https://github.com/tensorflow/models/issues/2739

gistfile1.txt

--- object_detection/samples/cloud/cloud.yml	2017-12-28 16:49:11.000000000 +0200
+++ object_detection/samples/cloud/cloud.yml	2017-12-28 16:49:27.000000000 +0200
@@ -1,5 +1,5 @@
 trainingInput:
-  runtimeVersion: "1.0"
+  runtimeVersion: "1.4"
   scaleTier: CUSTOM
   masterType: standard_gpu
   workerCount: 5
--- object_detection/evaluator.py	2017-12-28 16:30:11.000000000 +0200
+++ object_detection/evaluator.py	2017-12-28 16:33:13.000000000 +0200
@@ -181,7 +181,7 @@
     return result_dict

   variables_to_restore = tf.global_variables()
-  global_step = tf.train.get_or_create_global_step()
+  global_step = tf.contrib.framework.get_or_create_global_step()
   variables_to_restore.append(global_step)
   if eval_config.use_moving_averages:
     variable_averages = tf.train.ExponentialMovingAverage(0.0)
--- object_detection/builders/optimizer_builder.py	2017-12-28 16:35:02.000000000 +0200
+++ object_detection/builders/optimizer_builder.py	2017-12-28 16:35:55.000000000 +0200
@@ -100,7 +100,8 @@
     learning_rate_sequence = [config.initial_learning_rate]
     learning_rate_sequence += [x.learning_rate for x in config.schedule]
     learning_rate = learning_schedules.manual_stepping(
-        tf.train.get_or_create_global_step(), learning_rate_step_boundaries,
+        tf.contrib.framework.get_or_create_global_step(),
+        learning_rate_step_boundaries,
         learning_rate_sequence)

   if learning_rate_type == 'cosine_decay_learning_rate':
--- setup.py	2017-12-28 16:46:54.000000000 +0200
+++ setup_new.py	2017-12-28 16:46:06.000000000 +0200
@@ -1,10 +1,32 @@
 """Setup script for object_detection."""

+import logging
+import subprocess
 from setuptools import find_packages
 from setuptools import setup
+from setuptools.command.install import install

+class CustomCommands(install):

-REQUIRED_PACKAGES = ['Pillow>=1.0']
+	def RunCustomCommand(self, command_list):
+		p = subprocess.Popen(
+        command_list,
+        stdin=subprocess.PIPE,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.STDOUT)
+		stdout_data, _ = p.communicate()
+		logging.info('Log command output: %s', stdout_data)
+		if p.returncode != 0:
+			raise RuntimeError('Command %s failed: exit code: %s' %
+                         (command_list, p.returncode))
+
+	def run(self):
+		self.RunCustomCommand(['apt-get', 'update'])
+		self.RunCustomCommand(
+          ['apt-get', 'install', '-y', 'python-tk'])
+		install.run(self)
+
+REQUIRED_PACKAGES = ['Pillow>=1.0', 'protobuf>=3.3.0', 'Matplotlib>=2.1']

 setup(
     name='object_detection',
@@ -13,4 +35,7 @@
     include_package_data=True,
     packages=[p for p in find_packages() if p.startswith('object_detection')],
     description='Tensorflow Object Detection Library',
+ cmdclass={
+        'install': CustomCommands,
+    }
 )
--- object_detection/utils/visualization_utils.py	2017-12-28 16:23:30.000000000 +0200
+++ object_detection/utils/visualization_utils.py	2017-12-28 16:24:16.000000000 +0200
@@ -21,6 +21,8 @@
 """
 import collections
 import functools
+import matplotlib
+matplotlib.use('agg')
 import matplotlib.pyplot as plt
 import numpy as np
 import PIL.Image as Image