diff --git a/backend/Dockerfile b/backend/Dockerfile index 59fb7799f4f..c76c5f72fdd 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -29,7 +29,7 @@ COPY ./samples . #I think it's better to just use a shell loop though. #RUN for pipeline in $(find . -maxdepth 2 -name '*.py' -type f); do dsl-compile --py "$pipeline" --output "$pipeline.tar.gz"; done #The "for" loop breaks on all whitespace, so we either need to override IFS or use the "read" command instead. -RUN find . -maxdepth 2 -name '*.py' -type f | while read pipeline; do dsl-compile --py "$pipeline" --output "$pipeline.tar.gz"; done +RUN find . -maxdepth 3 -name '*.py' -type f | while read pipeline; do dsl-compile --py "$pipeline" --output "$pipeline.tar.gz"; done FROM debian:stretch diff --git a/backend/src/apiserver/config/sample_config.json b/backend/src/apiserver/config/sample_config.json index 8c2c96df797..dafe1ff0d28 100644 --- a/backend/src/apiserver/config/sample_config.json +++ b/backend/src/apiserver/config/sample_config.json @@ -1,32 +1,32 @@ [ { "name":"[Sample] ML - XGBoost - Training with Confusion Matrix", - "description":"A trainer that does end-to-end distributed training for XGBoost models. For source code, refer to https://github.com/kubeflow/pipelines/tree/master/samples/xgboost-spark", - "file":"/samples/xgboost-spark/xgboost-training-cm.py.tar.gz" + "description":"A trainer that does end-to-end distributed training for XGBoost models. For source code, refer to https://github.com/kubeflow/pipelines/tree/master/samples/core/xgboost-spark", + "file":"/samples/core/xgboost-spark/xgboost-training-cm.py.tar.gz" }, { "name":"[Sample] ML - TFX - Taxi Tip Prediction Model Trainer", - "description":"Example pipeline that does classification with model analysis based on a public tax cab BigQuery dataset. For source code, refer to https://github.com/kubeflow/pipelines/tree/master/samples/tfx", - "file":"/samples/tfx/taxi-cab-classification-pipeline.py.tar.gz" + "description":"Example pipeline that does classification with model analysis based on a public tax cab BigQuery dataset. For source code, refer to https://github.com/kubeflow/pipelines/tree/master/samples/core/tfx", + "file":"/samples/core/tfx/taxi-cab-classification-pipeline.py.tar.gz" }, { "name":"[Sample] Basic - Sequential execution", - "description":"A pipeline with two sequential steps. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/basic/sequential.py", - "file":"/samples/basic/sequential.py.tar.gz" + "description":"A pipeline with two sequential steps. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/core/sequential/sequential.py", + "file":"/samples/core/sequential/sequential.py.tar.gz" }, { "name":"[Sample] Basic - Parallel execution", - "description":"A pipeline that downloads two messages in parallel and prints the concatenated result. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/basic/parallel_join.py", - "file":"/samples/basic/parallel_join.py.tar.gz" + "description":"A pipeline that downloads two messages in parallel and prints the concatenated result. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/core/parallel_join/parallel_join.py", + "file":"/samples/core/parallel_join/parallel_join.py.tar.gz" }, { "name":"[Sample] Basic - Conditional execution", - "description":"A pipeline shows how to use dsl.Condition. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/basic/condition.py", - "file":"/samples/basic/condition.py.tar.gz" + "description":"A pipeline shows how to use dsl.Condition. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/core/condition/condition.py", + "file":"/samples/core/condition/condition.py.tar.gz" }, { "name":"[Sample] Basic - Exit Handler", - "description":"A pipeline that downloads a message and prints it out. Exit Handler will run at the end. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/basic/exit_handler.py", - "file":"/samples/basic/exit_handler.py.tar.gz" + "description":"A pipeline that downloads a message and prints it out. Exit Handler will run at the end. For source code, refer to https://github.com/kubeflow/pipelines/blob/master/samples/core/exit_handler/exit_handler.py", + "file":"/samples/core/exit_handler/exit_handler.py.tar.gz" } ] \ No newline at end of file diff --git a/samples/README.md b/samples/README.md index 0b4c281c4be..336326cf6a8 100644 --- a/samples/README.md +++ b/samples/README.md @@ -1,3 +1,35 @@ The sample pipelines give you a quick start to building and deploying machine learning pipelines with Kubeflow. * Follow the guide to [deploy the Kubeflow pipelines service](https://www.kubeflow.org/docs/guides/pipelines/deploy-pipelines-service/). * Build and deploy your pipeline [using the provided samples](https://www.kubeflow.org/docs/guides/pipelines/pipelines-samples/). + + + + +This page tells you how to use the _basic_ sample pipelines contained in the repo. + +## Compile the pipeline specification + +Follow the guide to [building a pipeline](https://www.kubeflow.org/docs/guides/pipelines/build-pipeline/) to install the Kubeflow Pipelines SDK and compile the sample Python into a workflow specification. The specification takes the form of a YAML file compressed into a `.tar.gz` file. + +For convenience, you can download a pre-compiled, compressed YAML file containing the +specification of the `core/sequential.py` pipeline. This saves you the steps required +to compile and compress the pipeline specification: +[sequential.tar.gz](https://storage.googleapis.com/sample-package/sequential.tar.gz) + +## Deploy + +Open the Kubeflow pipelines UI, and follow the prompts to create a new pipeline and upload the generated workflow +specification, `my-pipeline.tar.gz` (example: `sequential.tar.gz`). + +## Run + +Follow the pipeline UI to create pipeline runs. + +Useful parameter values: + +* For the "exit_handler" and "sequential" samples: `gs://ml-pipeline-playground/shakespeare1.txt` +* For the "parallel_join" sample: `gs://ml-pipeline-playground/shakespeare1.txt` and `gs://ml-pipeline-playground/shakespeare2.txt` + +## Components source + +All samples use pre-built components. The command to run for each container is built into the pipeline file. diff --git a/samples/basic/README.md b/samples/basic/README.md deleted file mode 100644 index f63430ca48e..00000000000 --- a/samples/basic/README.md +++ /dev/null @@ -1,30 +0,0 @@ - - -This page tells you how to use the _basic_ sample pipelines contained in the repo. - -## Compile the pipeline specification - -Follow the guide to [building a pipeline](https://www.kubeflow.org/docs/guides/pipelines/build-pipeline/) to install the Kubeflow Pipelines SDK and compile the sample Python into a workflow specification. The specification takes the form of a YAML file compressed into a `.tar.gz` file. - -For convenience, you can download a pre-compiled, compressed YAML file containing the -specification of the `sequential.py` pipeline. This saves you the steps required -to compile and compress the pipeline specification: -[sequential.tar.gz](https://storage.googleapis.com/sample-package/sequential.tar.gz) - -## Deploy - -Open the Kubeflow pipelines UI, and follow the prompts to create a new pipeline and upload the generated workflow -specification, `my-pipeline.tar.gz` (example: `sequential.tar.gz`). - -## Run - -Follow the pipeline UI to create pipeline runs. - -Useful parameter values: - -* For the "exit_handler" and "sequential" samples: `gs://ml-pipeline-playground/shakespeare1.txt` -* For the "parallel_join" sample: `gs://ml-pipeline-playground/shakespeare1.txt` and `gs://ml-pipeline-playground/shakespeare2.txt` - -## Components source - -All samples use pre-built components. The command to run for each container is built into the pipeline file. diff --git a/samples/ai-platform/Chicago Crime Pipeline.ipynb b/samples/contrib/ai-platform/Chicago Crime Pipeline.ipynb similarity index 100% rename from samples/ai-platform/Chicago Crime Pipeline.ipynb rename to samples/contrib/ai-platform/Chicago Crime Pipeline.ipynb diff --git a/samples/ai-platform/Chicago Crime Research.ipynb b/samples/contrib/ai-platform/Chicago Crime Research.ipynb similarity index 100% rename from samples/ai-platform/Chicago Crime Research.ipynb rename to samples/contrib/ai-platform/Chicago Crime Research.ipynb diff --git a/samples/ai-platform/README.md b/samples/contrib/ai-platform/README.md similarity index 100% rename from samples/ai-platform/README.md rename to samples/contrib/ai-platform/README.md diff --git a/samples/ai-platform/ai_platform_training/trainer/__init__.py b/samples/contrib/ai-platform/__init__.py old mode 100755 new mode 100644 similarity index 100% rename from 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samples/core/tfx/taxi-cab-classification/schema.json diff --git a/samples/tfx/taxi-cab-classification/train.csv b/samples/core/tfx/taxi-cab-classification/train.csv similarity index 100% rename from samples/tfx/taxi-cab-classification/train.csv rename to samples/core/tfx/taxi-cab-classification/train.csv diff --git a/samples/volumes/README.md b/samples/core/volume_ops/README.md similarity index 100% rename from samples/volumes/README.md rename to samples/core/volume_ops/README.md diff --git a/samples/volumes/volumeop_basic.py b/samples/core/volume_ops/volumeop_basic.py similarity index 100% rename from samples/volumes/volumeop_basic.py rename to samples/core/volume_ops/volumeop_basic.py diff --git a/samples/volumes/volumeop_dag.py b/samples/core/volume_ops/volumeop_dag.py similarity index 100% rename from samples/volumes/volumeop_dag.py rename to samples/core/volume_ops/volumeop_dag.py diff --git a/samples/volumes/volumeop_parallel.py b/samples/core/volume_ops/volumeop_parallel.py similarity index 100% rename from samples/volumes/volumeop_parallel.py rename to samples/core/volume_ops/volumeop_parallel.py diff --git a/samples/volumes/volumeop_sequential.py b/samples/core/volume_ops/volumeop_sequential.py similarity index 100% rename from samples/volumes/volumeop_sequential.py rename to samples/core/volume_ops/volumeop_sequential.py diff --git a/samples/snapshots/README.md b/samples/core/volume_snapshot_ops/README.md similarity index 100% rename from samples/snapshots/README.md rename to samples/core/volume_snapshot_ops/README.md diff --git a/samples/snapshots/volume_snapshotop_rokurl.py b/samples/core/volume_snapshot_ops/volume_snapshotop_rokurl.py similarity index 100% rename from samples/snapshots/volume_snapshotop_rokurl.py rename to samples/core/volume_snapshot_ops/volume_snapshotop_rokurl.py diff --git a/samples/snapshots/volume_snapshotop_sequential.py b/samples/core/volume_snapshot_ops/volume_snapshotop_sequential.py similarity index 100% rename from samples/snapshots/volume_snapshotop_sequential.py rename to samples/core/volume_snapshot_ops/volume_snapshotop_sequential.py diff --git a/samples/xgboost-spark/README.md b/samples/core/xgboost-spark/README.md similarity index 100% rename from samples/xgboost-spark/README.md rename to samples/core/xgboost-spark/README.md diff --git a/samples/xgboost-spark/xgboost-training-cm.py b/samples/core/xgboost-spark/xgboost-training-cm.py similarity index 100% rename from samples/xgboost-spark/xgboost-training-cm.py rename to samples/core/xgboost-spark/xgboost-training-cm.py diff --git a/samples/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/model_files/__init__.py b/samples/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/model_files/__init__.py deleted file mode 100644 index 8b137891791..00000000000 --- a/samples/ibm-samples/ffdl-seldon/source/seldon-pytorch-serving-image/model_files/__init__.py +++ /dev/null @@ -1 +0,0 @@ - diff --git a/test/sample-test/run_test.sh b/test/sample-test/run_test.sh index 539bccb618b..8ba59a85985 100755 --- a/test/sample-test/run_test.sh +++ b/test/sample-test/run_test.sh @@ -137,7 +137,7 @@ if [ "$TEST_NAME" == 'tf-training' ]; then #TODO: convert the sed commands to sed -e 's|gcr.io/ml-pipeline/|gcr.io/ml-pipeline-test/' and tag replacement. # Compile samples - cd ${BASE_DIR}/samples/kubeflow-tf + cd ${BASE_DIR}/samples/core/kubeflow-tf if [ -n "${DATAFLOW_TFT_IMAGE}" ];then sed -i -e "s|gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:\([a-zA-Z0-9_.-]\)\+|${DATAFLOW_TFT_IMAGE}|g" kubeflow-training-classification.py @@ -149,7 +149,7 @@ if [ "$TEST_NAME" == 'tf-training' ]; then dsl-compile --py kubeflow-training-classification.py --output kubeflow-training-classification.zip cd "${TEST_DIR}" - python3 run_kubeflow_test.py --input ${BASE_DIR}/samples/kubeflow-tf/kubeflow-training-classification.zip --result $SAMPLE_KUBEFLOW_TEST_RESULT --output $SAMPLE_KUBEFLOW_TEST_OUTPUT --namespace ${NAMESPACE} + python3 run_kubeflow_test.py --input ${BASE_DIR}/samples/core/kubeflow-tf/kubeflow-training-classification.zip --result $SAMPLE_KUBEFLOW_TEST_RESULT --output $SAMPLE_KUBEFLOW_TEST_OUTPUT --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_KUBEFLOW_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_KUBEFLOW_TEST_RESULT} @@ -158,7 +158,7 @@ elif [ "$TEST_NAME" == "tfx" ]; then SAMPLE_TFX_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/tfx + cd ${BASE_DIR}/samples/core/tfx dsl-compile --py taxi-cab-classification-pipeline.py --output taxi-cab-classification-pipeline.yaml @@ -175,7 +175,7 @@ elif [ "$TEST_NAME" == "tfx" ]; then fi cd "${TEST_DIR}" - python3 run_tfx_test.py --input ${BASE_DIR}/samples/tfx/taxi-cab-classification-pipeline.yaml --result $SAMPLE_TFX_TEST_RESULT --output $SAMPLE_TFX_TEST_OUTPUT --namespace ${NAMESPACE} + python3 run_tfx_test.py --input ${BASE_DIR}/samples/core/tfx/taxi-cab-classification-pipeline.yaml --result $SAMPLE_TFX_TEST_RESULT --output $SAMPLE_TFX_TEST_OUTPUT --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_TFX_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_TFX_TEST_RESULT} elif [ "$TEST_NAME" == "sequential" ]; then @@ -183,11 +183,11 @@ elif [ "$TEST_NAME" == "sequential" ]; then SAMPLE_SEQUENTIAL_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/basic + cd ${BASE_DIR}/samples/core/sequential dsl-compile --py sequential.py --output sequential.zip cd "${TEST_DIR}" - python3 run_basic_test.py --input ${BASE_DIR}/samples/basic/sequential.zip --result $SAMPLE_SEQUENTIAL_TEST_RESULT --output $SAMPLE_SEQUENTIAL_TEST_OUTPUT --testname sequential --namespace ${NAMESPACE} + python3 run_basic_test.py --input ${BASE_DIR}/samples/core/sequential/sequential.zip --result $SAMPLE_SEQUENTIAL_TEST_RESULT --output $SAMPLE_SEQUENTIAL_TEST_OUTPUT --testname sequential --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_SEQUENTIAL_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_SEQUENTIAL_TEST_RESULT} @@ -196,11 +196,11 @@ elif [ "$TEST_NAME" == "condition" ]; then SAMPLE_CONDITION_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/basic + cd ${BASE_DIR}/samples/core/condition dsl-compile --py condition.py --output condition.zip cd "${TEST_DIR}" - python3 run_basic_test.py --input ${BASE_DIR}/samples/basic/condition.zip --result $SAMPLE_CONDITION_TEST_RESULT --output $SAMPLE_CONDITION_TEST_OUTPUT --testname condition --namespace ${NAMESPACE} + python3 run_basic_test.py --input ${BASE_DIR}/samples/core/condition/condition.zip --result $SAMPLE_CONDITION_TEST_RESULT --output $SAMPLE_CONDITION_TEST_OUTPUT --testname condition --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_CONDITION_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_CONDITION_TEST_RESULT} @@ -209,11 +209,11 @@ elif [ "$TEST_NAME" == "exithandler" ]; then SAMPLE_EXIT_HANDLER_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/basic + cd ${BASE_DIR}/samples/core/exit_handler dsl-compile --py exit_handler.py --output exit_handler.zip cd "${TEST_DIR}" - python3 run_basic_test.py --input ${BASE_DIR}/samples/basic/exit_handler.zip --result $SAMPLE_EXIT_HANDLER_TEST_RESULT --output $SAMPLE_EXIT_HANDLER_TEST_OUTPUT --testname exithandler --namespace ${NAMESPACE} + python3 run_basic_test.py --input ${BASE_DIR}/samples/core/exit_handler/exit_handler.zip --result $SAMPLE_EXIT_HANDLER_TEST_RESULT --output $SAMPLE_EXIT_HANDLER_TEST_OUTPUT --testname exithandler --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_EXIT_HANDLER_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_EXIT_HANDLER_TEST_RESULT} @@ -222,11 +222,11 @@ elif [ "$TEST_NAME" == "paralleljoin" ]; then SAMPLE_PARALLEL_JOIN_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/basic + cd ${BASE_DIR}/samples/core/parallel_join dsl-compile --py parallel_join.py --output parallel_join.zip cd "${TEST_DIR}" - python3 run_basic_test.py --input ${BASE_DIR}/samples/basic/parallel_join.zip --result $SAMPLE_PARALLEL_JOIN_TEST_RESULT --output $SAMPLE_PARALLEL_JOIN_TEST_OUTPUT --testname paralleljoin --namespace ${NAMESPACE} + python3 run_basic_test.py --input ${BASE_DIR}/samples/core/parallel_join/parallel_join.zip --result $SAMPLE_PARALLEL_JOIN_TEST_RESULT --output $SAMPLE_PARALLEL_JOIN_TEST_OUTPUT --testname paralleljoin --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_PARALLEL_JOIN_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_PARALLEL_JOIN_TEST_RESULT} @@ -235,11 +235,11 @@ elif [ "$TEST_NAME" == "recursion" ]; then SAMPLE_RECURSION_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/basic + cd ${BASE_DIR}/samples/core/recursion dsl-compile --py recursion.py --output recursion.tar.gz cd "${TEST_DIR}" - python3 run_basic_test.py --input ${BASE_DIR}/samples/basic/recursion.tar.gz --result $SAMPLE_RECURSION_TEST_RESULT --output $SAMPLE_RECURSION_TEST_OUTPUT --testname recursion --namespace ${NAMESPACE} + python3 run_basic_test.py --input ${BASE_DIR}/samples/core/recursion/recursion.tar.gz --result $SAMPLE_RECURSION_TEST_RESULT --output $SAMPLE_RECURSION_TEST_OUTPUT --testname recursion --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_RECURSION_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_RECURSION_TEST_RESULT} @@ -248,7 +248,7 @@ elif [ "$TEST_NAME" == "xgboost" ]; then SAMPLE_XGBOOST_TEST_OUTPUT=${RESULTS_GCS_DIR} # Compile samples - cd ${BASE_DIR}/samples/xgboost-spark + cd ${BASE_DIR}/samples/core/xgboost-spark dsl-compile --py xgboost-training-cm.py --output xgboost-training-cm.yaml @@ -263,7 +263,7 @@ elif [ "$TEST_NAME" == "xgboost" ]; then sed -i -e "s|gcr.io/ml-pipeline/ml-pipeline-local-roc:\([a-zA-Z0-9_.-]\)\+|${LOCAL_ROC_IMAGE}|g" xgboost-training-cm.yaml fi cd "${TEST_DIR}" - python3 run_xgboost_test.py --input ${BASE_DIR}/samples/xgboost-spark/xgboost-training-cm.yaml --result $SAMPLE_XGBOOST_TEST_RESULT --output $SAMPLE_XGBOOST_TEST_OUTPUT --namespace ${NAMESPACE} + python3 run_xgboost_test.py --input ${BASE_DIR}/samples/core/xgboost-spark/xgboost-training-cm.yaml --result $SAMPLE_XGBOOST_TEST_RESULT --output $SAMPLE_XGBOOST_TEST_OUTPUT --namespace ${NAMESPACE} echo "Copy the test results to GCS ${RESULTS_GCS_DIR}/" gsutil cp ${SAMPLE_XGBOOST_TEST_RESULT} ${RESULTS_GCS_DIR}/${SAMPLE_XGBOOST_TEST_RESULT} @@ -275,7 +275,7 @@ elif [ "$TEST_NAME" == "notebook-tfx" ]; then DEPLOYER_MODEL=`cat /proc/sys/kernel/random/uuid` DEPLOYER_MODEL=Notebook_tfx_taxi_`echo ${DEPLOYER_MODEL//-/_}` - cd ${BASE_DIR}/samples/notebooks + cd ${BASE_DIR}/samples/core/kubeflow_pipeline_using_TFX_OSS_components export LC_ALL=C.UTF-8 export LANG=C.UTF-8 if [ -n "${DATAFLOW_TFT_IMAGE}" ];then @@ -310,7 +310,7 @@ elif [ "$TEST_NAME" == "notebook-lightweight" ]; then SAMPLE_NOTEBOOK_LIGHTWEIGHT_TEST_RESULT=junit_SampleNotebookLightweightOutput.xml SAMPLE_NOTEBOOK_LIGHTWEIGHT_TEST_OUTPUT=${RESULTS_GCS_DIR} - cd ${BASE_DIR}/samples/notebooks + cd ${BASE_DIR}/samples/core/lightweight_component export LC_ALL=C.UTF-8 export LANG=C.UTF-8 papermill --prepare-only -p EXPERIMENT_NAME notebook-lightweight -p PROJECT_NAME ml-pipeline-test -p KFP_PACKAGE /tmp/kfp.tar.gz Lightweight\ Python\ components\ -\ basics.ipynb notebook-lightweight.ipynb @@ -327,7 +327,7 @@ elif [ "$TEST_NAME" == "notebook-typecheck" ]; then SAMPLE_NOTEBOOK_TYPECHECK_TEST_RESULT=junit_SampleNotebookTypecheckOutput.xml SAMPLE_NOTEBOOK_TYPECHECK_TEST_OUTPUT=${RESULTS_GCS_DIR} - cd ${BASE_DIR}/samples/notebooks + cd ${BASE_DIR}/samples/core/dsl_static_type_checking export LC_ALL=C.UTF-8 export LANG=C.UTF-8 papermill --prepare-only -p KFP_PACKAGE /tmp/kfp.tar.gz DSL\ Static\ Type\ Checking.ipynb notebook-typecheck.ipynb