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tf.nn.crelu

tf.nn.crelu(
    features,
    name=None,
    axis=-1
)

Defined in tensorflow/python/ops/nn_ops.py.

See the guide: Neural Network > Activation Functions

Computes Concatenated ReLU.

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.

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/nn/crelu