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# Copyright 2017 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.
# ==============================================================================
"""Keras integration tests."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from tensorflow.contrib import autograph
class MinimalKeras(tf.keras.Model):
def call(self, x):
return x * 3
class ModelWithStaticConditional(object):
def __init__(self, initial):
self.initial = initial
if self.initial:
self.h = 15
@autograph.convert()
def call(self):
x = 10
if self.initial:
x += self.h
return x
class BasicBlock(tf.keras.Model):
def __init__(self):
super(BasicBlock, self).__init__()
self.conv1 = tf.keras.layers.Conv2D(8, 3)
self.pool = tf.keras.layers.GlobalAveragePooling2D()
self.dense = tf.keras.layers.Dense(3)
def call(self, x):
x = self.conv1(x)
x = self.pool(x)
x = self.dense(x)
return x
class CompoundModel(tf.keras.Model):
def __init__(self):
super(CompoundModel, self).__init__()
self.block = BasicBlock()
@autograph.convert(recursive=True)
def call(self, x):
x = self.block(x) # pylint: disable=not-callable
return x
class KerasTest(tf.test.TestCase):
def test_basic(self):
MinimalKeras()
def test_conditional_attributes_False(self):
model = ModelWithStaticConditional(False)
self.assertEqual(model.call(), 10)
def test_conditional_attributes_True(self):
model = ModelWithStaticConditional(True)
self.assertEqual(model.call(), 25)
def test_recursive_true(self):
with self.assertRaisesRegexp(NotImplementedError,
'Object conversion is not yet supported.'):
with tf.Graph().as_default():
model = CompoundModel()
model.build(tf.TensorShape((None, 10, 10, 1)))
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
sample_input = tf.random_uniform((1, 10, 10, 1))
output = model(sample_input) # pylint: disable=not-callable
self.assertEqual(sess.run(output).shape, (1, 3))
if __name__ == '__main__':
tf.test.main()
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