81 lines
2.8 KiB
Python
81 lines
2.8 KiB
Python
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for Softsign and SoftsignGrad."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import test_util
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from tensorflow.python.ops import gradient_checker
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from tensorflow.python.ops import nn_ops
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import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
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from tensorflow.python.platform import test
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class SoftsignTest(test.TestCase):
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def _npSoftsign(self, np_features):
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return np_features / (1 + np.abs(np_features))
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def _testSoftsign(self, np_features, use_gpu=False):
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np_softsign = self._npSoftsign(np_features)
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with self.cached_session(use_gpu=use_gpu):
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softsign = nn_ops.softsign(np_features)
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tf_softsign = self.evaluate(softsign)
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self.assertAllClose(np_softsign, tf_softsign)
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self.assertShapeEqual(np_softsign, softsign)
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def testNumbers(self):
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for t in [np.float, np.double]:
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self._testSoftsign(
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np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
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use_gpu=False)
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self._testSoftsign(
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np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
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use_gpu=True)
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@test_util.run_deprecated_v1
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def testGradient(self):
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with self.cached_session():
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x = constant_op.constant(
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[-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9],
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shape=[2, 5],
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name="x")
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y = nn_ops.softsign(x, name="softsign")
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x_init = np.asarray(
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[[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]],
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dtype=np.float32,
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order="F")
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err = gradient_checker.compute_gradient_error(
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x, [2, 5], y, [2, 5], x_init_value=x_init)
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print("softsign (float) gradient err = ", err)
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self.assertLess(err, 1e-4)
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@test_util.run_deprecated_v1
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def testNoInts(self):
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with self.cached_session():
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with self.assertRaisesRegexp(
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TypeError,
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"'features' has DataType int32 not in list of allowed values"):
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nn_ops.softsign(constant_op.constant(7)).eval()
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if __name__ == "__main__":
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test.main()
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