TensorFlow 1 version | View source on GitHub |
Computes Concatenated ReLU.
tf.nn.crelu(
features, axis=-1, name=None
)
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)