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Recently I changed my data pipeline in tensorflow from threading to a new Dataset api, which is pretty convenient once you want to validate your model each epoch.

I've noticed that current runtime version of tensorflow in Cloud ML is 1.2. Nevertheless, I've tried to use nightly build of tensorflow v1.3, but pip installation fails with: 

AssertionError: tensorflow==1.3.0 .dist-info directory not found
Command '['pip', 'install', '--user', '--upgrade', '--force-reinstall', '--no-deps', u'tensorflow-1.3.0-cp27-none-linux_x86_64.whl']' returned non-zero exit status 2

Does anyone succeeded with using tensorflow.cotrib.data.Dataset with Cloud ML engine?

Vlad Shkola
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1 Answers1

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This worked for me: create a setup.py file with the following content:

from setuptools import find_packages
from setuptools import setup

REQUIRED_PACKAGES = ['tensorflow==1.3.0']

setup(
    name='trainer',
    version='0.1',
    install_requires=REQUIRED_PACKAGES,
    packages=find_packages(),
    include_package_data=True,
    description='Upgrading tf to 1.3')

more info on the setup.py file is available at: Packaging a Training Application

Jan Krynauw
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