dags/inference/configs/trt_llm_mlperf_v40_config.py [82:102]:
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      "metadata_log_paths = glob.glob(metadata_log_pattern)",
      "def convert_to_jsonl(json_path, jsonl_path):",
      "  data = dict()",
      "  data['dimensions'] = dict()",
      "  data['metrics'] = dict()",
      "  with open(json_path, 'r') as file:",
      "      metadatadata = json.load(file)",
      "      for key in metadatadata:",
      "          try:",
      "              float(metadatadata[key])",
      "              data['metrics'][key] = float(metadatadata[key])",
      "          except:",
      "              data['dimensions'][key] = metadatadata[key]",
      "  with jsonlines.open(jsonl_path, 'a') as writer:",
      "      writer.write(data)",
      "if __name__ == '__main__':",
      "  for metadata_log_path in metadata_log_paths:",
      "    convert_to_jsonl(metadata_log_path, sys.argv[1])",
  )
  py_script = "\n".join(jsonl_converter_py_lines)
  make_jsonl_converter_cmd = f'echo "{py_script}" > jsonl_converter.py'
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dags/inference/configs/trt_llm_mlperf_v41_config.py [91:111]:
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      "metadata_log_paths = glob.glob(metadata_log_pattern)",
      "def convert_to_jsonl(json_path, jsonl_path):",
      "  data = dict()",
      "  data['dimensions'] = dict()",
      "  data['metrics'] = dict()",
      "  with open(json_path, 'r') as file:",
      "      metadatadata = json.load(file)",
      "      for key in metadatadata:",
      "          try:",
      "              float(metadatadata[key])",
      "              data['metrics'][key] = float(metadatadata[key])",
      "          except:",
      "              data['dimensions'][key] = metadatadata[key]",
      "  with jsonlines.open(jsonl_path, 'a') as writer:",
      "      writer.write(data)",
      "if __name__ == '__main__':",
      "  for metadata_log_path in metadata_log_paths:",
      "    convert_to_jsonl(metadata_log_path, sys.argv[1])",
  )
  py_script = "\n".join(jsonl_converter_py_lines)
  make_jsonl_converter_cmd = f'echo "{py_script}" > jsonl_converter.py'
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