# coding=utf-8
# Copyright (c) 2019 Alibaba PAI team.
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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import numpy as np
import tensorflow as tf
[docs]def gelu(x):
""" Gaussian Error Linear Unit.
Original Implementation of the gelu activation function in Google Bert repo when initially created.
For information: OpenAI GPT's gelu is slightly different (and gives slightly different results):
0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3))))
Also see https://arxiv.org/abs/1606.08415
"""
cdf = 0.5 * (1.0 + tf.math.erf(x / tf.math.sqrt(2.0)))
return x * cdf
[docs]def gelu_new(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((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))
return x * cdf
[docs]def swish(x):
return x * tf.sigmoid(x)
[docs]def relu(x):
return tf.nn.relu(x)