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			fix import issue in the mnist e2e testing (#531)
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			@ -23,7 +23,7 @@ import logging
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import os
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from kubernetes import client as k8s_client
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from py import test_runner #pylint: disable=no-name-in-module
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from kubeflow.tf_operator import test_runner #pylint: disable=no-name-in-module
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from kubeflow.testing import ks_util
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from kubeflow.testing import test_util
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			@ -28,8 +28,8 @@ import logging
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import os
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from kubernetes import client as k8s_client
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from py import tf_job_client #pylint: disable=no-name-in-module
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from py import test_runner #pylint: disable=no-name-in-module
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from kubeflow.tf_operator import tf_job_client #pylint: disable=no-name-in-module
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from kubeflow.tf_operator import test_runner #pylint: disable=no-name-in-module
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from kubeflow.testing import ks_util
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from kubeflow.testing import test_util
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			@ -18,13 +18,13 @@ local defaultParams = {
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  stepImage: "gcr.io/kubeflow-ci/test-worker/test-worker:v20190116-b7abb8d-e3b0c4",
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  // Which Kubeflow cluster to use for running TFJobs on.
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  kfProject: "kubeflow-ci",
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  kfZone: "us-east1-d",
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  kfCluster: "kf-v0-4-n00",
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  kfProject: "kubeflow-ci-deployment",
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  kfZone: "us-east1-b",
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  kfCluster: "kf-vmaster-n00",
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  // The bucket where the model should be written
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  // This needs to be writable by the GCP service account in the Kubeflow cluster (not the test cluster)
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  modelBucket: "kubeflow-ci_temp",
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  modelBucket: "kubeflow-ci-deployment_ci-temp",
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  // Whether to delete the namespace at the end.
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  // Leaving the namespace around can be useful for debugging.
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