lisht.py

# 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
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# ==============================================================================

import tensorflow as tf

from tensorflow_addons.utils.types import TensorLike


@tf.keras.utils.register_keras_serializable(package="Addons")
def lisht(x: TensorLike) -> tf.Tensor:
    r"""LiSHT: Non-Parameteric Linearly Scaled Hyperbolic Tangent Activation Function.

    Computes linearly scaled hyperbolic tangent (LiSHT):

    $$
    \mathrm{lisht}(x) = x * \tanh(x).
    $$

    See [LiSHT: Non-Parameteric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks](https://arxiv.org/abs/1901.05894).

    Usage:

    >>> x = tf.constant([1.0, 0.0, 1.0])
    >>> tfa.activations.lisht(x)
    <tf.Tensor: shape=(3,), dtype=float32, numpy=array([0.7615942, 0.       , 0.7615942], dtype=float32)>

    Args:
        x: A `Tensor`. Must be one of the following types:
            `bfloat16`, `float16`, `float32`, `float64`.
    Returns:
        A `Tensor`. Has the same type as `x`.
    """
    x = tf.convert_to_tensor(x)
    return x * tf.math.tanh(x)