code: def _check_dataset_ffcv_decoder(dataset) -> "DecoderDef":
      """
      Returns the dataset-specific FFCV decoder definition, if available.
      """
      decoder_fn_or_def = getattr(dataset, "_ffcv_decoder", None)
      return decoder_fn_or_def
  
file_path: avalanche/avalanche/benchmarks/utils/ffcv_support/ffcv_support_internals.py
imports: from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Sequence, Union
  from collections import OrderedDict
  import numpy
  from torch import Tensor
  from PIL.Image import Image
  from ffcv.fields import TorchTensorField
  from ffcv.fields.decoders import IntDecoder, FloatDecoder, NDArrayDecoder, SimpleRGBImageDecoder
label_desc: Use image node_id 5 for calling a global function with example usage: _check_dataset_ffcv_decoder(dataset) and returns: decoder_fn_or_def