code: def crelu(x):
      """CReLU
  
      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.
  
      Arguments:
          x : A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`,
              `int16`, or `int8`.
  
      Returns:
          A `Tensor` with the same type as `x`.
  
      Links:
          [https://arxiv.org/abs/1603.05201](https://arxiv.org/abs/1603.05201)
  
      """
  
      return tf.nn.crelu(x)
  
imports: from __future__ import division, print_function, absolute_import
  import tensorflow.compat.v1
  import numpy
  import tflearn
  from .None import initializations
  from .None import variables
  from .utils import get_from_module
label_desc: Use image node_id 13 for calling a global function with example usage: crelu(x) and returns: tf