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: Override the ``train_load_sample`` hook with data loading logic that is only required during training.
  
  Args:
      sample: A single sample from the output of the ``load_data`` hook.
docstr_tok: ["Override","the","``","train_load_sample","``","hook","with","data","loading","logic","that","is","only","required","during","training",".","Args",":","sample",":","A","single","sample","from","the","output","of","the","``","load_data","``","hook","."]
code: def train_load_sample(self, sample: Dict[str, Any]) -> Any:
      """Override the ``train_load_sample`` hook with data loading logic that is only required during training.
  
      Args:
          sample: A single sample from the output of the ``load_data`` hook.
  
      """
      return self.load_sample(sample)
  
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 9 for calling the InputBase obj's underlying member method code with example usage: obj.train_load_sample(sample) and returns: self