# tf.compat.v2.nn.crelu

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/nn_ops.py#L2774-L2776) |

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.](https://arxiv.org/abs/1603.05201)

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| ## Args ||
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| `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. |

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| ## Returns ||
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| A `Tensor` with the same type as `features`. ||

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