaconda.sh 2>&1 | ts
else
unbuffer scripts/build_local.sh 2>&1 | ts
fi
# Show sccache stats if it is running
if which sccache > /dev/null; then
sccache --show-stats
fi
binary_linux_build:
<<: *binary_linux_build_params
steps:
- checkout
- calculate_docker_image_tag
- run: