class_docstr: GLUE benchmark model, using Keras/TF2 and Huggingface Transformers.
  
  This is a general-purpose classification or regression model. It works for
  one- or two-segment input, and predicts either a multiclass label or
  a regression score. See GlueModelConfig for available options.
  
  This implements the LIT API for inference (e.g. input_spec(), output_spec(),
  and predict()), but also provides a train() method to run fine-tuning.
  
  This is a full-featured implementation, which includes embeddings, attention,
  gradients, as well as support for the different input and output types above.
  For a more minimal example, see ../simple_tf2_demo.py.
class_docstr_tok: ["GLUE","benchmark","model",",","using","Keras\/TF2","and","Huggingface","Transformers",".","This","is","a","general-purpose","classification","or","regression","model",".","It","works","for","one-","or","two-segment","input",",","and","predicts","either","a","multiclass","label","or","a","regression","score",".","See","GlueModelConfig","for","available","options",".","This","implements","the","LIT","API","for","inference","(","e.g",".","input_spec","(",")",",","output_spec","(",")",",","and","predict","(",")",")",",","but","also","provides","a","train","(",")","method","to","run","fine-tuning",".","This","is","a","full-featured","implementation",",","which","includes","embeddings",",","attention",",","gradients",",","as","well","as","support","for","the","different","input","and","output","types","above",".","For","a","more","minimal","example",",","see","..","\/simple_tf2_demo.py","."]
code: def max_minibatch_size(self):
      return self.config.inference_batch_size
  
imports: import os
  from collections.abc import Iterable, Sequence
  import re
  import threading
  from typing import Any, Optional
  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 numpy
  import tensorflow
  import transformers
label_desc: Use image node_id 15 for calling the GlueModel obj's underlying member method code with example usage: obj.max_minibatch_size() and returns: self