class_docstr: Featurizer is tasked with performing data preprocessing that should be shared
  between training and inference, namely, tokenization and gazetteer features
  alignment.
  
  This is an interface whose featurize() method must be implemented so that
  the implemented interface can be used with the appropriate data handler.
docstr: Featurize a batch of instances/examples.
docstr_tok: ["Featurize","a","batch","of","instances\/examples","."]
code: def featurize_batch(
      self, input_record_list: Sequence[InputRecord]
  ) -> Sequence[OutputRecord]:
      """Featurize a batch of instances/examples."""
      return [self.featurize(record) for record in input_record_list]
  
file_path: pytext/pytext/data/featurizer/featurizer.py
imports: from typing import List, NamedTuple, Optional, Sequence, Tuple
  from pytext.config.component import Component, ComponentType
  from pytext.config.field_config import FeatureConfig
label_desc: Use image node_id 4 for calling the Featurizer obj's underlying member method code with example usage: obj.featurize_batch(input_record_list) and returns: unknown