# Copyright 2023 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 Sigmoid activation.""" import numpy as np import tensorflow as tf, tf_keras from official.modeling import activations class CustomizedSigmoidTest(tf.test.TestCase): def _hard_sigmoid_nn(self, x): x = np.float32(x) return tf.nn.relu6(x + 3.) * 0.16667 def test_hard_sigmoid(self): features = [[.25, 0, -.25], [-1, -2, 3]] customized_hard_sigmoid_data = activations.hard_sigmoid(features) sigmoid_data = self._hard_sigmoid_nn(features) self.assertAllClose(customized_hard_sigmoid_data, sigmoid_data) if __name__ == '__main__': tf.test.main()