class_docstr: The ``TabularForecastingData`` class is a :class:`~flash.core.data.data_module.DataModule` with a set of
  classmethods for loading data for tabular forecasting.
class_docstr_tok: ["The","``","TabularForecastingData","``","class","is","a",":","class",":","`","~flash.core.data.data_module.DataModule","`","with","a","set","of","classmethods","for","loading","data","for","tabular","forecasting","."]
docstr: The ``parameters`` dictionary from the ``TimeSeriesDataSet`` object created from the train data when
  constructing the ``TabularForecastingData`` object.
docstr_tok: ["The","``","parameters","``","dictionary","from","the","``","TimeSeriesDataSet","``","object","created","from","the","train","data","when","constructing","the","``","TabularForecastingData","``","object","."]
code: def parameters(self) -> Optional[Dict[str, Any]]:
      """The ``parameters`` dictionary from the ``TimeSeriesDataSet`` object created from the train data when
      constructing the ``TabularForecastingData`` object."""
      return getattr(self.train_dataset, "parameters", None)
  
file_path: lightning-flash/src/flash/tabular/forecasting/data.py
imports: from typing import Any, Dict, List, Optional, Type, Union
  from torch.utils.data.sampler import Sampler
  from flash.core.data.callback import BaseDataFetcher
  from flash.core.data.data_module import DataModule
  from flash.core.data.io.input import Input
  from flash.core.data.io.input_transform import INPUT_TRANSFORM_TYPE, InputTransform
  from flash.core.utilities.imports import _PANDAS_AVAILABLE, _TOPIC_TABULAR_AVAILABLE
  from flash.core.utilities.stages import RunningStage
  from flash.tabular.forecasting.input import TabularForecastingDataFrameInput
label_desc: Use image node_id 1 for calling the TabularForecastingData obj's underlying member method code with example usage: obj.parameters() and returns: getattr