code: def is_tf_dataset(x):
      if hasattr(x, "__class__"):
          for parent in x.__class__.__mro__:
              if parent.__name__ in (
                  "DatasetV2",
                  "DistributedDataset",
              ) and "tensorflow.python." in str(parent.__module__):
                  return True
      return False
  
file_path: keras/keras/trainers/data_adapters/__init__.py
imports: import types
  from keras.distribution import distribution_lib
  from keras.trainers.data_adapters import array_data_adapter
  from keras.trainers.data_adapters import py_dataset_adapter
  from keras.trainers.data_adapters.array_data_adapter import ArrayDataAdapter
  from keras.trainers.data_adapters.generator_data_adapter import GeneratorDataAdapter
  from keras.trainers.data_adapters.py_dataset_adapter import PyDatasetAdapter
  from keras.trainers.data_adapters.tf_dataset_adapter import TFDatasetAdapter
  from keras.trainers.data_adapters.torch_data_loader_adapter import TorchDataLoaderAdapter
label_desc: Use image node_id 3 for calling a global function with example usage: is_tf_dataset(x) and returns: False, True