class_docstr: ``InputBase`` is the base class for the :class:`~flash.core.data.io.input.Input` and
  :class:`~flash.core.data.io.input.IterableInput` dataset implementations in Flash. These datasets are constructed
  via the ``load_data`` and ``load_sample`` hooks, which allow a single dataset object to include custom loading logic
  according to the running stage (e.g. train, validate, test, predict).
  
  Args:
      running_stage: The running stage for which the input will be used.
      *args: Any arguments that are to be passed to the ``load_data`` hook.
      **kwargs: Any additional keyword arguments to pass to the ``load_data`` hook.
docstr: If ``self.data`` is ``None`` then the ``InputBase`` is considered falsey.
  
  This allows for quickly checking whether or not the ``InputBase`` is populated with data.
docstr_tok: ["If","``","self.data","``","is","``","None","``","then","the","``","InputBase","``","is","considered","falsey",".","This","allows","for","quickly","checking","whether","or","not","the","``","InputBase","``","is","populated","with","data","."]
code: def __bool__(self):
      """If ``self.data`` is ``None`` then the ``InputBase`` is considered falsey.
  
      This allows for quickly checking whether or not the ``InputBase`` is populated with data.
  
      """
      return self.data is not None
  
imports: import functools
  import os
  from enum import Enum
  from typing import Any, Dict, Iterable, List, Sequence, Tuple, Union, cast
  from pytorch_lightning.utilities.enums import LightningEnum
  from torch.utils.data import Dataset
  from flash.core.data.properties import Properties
  from flash.core.data.utils import _STAGES_PREFIX
  from flash.core.utilities.stages import RunningStage
label_desc: Use image node_id 13 for calling the InputBase obj's underlying member method code with example usage: obj.__bool__() and returns: unknown