TensorFlow 1 version View source on GitHub

Computes Concatenated ReLU.

    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.


  • 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.