parameters: (self, examples_batch)
return_statement: return tensor_signature.create_example_parser_from_signatures(
          self._features_info, examples_batch)
docstring: Returns feature parser for given example batch using features info.
  
      This function requires `fit()` has been called.
  
      Args:
        examples_batch: batch of tf.Example
  
      Returns:
        features: `Tensor` or `dict` of `Tensor` objects.
  
      Raises:
        ValueError: If `_features_info` attribute is not available (usually
        because `fit()` has not been called).
docstring_summary: Returns feature parser for given example batch using features info.
docstring_tokens: Returns feature parser for given example batch using features info .
function: def _get_feature_ops_from_example(self, examples_batch):
      """Returns feature parser for given example batch using features info.
  
      This function requires `fit()` has been called.
  
      Args:
        examples_batch: batch of tf.Example
  
      Returns:
        features: `Tensor` or `dict` of `Tensor` objects.
  
      Raises:
        ValueError: If `_features_info` attribute is not available (usually
        because `fit()` has not been called).
      """
      if self._features_info is None:
        raise ValueError('Features information missing, was fit() ever called?')
      return tensor_signature.create_example_parser_from_signatures(
          self._features_info, examples_batch)
function_tokens: def _get_feature_ops_from_example ( self , examples_batch ) : if self . _features_info is None : raise ValueError ( 'Features information missing, was fit() ever called?' ) return tensor_signature . create_example_parser_from_signatures ( self . _features_info , examples_batch )