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import os
from kubeflow import fairing


    

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# Setting up google container repositories (GCR) for storing output containers
# You can use any docker container registry istead of GCR
GCP_PROJECT = fairing.cloud.gcp.guess_project_name()
DOCKER_REGISTRY = 'gcr.io/{}/fairing-job'.format(GCP_PROJECT)
fairing.config.set_builder('append',base_image='tensorflow/tensorflow:latest-py3', registry=DOCKER_REGISTRY, push=True)
fairing.config.set_deployer('job')


    

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def train():
    print("hello world!")


    

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# Local training
train()


    

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remote_train = fairing.config.fn(train)
remote_train()