text: # pylint: disable=no-self-use
  from typing import Any, Dict, List, Mapping
  
  from overrides import overrides
  
  from allennlp.common.util import ScatterableList
  from allennlp.data.fields.field import DataArray, Field
  
  
  class MetadataField(Field[DataArray], Mapping[str, Any]):
      """
      A ``MetadataField`` is a ``Field`` that does not get converted into tensors.  It just carries
      side information that might be needed later on, for computing some third-party metric, or
      outputting debugging information, or whatever else you need.  We use this in the BiDAF model,
      for instance, to keep track of question IDs and passage token offsets, so we can more easily
      use the official evaluation script to compute metrics.
  
      We don't try to do any kind of smart combination of this field for batched input - when you use
      this ``Field`` in a model, you'll get a list of metadata objects, one for each instance in the
      batch.
  
      Parameters
      ----------
      metadata : ``Any``
          Some object containing the metadata that you want to store.  It's likely that you'll want
          this to be a dictionary, but it could be anything you want.
      """
      def __init__(self, metadata: Any) -> None:
          self.metadata = metadata
  
      def __getitem__(self, key: str) -> Any:
          try:
              return self.metadata[key]  # type: ignore
          except TypeError:
              raise TypeError("your metadata is not a dict")
  
      def __iter__(self):
          try:
              return iter(self.metadata)
          except TypeError:
              raise TypeError("your metadata is not iterable")
  
      def __len__(self):
          try:
              return len(self.metadata)
          except TypeError:
              raise TypeError("your metadata has no length")
  
      @overrides
      def get_padding_lengths(self) -> Dict[str, int]:
          return {}
  
      @overrides
      def as_tensor(self, padding_lengths: Dict[str, int]) -> DataArray:
          # pylint: disable=unused-argument
          return self.metadata  # type: ignore
  
      @overrides
      def empty_field(self) -> 'MetadataField':
          return MetadataField(None)
  
      @classmethod
      @overrides
      def batch_tensors(cls, tensor_list: List[DataArray]) -> ScatterableList:  # type: ignore
          return ScatterableList(tensor_list)
  
  
      def __str__(self) -> str:
          return f"MetadataField (print field.metadata to see specific information)."
  