config.yml

version: 2.1
orbs:
    gcp-gke: circleci/gcp-gke@1.0.4
    go: circleci/go@1.3.0

# TPU REFERENCES
references:
    checkout_ml_testing: &checkout_ml_testing
        run:
            name: Checkout ml-testing-accelerators
            command: |
                git clone https://github.com/GoogleCloudPlatform/ml-testing-accelerators.git
                cd ml-testing-accelerators
                git fetch origin 5e88ac24f631c27045e62f0e8d5dfcf34e425e25:stable
                git checkout stable
    build_push_docker: &build_push_docker
        run:
            name: Configure Docker
            command: |
                gcloud --quiet auth configure-docker
                cd docker/transformers-pytorch-tpu
                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
                docker push "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID"
    deploy_cluster: &deploy_cluster
        run:
            name: Deploy the job on the kubernetes cluster
            command: |
                go get github.com/google/go-jsonnet/cmd/jsonnet && \
                export PATH=$PATH:$HOME/go/bin && \
                kubectl create -f docker/transformers-pytorch-tpu/dataset.yaml || true && \
                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=$CIRCLE_WORKFLOW_JOB_ID | kubectl create -f -) && \
                job_name=${job_name#job.batch/} && \
                job_name=${job_name% created} && \
                echo "Waiting on kubernetes job: $job_name" && \
                i=0 && \
                # 30 checks spaced 30s apart = 900s total.
                max_checks=30 && \
                status_code=2 && \
                # Check on the job periodically. Set the status code depending on what
                # happened to the job in Kubernetes. If we try max_checks times and
                # still the job hasn't finished, give up and return the starting
                # non-zero status code.
                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 && \
                echo "Done waiting. Job status code: $status_code" && \
                pod_name=$(kubectl get po -l controller-uid=`kubectl get job $job_name -o "jsonpath={.metadata.labels.controller-uid}"` | awk 'match($0,!/NAME/) {print $1}') && \
                echo "GKE pod name: $pod_name" && \
                kubectl logs -f $pod_name --container=train
                echo "Done with log retrieval attempt." && \
                gcloud container images delete "$GCR_IMAGE_PATH:$CIRCLE_WORKFLOW_JOB_ID" --force-delete-tags && \
                exit $status_code
    delete_gke_jobs: &delete_gke_jobs
        run:
            name: Delete GKE Jobs
            command: |
                # Match jobs whose age matches patterns like '1h' or '1d', i.e. any job
                # that has been around longer than 1hr. First print all columns for
                # matches, then execute the delete.
                kubectl get job | awk 'match($4,/[0-9]+[dh]/) {print $0}'
                kubectl delete job $(kubectl get job | awk 'match($4,/[0-9]+[dh]/) {print $1}')




jobs:
    run_tests_torch_and_tf:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-torch_and_tf-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install git+https://github.com/huggingface/datasets
            - run: pip install .[sklearn,tf-cpu,torch,testing]
            - run: pip install codecov pytest-cov
            - save_cache:
                key: v0.3-{{ checksum "setup.py" }}
                paths:
                    - '~/.cache/pip'
            - run: python -m pytest -n 8 --dist=loadfile -rA -s ./tests/ --cov --durations=0 | tee output.txt
            - run: codecov
            - store_artifacts:
                  path: ~/transformers/output.txt
                  destination: test_output.txt
    run_tests_torch:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.7
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-torch-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install git+https://github.com/huggingface/datasets
            - run: pip install .[sklearn,torch,testing]
            - save_cache:
                  key: v0.3-torch-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: python -m pytest -n 8 --dist=loadfile -rA -s ./tests/ | tee output.txt
            - store_artifacts:
                  path: ~/transformers/output.txt
                  destination: test_output.txt
    run_tests_tf:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.7
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-tf-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install git+https://github.com/huggingface/datasets
            - run: pip install .[sklearn,tf-cpu,testing]
            - save_cache:
                  key: v0.3-tf-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: python -m pytest -n 8 --dist=loadfile -rA -s ./tests/ | tee output.txt
            - store_artifacts:
               path: ~/transformers/output.txt
               destination: test_output.txt
    run_tests_flax:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.7
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                keys:
                    - v0.3-flax-{{ checksum "setup.py" }}
                    - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install git+https://github.com/huggingface/datasets
            - run: sudo pip install .[flax,sklearn,torch,testing]
            - save_cache:
                  key: v0.3-flax-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: python -m pytest -n 8 --dist=loadfile -rA -s ./tests/ | tee output.txt
            - store_artifacts:
                  path: ~/transformers/output.txt
                  destination: test_output.txt
    run_tests_custom_tokenizers:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        environment:
            RUN_CUSTOM_TOKENIZERS: yes
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-custom_tokenizers-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install .[ja,testing]
            - run: python -m unidic download
            - save_cache:
                  key: v0.3-custom_tokenizers-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: python -m pytest -s ./tests/test_tokenization_bert_japanese.py | tee output.txt
            - store_artifacts:
                path: ~/transformers/output.txt
                destination: test_output.txt
    run_examples_torch:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-torch_examples-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install .[sklearn,torch,testing]
            - run: pip install -r examples/requirements.txt
            - save_cache:
                  key: v0.3-torch_examples-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: python -m pytest -n 8 --dist=loadfile -rA -s ./examples/ | tee output.txt
            - store_artifacts:
                  path: ~/transformers/output.txt
                  destination: test_output.txt
    build_doc:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-build_doc-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install .[tf,torch,sentencepiece,docs]
            - save_cache:
                  key: v0.3-build_doc-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: cd docs && make html SPHINXOPTS="-W"
            - store_artifacts:
                path: ./docs/_build
    deploy_doc:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        steps:
            - add_ssh_keys:
                fingerprints:
                    - "5b:7a:95:18:07:8c:aa:76:4c:60:35:88:ad:60:56:71"
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-deploy_doc-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install .[tf,torch,sentencepiece,docs]
            - save_cache:
                  key: v0.3-deploy_doc-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: ./.circleci/deploy.sh
    check_code_quality:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        resource_class: medium
        parallelism: 1
        steps:
            - checkout
            - restore_cache:
                  keys:
                      - v0.3-code_quality-{{ checksum "setup.py" }}
                      - v0.3-{{ checksum "setup.py" }}
            - run: pip install --upgrade pip
            - run: pip install isort
            - run: pip install .[tf,torch,quality]
            - save_cache:
                  key: v0.3-code_quality-{{ checksum "setup.py" }}
                  paths:
                      - '~/.cache/pip'
            - run: black --check examples templates tests src utils
            - run: isort --check-only examples templates tests src utils
            - run: flake8 examples templates tests src utils
            - run: python utils/check_copies.py
            - run: python utils/check_dummies.py
            - run: python utils/check_repo.py
    check_repository_consistency:
        working_directory: ~/transformers
        docker:
            - image: circleci/python:3.6
        resource_class: small
        parallelism: 1
        steps:
            - checkout
            - run: pip install requests
            - run: python ./utils/link_tester.py

# TPU JOBS
    run_examples_tpu:
        docker:
            - image: circleci/python:3.6
        environment:
            OMP_NUM_THREADS: 1
        resource_class: xlarge
        parallelism: 1
        steps:
            - checkout
            - go/install
            - *checkout_ml_testing
            - gcp-gke/install
            - gcp-gke/update-kubeconfig-with-credentials:
                  cluster: $GKE_CLUSTER
                  perform-login: true
            - setup_remote_docker
            - *build_push_docker
            - *deploy_cluster
    cleanup-gke-jobs:
        docker:
            - image: circleci/python:3.6
        steps:
            - gcp-gke/install
            - gcp-gke/update-kubeconfig-with-credentials:
                  cluster: $GKE_CLUSTER
                  perform-login: true
            - *delete_gke_jobs
workflow_filters: &workflow_filters
    filters:
        branches:
            only:
                - master
workflows:
    version: 2
    build_and_test:
        jobs:
            - check_code_quality
            - check_repository_consistency
            - run_examples_torch
            - run_tests_custom_tokenizers
            - run_tests_torch_and_tf
            - run_tests_torch
            - run_tests_tf
            - run_tests_flax
            - build_doc
            - deploy_doc: *workflow_filters
    tpu_testing_jobs:
        triggers:
            - schedule:
                # Set to run at the first minute of every hour.
                cron: "0 8 * * *"
                filters:
                    branches:
                        only:
                            - master
        jobs:
            - cleanup-gke-jobs
            - run_examples_tpu