parameters: (source_path, output_path, device_id)
docstring: Execute the parser.
  
          Args:
              source_path (str): the source file path.
              output_path (str): the output file path.
              device_id (str): the device id.
docstring_summary: Execute the parser.
docstring_tokens: Execute the parser .
function: def execute(source_path, output_path, device_id):
          """
          Execute the parser.
  
          Args:
              source_path (str): the source file path.
              output_path (str): the output file path.
              device_id (str): the device id.
          """
          col_names = ["node_name", "start_time", "end_time", "queue_size"]
          source_path = validate_and_normalize_path(source_path)
          minddata_aicpu_source_path = get_file_join_name(
              input_path=source_path, file_name='DATA_PREPROCESS.AICPUMI')
          if not minddata_aicpu_source_path:
              minddata_aicpu_source_path = get_file_join_name(
                  input_path=source_path, file_name='DATA_PREPROCESS.dev.AICPUMI')
              if not minddata_aicpu_source_path:
                  minddata_aicpu_source_path = get_file_join_name(
                      input_path=os.path.join(source_path, "data"), file_name='DATA_PREPROCESS.AICPUMI')
                  if not minddata_aicpu_source_path:
                      minddata_aicpu_source_path = get_file_join_name(
                          input_path=os.path.join(source_path, "data"), file_name='DATA_PREPROCESS.dev.AICPUMI')
                      if not minddata_aicpu_source_path:
                          return
          minddata_aicpu_output_path = os.path.join(output_path, "minddata_aicpu_" + device_id + ".txt")
          minddata_aicpu_data = MinddataParser.parse_minddata_aicpu_data(minddata_aicpu_source_path)
          if minddata_aicpu_data:
              fwrite_format(minddata_aicpu_output_path, " ".join(col_names), is_start=True)
              fwrite_format(minddata_aicpu_output_path, minddata_aicpu_data, is_start=True)
function_tokens: def execute ( source_path , output_path , device_id ) : col_names = [ "node_name" , "start_time" , "end_time" , "queue_size" ] source_path = validate_and_normalize_path ( source_path ) minddata_aicpu_source_path = get_file_join_name ( input_path = source_path , file_name = 'DATA_PREPROCESS.AICPUMI' ) if not minddata_aicpu_source_path : minddata_aicpu_source_path = get_file_join_name ( input_path = source_path , file_name = 'DATA_PREPROCESS.dev.AICPUMI' ) if not minddata_aicpu_source_path : minddata_aicpu_source_path = get_file_join_name ( input_path = os . path . join ( source_path , "data" ) , file_name = 'DATA_PREPROCESS.AICPUMI' ) if not minddata_aicpu_source_path : minddata_aicpu_source_path = get_file_join_name ( input_path = os . path . join ( source_path , "data" ) , file_name = 'DATA_PREPROCESS.dev.AICPUMI' ) if not minddata_aicpu_source_path : return minddata_aicpu_output_path = os . path . join ( output_path , "minddata_aicpu_" + device_id + ".txt" ) minddata_aicpu_data = MinddataParser . parse_minddata_aicpu_data ( minddata_aicpu_source_path ) if minddata_aicpu_data : fwrite_format ( minddata_aicpu_output_path , " " . join ( col_names ) , is_start = True ) fwrite_format ( minddata_aicpu_output_path , minddata_aicpu_data , is_start = True )