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# 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. | |
"""Customized Sigmoid activation.""" | |
import tensorflow as tf, tf_keras | |
def hard_sigmoid(features): | |
"""Computes the hard sigmoid activation function. | |
Args: | |
features: A `Tensor` representing preactivation values. | |
Returns: | |
The activation value. | |
""" | |
features = tf.convert_to_tensor(features) | |
return tf.nn.relu6(features + tf.cast(3., features.dtype)) * 0.16667 | |