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# 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 | |
# limitations under the License. | |
# ============================================================================== | |
"""Gaussian error linear unit.""" | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
import math | |
import tensorflow as tf | |
def gelu(x): | |
"""Gaussian Error Linear Unit. | |
This is a smoother version of the RELU. | |
Original paper: https://arxiv.org/abs/1606.08415 | |
Args: | |
x: float Tensor to perform activation. | |
Returns: | |
`x` with the GELU activation applied. | |
""" | |
cdf = 0.5 * (1.0 + tf.tanh( | |
(math.sqrt(2 / math.pi) * (x + 0.044715 * tf.pow(x, 3))))) | |
return x * cdf | |