code: def load_model():
      if FLAGS.model_size not in MODEL_SIZE_MAP.keys():
          raise KeyError(
              f"`model_size` must be one of {MODEL_SIZE_MAP.keys()}, but "
              f"received {FLAGS.model_size}."
          )
      return keras_nlp.models.BertClassifier.from_preset(
          MODEL_SIZE_MAP[FLAGS.model_size], num_classes=2
      )
  
file_path: keras/benchmarks/model_benchmark/bert_benchmark.py
imports: import time
  import keras_nlp
  import numpy
  import tensorflow
  import tensorflow_datasets
  from absl import app
  from absl import flags
  from absl import logging
  from model_benchmark.benchmark_utils import BenchmarkMetricsCallback
  import keras
label_desc: Use image node_id 2 for calling a global function with example usage: load_model() and returns: keras_nlp