120 lines
5.2 KiB
YAML
120 lines
5.2 KiB
YAML
version: 2.1
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orbs:
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gcp-gke: circleci/gcp-gke@1.0.4
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go: circleci/go@1.3.0
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# TPU REFERENCES
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references:
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checkout_ml_testing: &checkout_ml_testing
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run:
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name: Checkout ml-testing-accelerators
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command: |
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git clone https://github.com/GoogleCloudPlatform/ml-testing-accelerators.git
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cd ml-testing-accelerators
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git fetch origin 5e88ac24f631c27045e62f0e8d5dfcf34e425e25:stable
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git checkout stable
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build_push_docker: &build_push_docker
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run:
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name: Configure Docker
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command: |
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gcloud --quiet auth configure-docker
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cd docker/transformers-pytorch-tpu
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if [ -z "$CIRCLE_PR_NUMBER" ]; then docker build --tag "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID" -f Dockerfile --build-arg "TEST_IMAGE=1" . ; else docker build --tag "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID" -f Dockerfile --build-arg "TEST_IMAGE=1" --build-arg "GITHUB_REF=pull/$CIRCLE_PR_NUMBER/head" . ; fi
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docker push "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID"
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deploy_cluster: &deploy_cluster
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run:
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name: Deploy the job on the kubernetes cluster
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command: |
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go get github.com/google/go-jsonnet/cmd/jsonnet && \
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export PATH=$PATH:$HOME/go/bin && \
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kubectl create -f docker/transformers-pytorch-tpu/dataset.yaml || true && \
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job_name=$(jsonnet -J ml-testing-accelerators/ docker/transformers-pytorch-tpu/bert-base-cased.jsonnet --ext-str image=$GCR_IMAGE_PATH --ext-str image-tag=$CIRCLE_WORKFLOW_JOB_ID | kubectl create -f -) && \
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job_name=${job_name#job.batch/} && \
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job_name=${job_name% created} && \
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echo "Waiting on kubernetes job: $job_name" && \
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i=0 && \
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# 30 checks spaced 30s apart = 900s total.
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max_checks=30 && \
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status_code=2 && \
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# Check on the job periodically. Set the status code depending on what
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# happened to the job in Kubernetes. If we try max_checks times and
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# still the job hasn't finished, give up and return the starting
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# non-zero status code.
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while [ $i -lt $max_checks ]; do ((i++)); if kubectl get jobs $job_name -o jsonpath='Failed:{.status.failed}' | grep "Failed:1"; then status_code=1 && break; elif kubectl get jobs $job_name -o jsonpath='Succeeded:{.status.succeeded}' | grep "Succeeded:1" ; then status_code=0 && break; else echo "Job not finished yet"; fi; sleep 30; done && \
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echo "Done waiting. Job status code: $status_code" && \
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pod_name=$(kubectl get po -l controller-uid=`kubectl get job $job_name -o "jsonpath={.metadata.labels.controller-uid}"` | awk 'match($0,!/NAME/) {print $1}') && \
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echo "GKE pod name: $pod_name" && \
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kubectl logs -f $pod_name --container=train
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echo "Done with log retrieval attempt." && \
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gcloud container images delete "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID" --force-delete-tags && \
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exit $status_code
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delete_gke_jobs: &delete_gke_jobs
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run:
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name: Delete GKE Jobs
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command: |
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# Match jobs whose age matches patterns like '1h' or '1d', i.e. any job
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# that has been around longer than 1hr. First print all columns for
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# matches, then execute the delete.
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kubectl get job | awk 'match($4,/[0-9]+[dh]/) {print $0}'
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kubectl delete job $(kubectl get job | awk 'match($4,/[0-9]+[dh]/) {print $1}')
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jobs:
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check_code_quality:
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working_directory: ~/transformers
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docker:
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- image: circleci/python:3.6
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resource_class: medium
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parallelism: 1
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steps:
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- checkout
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- restore_cache:
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keys:
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- v0.4-code_quality-{{ checksum "setup.py" }}
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- v0.4-{{ checksum "setup.py" }}
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- run: pip install --upgrade pip
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- run:
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command: |
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set +e
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echo "my experiment is here"
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# emulate failure
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false
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echo "it can safely fail"
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some non existing command
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echo "should still reach here"
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some non existing command again
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echo "should still reach here too"
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false
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- run:
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when: always
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command: |
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echo "forcing success for this experiment"
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check_repository_consistency:
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working_directory: ~/transformers
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docker:
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- image: circleci/python:3.6
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resource_class: small
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parallelism: 1
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steps:
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- checkout
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- run: pip install requests
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- run: python ./utils/link_tester.py
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workflow_filters: &workflow_filters
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filters:
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branches:
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only:
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- master
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workflows:
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version: 2
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build_and_test:
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jobs:
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- check_code_quality
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- check_repository_consistency
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