class_docstr: Coref model for a single edge. Compatible with EdgeFeaturesDataset.
class_docstr_tok: ["Coref","model","for","a","single","edge",".","Compatible","with","EdgeFeaturesDataset","."]
code: def predict_minibatch(self, inputs):
      features = self._make_feature_columns(inputs)
      probas = self.model(features)  # <tf.float32>[batch_size, 1]
      preds = {"proba": tf.squeeze(probas, axis=-1).numpy()}
      return list(utils.unbatch_preds(preds))
  
imports: import os
  from collections.abc import Iterable
  from typing import Optional
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import utils
  import numpy
  import tensorflow
label_desc: Use image node_id 8 for calling the SingleEdgePredictor obj's underlying member method code with example usage: obj.predict_minibatch(inputs) and returns: list