class_docstr: A `Predictor` that always produces the same forecast.
  
  Parameters
  ----------
  samples
      Samples to use to construct SampleForecast objects for every
      prediction.
code: def predict_item(self, item: DataEntry) -> SampleForecast:
      return SampleForecast(
          samples=self.samples,
          start_date=item["start"],
          item_id=item.get(FieldName.ITEM_ID),
      )
  
file_path: gluonts/src/gluonts/model/trivial/constant.py
imports: import numpy
  from gluonts.core.component import validated
  from gluonts.dataset.common import DataEntry
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.util import forecast_start
  from gluonts.model.forecast import SampleForecast
  from gluonts.model.predictor import RepresentablePredictor
label_desc: Use image node_id 2 for calling the ConstantPredictor obj's underlying member method code with example usage: obj.predict_item(item) and returns: SampleForecast