code: def check_results_dict_not_empty(self, results):
      for model_result in results.values():
          for batch_size, sequence_length in zip(
              model_result["bs"], model_result["ss"]
          ):
              result = model_result["result"][batch_size][
                  sequence_length
              ]
              self.assertIsNotNone(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 1 for calling the BenchmarkTest obj's underlying member method code with example usage: obj.check_results_dict_not_empty(results) without return types