code: def test_train_no_configs_fp16(self):
      MODEL_ID = "sshleifer/tiny-gpt2"
      benchmark_args = PyTorchBenchmarkArguments(
          models=[MODEL_ID],
          training=True,
          inference=False,
          sequence_lengths=[8],
          batch_sizes=[1],
          fp16=True,
          multi_process=False,
      )
      benchmark = PyTorchBenchmark(benchmark_args)
      results = benchmark.run()
      self.check_results_dict_not_empty(results.time_train_result)
      self.check_results_dict_not_empty(results.memory_train_result)
  
imports: import os
  import tempfile
  import unittest
  from pathlib import Path
  from transformers import AutoConfig, is_torch_available
  from transformers.testing_utils import require_torch, torch_device
label_desc: Use image node_id 8 for calling the BenchmarkTest obj's underlying member method code with example usage: obj.test_train_no_configs_fp16() without return types