code: def leaky_relu(x, alpha=0.1, name="LeakyReLU"):
      """LeakyReLU.
  
      Modified version of ReLU, introducing a nonzero gradient for negative
      input.
  
      Arguments:
          x: A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`,
              `int16`, or `int8`.
          alpha: `float`. slope.
          name: A name for this activation op (optional).
  
      Returns:
          A `Tensor` with the same type as `x`.
  
      References:
          Rectifier Nonlinearities Improve Neural Network Acoustic Models,
          Maas et al. (2013).
  
      Links:
          [http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf]
          (http://web.stanford.edu/~awni/papers/relu_hybrid_icml2013_final.pdf)
  
      """
  
      with tf.name_scope(name) as scope:
          m_x = tf.nn.relu(-x)
          x = tf.nn.relu(x)
          x -= alpha * m_x
  
      x.scope = scope
  
      return 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 10 for calling a global function with example usage: leaky_relu(x, alpha, name) and returns: x