class_docstr: T5 from a TensorFlow SavedModel, for black-box access.
  
  To create a SavedModel from a regular T5 checkpoint, see
  https://github.com/google-research/text-to-text-transfer-transformer#export
code: def max_minibatch_size(self) -> int:
      # The lit.Model base class handles batching automatically in the
      # implementation of predict(), and uses this value as the batch size.
      return self.config.inference_batch_size
  
imports: import re
  import attr
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.models import model_utils
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import tensorflow
  import tensorflow_text
  import transformers
  from rouge_score import rouge_scorer
label_desc: Use image node_id 2 for calling the T5SavedModel obj's underlying member method code with example usage: obj.max_minibatch_size() and returns: self