(input_size: int, output_size: int,
            stacks: int, layers: int, layer_size: int)
return NBeats(t.nn.ModuleList([NBeatsBlock(input_size=input_size,
                                               theta_size=input_size + output_size,
                                               basis_function=GenericBasis(backcast_size=input_size,
                                                                           forecast_size=output_size),
                                               layers=layers,
                                               layer_size=layer_size)
                                   for _ in range(stacks)]))
Create N-BEATS generic model.
Create N-BEATS generic model.
Create N - BEATS generic model .
def generic(input_size: int, output_size: int,
            stacks: int, layers: int, layer_size: int):
    """
    Create N-BEATS generic model.
    """
    return NBeats(t.nn.ModuleList([NBeatsBlock(input_size=input_size,
                                               theta_size=input_size + output_size,
                                               basis_function=GenericBasis(backcast_size=input_size,
                                                                           forecast_size=output_size),
                                               layers=layers,
                                               layer_size=layer_size)
                                   for _ in range(stacks)]))
def generic ( input_size : int , output_size : int , stacks : int , layers : int , layer_size : int ) : return NBeats ( t . nn . ModuleList ( [ NBeatsBlock ( input_size = input_size , theta_size = input_size + output_size , basis_function = GenericBasis ( backcast_size = input_size , forecast_size = output_size ) , layers = layers , layer_size = layer_size ) for _ in range ( stacks ) ] ) )