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.

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.

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)