code: def test_inference_encoder_decoder_with_configs(self):
      MODEL_ID = "sshleifer/tinier_bart"
      config = AutoConfig.from_pretrained(MODEL_ID)
      benchmark_args = PyTorchBenchmarkArguments(
          models=[MODEL_ID],
          training=False,
          inference=True,
          sequence_lengths=[8],
          batch_sizes=[1],
          multi_process=False,
      )
      benchmark = PyTorchBenchmark(benchmark_args, configs=[config])
      results = benchmark.run()
      self.check_results_dict_not_empty(results.time_inference_result)
      self.check_results_dict_not_empty(results.memory_inference_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 10 for calling the BenchmarkTest obj's underlying member method code with example usage: obj.test_inference_encoder_decoder_with_configs() without return types