# Copyright 2019 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 the customized Swish activation.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf from tensorflow.python.keras import keras_parameterized # pylint: disable=g-direct-tensorflow-import from official.modeling import activations @keras_parameterized.run_all_keras_modes class CustomizedSwishTest(keras_parameterized.TestCase): def _hard_swish_np(self, x): x = np.float32(x) return x * np.clip(x + 3, 0, 6) / 6 def test_simple_swish(self): features = [[.25, 0, -.25], [-1, -2, 3]] customized_swish_data = activations.simple_swish(features) swish_data = tf.nn.swish(features) self.assertAllClose(customized_swish_data, swish_data) def test_hard_swish(self): features = [[.25, 0, -.25], [-1, -2, 3]] customized_swish_data = activations.hard_swish(features) swish_data = self._hard_swish_np(features) self.assertAllClose(customized_swish_data, swish_data) if __name__ == '__main__': tf.test.main()