TensorFlow 1 version
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View source on GitHub
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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 | |
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features
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A Tensor with type float, double, int32, int64, uint8,
int16, or int8.
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name
|
A name for the operation (optional). |
axis
|
The axis that the output values are concatenated along. Default is -1. |
Returns | |
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A Tensor with the same type as features.
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References:
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units: Shang et al., 2016 (pdf)