class_docstr: A `Dataset` that concatenates its input with given dataset.
docstr: See `Dataset.concatenate()` for details.
code: def __init__(self, input_dataset, dataset_to_concatenate, name=None):
      """See `Dataset.concatenate()` for details."""
      self._input_dataset = input_dataset
      self._dataset_to_concatenate = dataset_to_concatenate
  
      def common_supertype(a, b):
          result = a.most_specific_common_supertype([b])
          if result is None:
              raise TypeError(f"No common supertype of {a} and {b}.")
          return result
  
      try:
          self._structure = tf_nest.map_structure(
              common_supertype,
              input_dataset.element_spec,
              dataset_to_concatenate.element_spec,
          )
      except (TypeError, ValueError) as e:
          raise TypeError(
              f"Incompatible dataset elements:\n"
              f"  {input_dataset.element_spec} vs. "
              f"  {dataset_to_concatenate.element_spec}"
          ) from e
  
      self._input_datasets = [input_dataset, dataset_to_concatenate]
      self._name = name
      # pylint: disable=protected-access
      variant_tensor = gen_dataset_ops.concatenate_dataset(
          input_dataset._variant_tensor,
          dataset_to_concatenate._variant_tensor,
          **self._common_args,
      )
      # pylint: enable=protected-access
      super().__init__(variant_tensor)
  
file_path: tensorflow/tensorflow/python/data/ops/concatenate_op.py
imports: from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.ops import gen_dataset_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 to create a new _ConcatenateDataset object from inherited base classes: dataset_ops with example: obj = _ConcatenateDataset(input_dataset, dataset_to_concatenate, name)