class_docstr: Classes used to bring the output of a network into a class.
class_docstr_tok: ["Classes","used","to","bring","the","output","of","a","network","into","a","class","."]
code: def __call__(
      self,
      inference_data_loader: DataLoader,
      prediction_net,
      input_names: List[str],
      output_transform: Optional[OutputTransform],
      num_samples: Optional[int],
      **kwargs,
  ) -> Iterator[Forecast]:
      raise NotImplementedError()
  
imports: import logging
  from functools import singledispatch
  from typing import Callable, Iterator, List, Optional
  import numpy
  from gluonts.core.component import validated
  from gluonts.dataset.common import DataEntry
  from gluonts.dataset.field_names import FieldName
  from gluonts.itertools import select
  from gluonts.dataset.loader import DataLoader
  from gluonts.model.forecast import Forecast, QuantileForecast, SampleForecast
label_desc: Use image node_id 1 for calling the ForecastGenerator obj's underlying member method code with example usage: obj.__call__(inference_data_loader, prediction_net, input_names, output_transform, num_samples) without return types