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 tensorflow variable with the given name and shape.
  :param name: name to set for the variable.
  :param shape: list defining the shape of the variable.
  :return: created TF variable.
docstr_tok: ["Creates","a","tensorflow","variable","with","the","given","name","and","shape",".",":","param","name",":","name","to","set","for","the","variable",".",":","param","shape",":","list","defining","the","shape","of","the","variable",".",":","return",":","created","TF","variable","."]
code: def __make_var(self, name: str, shape: list):
      """
      Creates a tensorflow variable with the given name and shape.
      :param name: name to set for the variable.
      :param shape: list defining the shape of the variable.
      :return: created TF variable.
      """
      return tf.compat.v1.get_variable(
          name,
          shape,
          trainable=self.__network.is_trainable(),
          use_resource=False,
      )
  
file_path: mtcnn/mtcnn/layer_factory.py
imports: import tensorflow
  from distutils.version import LooseVersion
label_desc: Use image node_id 5 for calling the LayerFactory obj's underlying member method code with example usage: obj.__make_var(name, shape) and returns: tf