mirror of https://github.com/kubeflow/examples.git
Fix the mnist_gcp_test.py (#741)
* Fix the mnist_gcp_test.py
* The job spec was invalid; we were missing container name
* There were a bunch of other issues as well.
* Pull in the changes from xgboost_synthetic to upload an HTML version
of the notebook output to GCS.
* Add exceptoin
* Revert "Add exceptoin"
This reverts commit 44f34d9d74
.
This commit is contained in:
parent
5b4b0c6c94
commit
b218d2b23c
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@ -56,6 +56,7 @@ workflows:
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include_dirs:
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- xgboost_synthetic/*
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- mnist/*
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- py/kubeflow/examples/notebook_tests
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- py/kubeflow/examples/create_e2e_workflow.py
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# E2E test for various notebooks
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@ -1,4 +1,4 @@
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import fire
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import argparse
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import tempfile
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import logging
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import os
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@ -6,10 +6,13 @@ import subprocess
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logger = logging.getLogger(__name__)
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from google.cloud import storage
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from kubeflow.testing import util
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def prepare_env():
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subprocess.check_call(["pip3", "install", "-U", "papermill"])
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subprocess.check_call(["pip3", "install", "-r", "../requirements.txt"])
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subprocess.check_call(["pip3", "install", "-U", "nbconvert"])
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subprocess.check_call(["pip3", "install", "-U", "nbformat"])
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def execute_notebook(notebook_path, parameters=None):
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import papermill #pylint: disable=import-error
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@ -21,13 +24,32 @@ def execute_notebook(notebook_path, parameters=None):
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log_output=True)
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return notebook_output_path
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def run_notebook_test(notebook_path, expected_messages, parameters=None):
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def _upload_notebook_html(content, target):
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gcs_client = storage.Client()
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bucket_name, path = util.split_gcs_uri(target)
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bucket = gcs_client.get_bucket(bucket_name)
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logging.info("Uploading notebook to %s.", target)
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blob = bucket.blob(path)
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# Need to set content type so that if we browse in GCS we end up rendering
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# as html.
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blob.upload_from_string(content, content_type="text/html")
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def run_notebook_test(notebook_path, parameters=None):
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import nbformat #pylint: disable=import-error
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import nbconvert #pylint: disable=import-error
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output_path = execute_notebook(notebook_path, parameters=parameters)
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actual_output = open(output_path, 'r').read()
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for expected_message in expected_messages:
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if not expected_message in actual_output:
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logger.error(actual_output)
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assert False, "Unable to find from output: " + expected_message
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with open(output_path, "r") as hf:
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actual_output = hf.read()
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nb = nbformat.reads(actual_output, as_version=4)
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html_exporter = nbconvert.HTMLExporter()
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(html_output, _) = html_exporter.from_notebook_node(nb)
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gcs_path = os.getenv("OUTPUT_GCS")
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_upload_notebook_html(html_output, gcs_path)
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class NotebookExecutor:
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@staticmethod
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@ -40,13 +62,7 @@ class NotebookExecutor:
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prepare_env()
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FILE_DIR = os.path.dirname(__file__)
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EXPECTED_MGS = [
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"Finished upload of",
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"Model export success: mockup-model.dat",
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"Pod started running True",
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"Cluster endpoint: http:",
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]
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run_notebook_test(notebook_path, EXPECTED_MGS)
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run_notebook_test(notebook_path)
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO,
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@ -55,4 +71,13 @@ if __name__ == "__main__":
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datefmt='%Y-%m-%dT%H:%M:%S',
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)
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fire.Fire(NotebookExecutor)
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# fire isn't available in the notebook image which is why we aren't
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# using it.
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--notebook_path", default="", type=str, help=("Path to the notebook"))
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args = parser.parse_args()
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NotebookExecutor.test(args.notebook_path)
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@ -1,4 +1,7 @@
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# A batch job to run a notebook using papermill.
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# The YAML is modified by nb_test_util.py to generate a Job specific
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# to a notebook.
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#
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# TODO(jlewi): We should switch to using Tekton
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apiVersion: batch/v1
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kind: Job
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@ -36,8 +39,9 @@ spec:
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- env:
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- name: PYTHONPATH
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value: /src/kubeflow/examples/py/
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- name: executing-notebooks
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name: executing-notebooks
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image: execute-image
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# Command will get overwritten by nb_test_util.py
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command: ["python3", "-m",
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"kubeflow.examples.notebook_tests.execute_notebook",
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"test", "/src/kubeflow/examples/mnist/mnist_gcp.ipynb"]
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@ -1,22 +1,26 @@
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import datetime
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import logging
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import os
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import uuid
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import pytest
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from kubeflow.examples.notebook_tests import nb_test_util
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from kubeflow.testing import util
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# TODO(jlewi): This test is new; there's some work to be done to make it
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# reliable. So for now we mark it as expected to fail in presubmits
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# We only mark it as expected to fail
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# on presubmits because if expected failures don't show up in test grid
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# and we want signal in postsubmits and periodics
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@pytest.mark.xfail(os.getenv("JOB_TYPE") == "presubmit", reason="Flaky")
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def test_mnist_gcp(record_xml_attribute, name, namespace, # pylint: disable=too-many-branches,too-many-statements
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repos, image):
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'''Generate Job and summit.'''
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util.set_pytest_junit(record_xml_attribute, "test_mnist")
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if not name:
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name = "mnist-" + datetime.datetime.now().strftime("%H%M%S") + "-"
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name = name + uuid.uuid4().hex[0:3]
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util.set_pytest_junit(record_xml_attribute, "test_mnist_gcp")
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nb_test_util.run_papermill_job(name, namespace, repos, image)
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notebook_path = "kubeflow/examples/mnist/mnist_gcp.ipynb"
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nb_test_util.run_papermill_job(notebook_path, name, namespace, repos, image)
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if __name__ == "__main__":
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@ -2,23 +2,36 @@
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import datetime
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import logging
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import os
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import uuid
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import tempfile
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import yaml
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from google.cloud import storage
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from kubernetes import client as k8s_client
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from kubeflow.testing import argo_build_util
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from kubeflow.testing import prow_artifacts
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from kubeflow.testing import util
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def run_papermill_job(name, namespace, # pylint: disable=too-many-branches,too-many-statements
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# This is the bucket where the batch jobs will uploaded an HTML version of the
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# notebook will be written to. The K8s job is running in a Kubeflow cluster
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# so it needs to be a bucket that the kubeflow cluster can write to.
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# This is why we don't write directly to the bucket used for prow artifacts
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NB_BUCKET = "kubeflow-ci-deployment"
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PROJECT = "kbueflow-ci-deployment"
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def run_papermill_job(notebook_path, name, namespace, # pylint: disable=too-many-branches,too-many-statements
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repos, image):
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"""Generate a K8s job to run a notebook using papermill
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Args:
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notebook_path: Path to the notebook. This should be in the form
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"{REPO_OWNER}/{REPO}/path/to/notebook.ipynb"
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name: Name for the K8s job
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namespace: The namespace where the job should run.
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repos: (Optional) Which repos to checkout; if not specified tries
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repos: Which repos to checkout; if None or empty tries
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to infer based on PROW environment variables
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image:
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image: The docker image to run the notebook in.
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"""
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util.maybe_activate_service_account()
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with open("job.yaml") as hf:
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job = yaml.load(hf)
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if notebook_path.startswith("/"):
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raise ValueError("notebook_path={0} should not start with /".format(
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notebook_path))
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# We need to checkout the correct version of the code
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# in presubmits and postsubmits. We should check the environment variables
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# for the prow environment variables to get the appropriate values.
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if not repos:
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repos = argo_build_util.get_repo_from_prow_env()
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if not repos:
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raise ValueError("Could not get repos from prow environment variable "
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"and --repos isn't explicitly set")
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repos += ",kubeflow/testing@HEAD"
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logging.info("Repos set to %s", repos)
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job["spec"]["template"]["spec"]["initContainers"][0]["command"] = [
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"/usr/local/bin/checkout_repos.sh",
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"--src_dir=/src",
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"--depth=all",
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]
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job["spec"]["template"]["spec"]["containers"][0]["image"] = image
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full_notebook_path = os.path.join("/src", notebook_path)
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job["spec"]["template"]["spec"]["containers"][0]["command"] = [
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"python3", "-m",
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"kubeflow.examples.notebook_tests.execute_notebook",
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"--notebook_path", full_notebook_path]
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job["spec"]["template"]["spec"]["containers"][0][
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"workingDir"] = os.path.dirname(full_notebook_path)
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# The prow bucket to use for results/artifacts
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prow_bucket = prow_artifacts.PROW_RESULTS_BUCKET
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if os.getenv("REPO_OWNER") and os.getenv("REPO_NAME"):
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# Running under prow
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prow_dir = prow_artifacts.get_gcs_dir(prow_bucket)
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prow_dir = os.path.join(prow_dir, "artifacts")
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if os.getenv("TEST_TARGET_NAME"):
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prow_dir = os.path.join(
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prow_dir, os.getenv("TEST_TARGET_NAME").lstrip("/"))
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prow_bucket, prow_path = util.split_gcs_uri(prow_dir)
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else:
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prow_path = "notebook-test" + datetime.datetime.now().strftime("%H%M%S")
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prow_path = prow_path + "-" + uuid.uuid4().hex[0:3]
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prow_dir = util.to_gcs_uri(prow_bucket, prow_path)
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prow_path = os.path.join(prow_path, name + ".html")
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output_gcs = util.to_gcs_uri(NB_BUCKET, prow_path)
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job["spec"]["template"]["spec"]["containers"][0]["env"] = [
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{"name": "OUTPUT_GCS", "value": output_gcs},
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{"name": "PYTHONPATH",
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"value": "/src/kubeflow/testing/py:/src/kubeflow/examples/py"},
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]
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logging.info("Notebook will be written to %s", output_gcs)
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util.load_kube_config(persist_config=False)
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if name:
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job["metadata"]["name"] = name
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else:
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job["metadata"]["name"] = ("xgboost-test-" +
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job["metadata"]["name"] = ("notebook-test-" +
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datetime.datetime.now().strftime("%H%M%S")
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+ "-" + uuid.uuid4().hex[0:3])
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name = job["metadata"]["name"]
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name = job["metadata"]["name"]
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job["metadata"]["namespace"] = namespace
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logging.info("Final job:\n%s", yaml.safe_dump(final_job.to_dict()))
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# Download notebook html to artifacts
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logging.info("Copying %s to bucket %s", output_gcs, prow_bucket)
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storage_client = storage.Client()
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bucket = storage_client.get_bucket(NB_BUCKET)
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blob = bucket.get_blob(prow_path)
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destination_bucket = storage_client.get_bucket(prow_bucket)
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bucket.copy_blob(blob, destination_bucket)
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if not final_job.status.conditions:
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raise RuntimeError("Job {0}.{1}; did not complete".format(namespace, name))
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if last_condition.type not in ["Complete"]:
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logging.error("Job didn't complete successfully")
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raise RuntimeError("Job {0}.{1} failed".format(namespace, name))
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@ -13,7 +13,6 @@ def prepare_env():
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subprocess.check_call(["pip3", "install", "-U", "nbformat"])
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subprocess.check_call(["pip3", "install", "-r", "../requirements.txt"])
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def execute_notebook(notebook_path, parameters=None):
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temp_dir = tempfile.mkdtemp()
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notebook_output_path = os.path.join(temp_dir, "out.ipynb")
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