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snake.py
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snake.py
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# Copyright 2020 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.
# ==============================================================================
import tensorflow as tf
from tensorflow_addons.utils import types
@tf.keras.utils.register_keras_serializable(package="Addons")
def snake(x: types.TensorLike, frequency: types.Number = 1) -> tf.Tensor:
r"""Snake activation to learn periodic functions.
Computes snake activation:
$$
\mathrm{snake}(x) = \mathrm{x} + \frac{1 - \cos(2 \cdot \mathrm{frequency} \cdot x)}{2 \cdot \mathrm{frequency}}.
$$
See [Neural Networks Fail to Learn Periodic Functions and How to Fix It](https://arxiv.org/abs/2006.08195).
Usage:
>>> x = tf.constant([-1.0, 0.0, 1.0])
>>> tfa.activations.snake(x)
<tf.Tensor: shape=(3,), dtype=float32, numpy=array([-0.29192656, 0. , 1.7080734 ], dtype=float32)>
Args:
x: A `Tensor`.
frequency: A scalar, frequency of the periodic part.
Returns:
A `Tensor`. Has the same type as `x`.
"""
x = tf.convert_to_tensor(x)
frequency = tf.cast(frequency, x.dtype)
return x + (1 - tf.cos(2 * frequency * x)) / (2 * frequency)