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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
@tf_keras.utils.register_keras_serializable(package='Text')
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
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