code: def benchmark(model_cls, config, x, y, runs):
      train_time = 0
      inference_time = 0
      for _ in range(runs):
          model = model_cls(**config)
          train_start_time = time.time()
          model.fit(x, y)
          train_time += time.time() - train_start_time
  
          infer_start_time = time.time()
          model.predict(x)
          inference_time += time.time() - infer_start_time
      return train_time / runs, inference_time / runs
  
file_path: finetune/speed_benchmarks/run.py
imports: import time
  from tabulate import tabulate
  from finetune import Classifier, SequenceLabeler
  from finetune.base_models import RoBERTa
  from synthetic_data import multi_label_sequence_data, sequence_data, classification_data
label_desc: Use image node_id 1 for calling a global function with example usage: benchmark(model_cls, config, x, y, runs) and returns: unknown,  unknown