Computes Concatenated ReLU.
tf.compat.v2.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 . |
© 2020 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/versions/r1.15/api_docs/python/tf/compat/v2/nn/crelu