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 fully connected layer.
  
  :param name: name for the layer.
  :param output_count: number of outputs of the fully connected layer.
  :param relu: boolean flag to set if ReLu should be applied at the end of this layer.
  :param input_layer_name: name of the input layer for this layer. If None, it will take the last added layer of
  the network.
docstr_tok: ["Creates","a","new","fully","connected","layer",".",":","param","name",":","name","for","the","layer",".",":","param","output_count",":","number","of","outputs","of","the","fully","connected","layer",".",":","param","relu",":","boolean","flag","to","set","if","ReLu","should","be","applied","at","the","end","of","this","layer",".",":","param","input_layer_name",":","name","of","the","input","layer","for","this","layer",".","If","None",",","it","will","take","the","last","added","layer","of","the","network","."]
code: def new_fully_connected(
      self,
      name: str,
      output_count: int,
      relu=True,
      input_layer_name: str = None,
  ):
      """
      Creates a new fully connected layer.
  
      :param name: name for the layer.
      :param output_count: number of outputs of the fully connected layer.
      :param relu: boolean flag to set if ReLu should be applied at the end of this layer.
      :param input_layer_name: name of the input layer for this layer. If None, it will take the last added layer of
      the network.
      """
  
      with tf.compat.v1.variable_scope(name):
          input_layer = self.__network.get_layer(input_layer_name)
          vectorized_input, dimension = self.vectorize_input(
              input_layer
          )
  
          weights = self.__make_var(
              "weights", shape=[dimension, output_count]
          )
          biases = self.__make_var("biases", shape=[output_count])
          operation = (
              tf.compat.v1.nn.relu_layer
              if relu
              else tf.compat.v1.nn.xw_plus_b
          )
  
          fc = operation(vectorized_input, weights, biases, name=name)
  
      self.__network.add_layer(name, layer_output=fc)
  
file_path: mtcnn/mtcnn/layer_factory.py
imports: import tensorflow
  from distutils.version import LooseVersion
label_desc: Use image node_id 10 for calling the LayerFactory obj's underlying member method code with example usage: obj.new_fully_connected(name, output_count, relu, input_layer_name) without return types