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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for tf upgrader."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import tempfile
import six
from tensorflow.python.framework import test_util
from tensorflow.python.platform import test as test_lib
from tensorflow.tools.compatibility import tf_upgrade
class TestUpgrade(test_util.TensorFlowTestCase):
"""Test various APIs that have been changed in 1.0.
We also test whether a converted file is executable. test_file_v0_11.py
aims to exhaustively test that API changes are convertible and actually
work when run with current TensorFlow.
"""
def _upgrade(self, old_file_text):
in_file = six.StringIO(old_file_text)
out_file = six.StringIO()
upgrader = tf_upgrade.TensorFlowCodeUpgrader()
count, report, errors = (
upgrader.process_opened_file("test.py", in_file,
"test_out.py", out_file))
return count, report, errors, out_file.getvalue()
def testParseError(self):
_, report, unused_errors, unused_new_text = self._upgrade(
"import tensorflow as tf\na + \n")
self.assertTrue(report.find("Failed to parse") != -1)
def testReport(self):
text = "tf.mul(a, b)\n"
_, report, unused_errors, unused_new_text = self._upgrade(text)
# This is not a complete test, but it is a sanity test that a report
# is generating information.
self.assertTrue(report.find("Renamed function `tf.mul` to `tf.multiply`"))
def testRename(self):
text = "tf.mul(a, tf.sub(b, c))\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.multiply(a, tf.subtract(b, c))\n")
def testRenamePack(self):
text = "tf.pack(a)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.stack(a)\n")
text = "tf.unpack(a)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.unstack(a)\n")
def testReorder(self):
text = "tf.concat(a, b)\ntf.split(a, b, c)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.concat(axis=a, values=b)\n"
"tf.split(axis=a, num_or_size_splits=b, value=c)\n")
def testConcatReorderWithKeywordArgs(self):
text = "tf.concat(concat_dim=a, values=b)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.concat(axis=a, values=b)\n")
text = "tf.concat(values=b, concat_dim=a)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.concat(values=b, axis=a)\n")
text = "tf.concat(a, values=b)\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.concat(axis=a, values=b)\n")
def testConcatReorderNested(self):
text = "tf.concat(a, tf.concat(c, d))\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(
new_text, "tf.concat(axis=a, values=tf.concat(axis=c, values=d))\n")
def testInitializers(self):
text = ("tf.zeros_initializer;tf.zeros_initializer ()\n"
"tf.ones_initializer;tf.ones_initializer ()\n")
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(
new_text, "tf.zeros_initializer();tf.zeros_initializer ()\n"
"tf.ones_initializer();tf.ones_initializer ()\n")
def testKeyword(self):
text = "tf.reduce_any(a, reduction_indices=[1, 2])\n"
_, unused_report, unused_errors, new_text = self._upgrade(text)
self.assertEqual(new_text, "tf.reduce_any(a, axis=[1, 2])\n")
def testComplexExpression(self):
text = "(foo + bar)[a].word()"
_ = self._upgrade(text)
def testReverse(self):
text = "tf.reverse(a, b)\n"
_, unused_report, errors, new_text = self._upgrade(text)
self.assertEqual(new_text, new_text)
self.assertEqual(errors, ["test.py:1: tf.reverse requires manual check."])
def testListComprehension(self):
def _test(input, output):
_, unused_report, errors, new_text = self._upgrade(input)
self.assertEqual(new_text, output)
_test("tf.concat(0, \t[x for x in y])\n",
"tf.concat(axis=0, \tvalues=[x for x in y])\n")
_test("tf.concat(0,[x for x in y])\n",
"tf.concat(axis=0,values=[x for x in y])\n")
_test("tf.concat(0,[\nx for x in y])\n",
"tf.concat(axis=0,values=[\nx for x in y])\n")
_test("tf.concat(0,[\n \tx for x in y])\n",
"tf.concat(axis=0,values=[\n \tx for x in y])\n")
# TODO(aselle): Explicitly not testing command line interface and process_tree
# for now, since this is a one off utility.
class TestUpgradeFiles(test_util.TensorFlowTestCase):
def testInplace(self):
"""Check to make sure we don't have a file system race."""
temp_file = tempfile.NamedTemporaryFile("w", delete=False)
original = "tf.mul(a, b)\n"
upgraded = "tf.multiply(a, b)\n"
temp_file.write(original)
temp_file.close()
upgrader = tf_upgrade.TensorFlowCodeUpgrader()
upgrader.process_file(temp_file.name, temp_file.name)
self.assertAllEqual(open(temp_file.name).read(), upgraded)
os.unlink(temp_file.name)
if __name__ == "__main__":
test_lib.main()
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