class_docstr: The layer that converts data type of its input
  
  :param input_layer: The input layer and the number of its output. If no number
      is specified, the first output will be connected.
  :type input_layer: object, tuple(object, int)
  :param output_type: Type of the output.
  :type output_type: str, 'float' or 'int', default='float'
  :param name: The layer name.
  :type name: str, default=None
code: def __init__(self, input_layer, output_type="float", name=None):
      if type(input_layer) is PythonWrapper.Cast:
          super().__init__(input_layer)
          return
  
      layers, outputs = check_input_layers(input_layer, 1)
  
      if output_type != "float" and output_type != "int":
          raise ValueError("The `output_type` must be `int` or `float`")
      internal = PythonWrapper.Cast(
          str(name), layers[0], int(outputs[0]), str(output_type)
      )
      super().__init__(internal)
  
file_path: neoml/NeoML/Python/neoml/Dnn/Cast.py
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 1 to create a new Cast object from inherited base classes: Layer with example: obj = Cast(input_layer, output_type, name)