tf.compat.v1.nn.crelu
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Computes Concatenated ReLU.
tf.compat.v1.nn.crelu(
features, name=None, axis=-1
)
Concatenates a ReLU which selects only the positive part of the activation
with a ReLU which selects only the negative part of the activation.
Note that as a result this non-linearity doubles the depth of the activations.
Source: Understanding and Improving Convolutional Neural Networks via
Concatenated Rectified Linear Units. W. Shang, et
al.
Args |
features
|
A Tensor with type float , double , int32 , int64 , uint8 ,
int16 , or int8 .
|
name
|
A name for the operation (optional).
|
axis
|
The axis that the output values are concatenated along. Default is -1.
|
Returns |
A Tensor with the same type as features .
|
References |
Understanding and Improving Convolutional Neural Networks via Concatenated
Rectified Linear Units:
Shang et al., 2016
(pdf)
|
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Last updated 2024-04-26 UTC.
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