# Copyright 2018 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.

# ==============================================================================

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

from tensorflow.python.eager import wrap_function

from tensorflow.python.framework import dtypes

from tensorflow.python.framework import ops

from tensorflow.python.framework import tensor_spec

from tensorflow.python.ops import variables

from tensorflow.python.platform import test

class WrapFunctionTest(test.TestCase):

def testDocString(self):

def f(x, do_add):

v = variables.Variable(5.0)

if do_add:

op = v.assign_add(x)

else:

op = v.assign_sub(x)

with ops.control_dependencies([op]):

return v.read_value()

f_add = wrap_function.wrap_function(

f, [tensor_spec.TensorSpec((), dtypes.float32), True])

self.assertAllEqual(f_add(1.0), 6.0)

self.assertAllEqual(f_add(1.0), 7.0)

# Can call tf.compat.v1.wrap_function again to get a new trace, a new set

# of variables, and possibly different non-template arguments.

f_sub = wrap_function.wrap_function(

f, [tensor_spec.TensorSpec((), dtypes.float32), False])

self.assertAllEqual(f_sub(1.0), 4.0)

self.assertAllEqual(f_sub(1.0), 3.0)

if __name__ == '__main__':

ops.enable_eager_execution()

test.main()