class_docstr: Frozen-encoder coreference model.
class_docstr_tok: ["Frozen-encoder","coreference","model","."]
code: def input_spec(self):
      return {
          "text": lit_types.TextSegment(),
          "tokens": lit_types.Tokens(parent="text"),
          "coref": lit_types.EdgeLabels(align="tokens"),
          # Index of predicted (single) edge for Winogender
          "answer": lit_types.CategoryLabel(
              vocab=winogender.ANSWER_VOCAB, required=False
          ),
          # TODO(b/172975096): allow plotting of scalars from input data,
          # so we don't need to add this to the predictions.
          "pf_bls": lit_types.Scalar(required=False),
      }
  
imports: import os
  from absl import logging
  from lit_nlp.api import dtypes
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.coref import edge_predictor
  from lit_nlp.examples.coref import encoders
  from lit_nlp.examples.coref.datasets import winogender
  from lit_nlp.lib import utils
  import numpy
  import tqdm
label_desc: Use image node_id 8 for calling the FrozenEncoderCoref obj's underlying member method code with example usage: obj.input_spec() and returns: dict