class_docstr: Allows to create stack layers for a given network.
class_docstr_tok: ["Allows","to","create","stack","layers","for","a","given","network","."]
docstr: Creates a new prelu layer with the given name and input.
  :param name: name for this layer.
  :param input_layer_name: name of the layer that serves as input for this one.
docstr_tok: ["Creates","a","new","prelu","layer","with","the","given","name","and","input",".",":","param","name",":","name","for","this","layer",".",":","param","input_layer_name",":","name","of","the","layer","that","serves","as","input","for","this","one","."]
code: def new_prelu(self, name: str, input_layer_name: str = None):
      """
      Creates a new prelu layer with the given name and input.
      :param name: name for this layer.
      :param input_layer_name: name of the layer that serves as input for this one.
      """
      input_layer = self.__network.get_layer(input_layer_name)
  
      with tf.compat.v1.variable_scope(name):
          channels_input = int(input_layer.get_shape()[-1])
          alpha = self.__make_var("alpha", shape=[channels_input])
          output = tf.nn.relu(input_layer) + tf.multiply(
              alpha, -tf.nn.relu(-input_layer)
          )
  
      self.__network.add_layer(name, layer_output=output)
  
file_path: mtcnn/mtcnn/layer_factory.py
imports: import tensorflow
  from distutils.version import LooseVersion
label_desc: Use image node_id 8 for calling the LayerFactory obj's underlying member method code with example usage: obj.new_prelu(name, input_layer_name) without return types