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# Copyright 2015 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 tensorflow.ops.argmax_op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
class GradientCorrectnessTest(tf.test.TestCase):
def testMultipleOutputChainedGradients(self):
with self.test_session() as sess:
x = tf.constant(1.0, dtype=tf.float32)
yexp = tf.exp(x)
yexplog = tf.log(yexp)
grads = tf.gradients([yexp, yexplog], [x])
grad_vals = sess.run(grads)
exp1_plus_one = (1.0 + np.exp(1.0)).astype(np.float32)
# [dexp(x)/dx + d(log(exp(x)))/dx] @ x=1 == exp(1) + 1
self.assertAllClose(grad_vals[0], exp1_plus_one)
if __name__ == '__main__':
tf.test.main()
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