class_docstr: Dataset class for mt_bench dataset.
  Data source: https://github.com/lm-sys/FastChat/blob/main/fastchat/llm_judge/data/mt_bench/question.jsonl
  This dataset class will convert the original dataset into the inference dataset.
code: def load(
      path: str, logger: DistributedLogger, few_shot: bool
  ) -> List[Dict]:
      dataset = {"test": defaultdict(dict)}
  
      file_path = os.path.join(path, "question.jsonl")
      ref_path = os.path.join(path, "reference_answer/gpt-4.jsonl")
  
      reference = defaultdict(list)
      ref_origin = get_json_list(ref_path)
      for ref in ref_origin:
          reference[ref["question_id"]] = ref["choices"][0]["turns"]
  
      with open(file_path, "r", encoding="utf-8") as file:
          for line in file:
              question = json.loads(line)
              category = question["category"]
              turn_number = len(question["turns"])
              data_point = {
                  "id": question["question_id"],
                  "dataset": "mtbench",
                  "split": "test",
                  "category": category,
                  "instruction": question["turns"],
                  "input": "",
                  "output": [],
                  "target": [""] * turn_number
                  if question["question_id"] not in reference
                  else reference[question["question_id"]],
              }
  
              if category in dataset["test"]:
                  dataset["test"][category]["data"].append(data_point)
              else:
                  dataset["test"][category] = {
                      "data": [data_point],
                      "inference_kwargs": copy.deepcopy(
                          default_inference_kwargs
                      ),
                  }
  
      return dataset
  
file_path: ColossalAI/applications/ColossalEval/colossal_eval/dataset/mtbench.py
imports: import copy
  import json
  import os
  from collections import defaultdict
  from typing import Dict, List
  from colossal_eval.utils import get_json_list
  from colossalai.logging import DistributedLogger
  from .base import BaseDataset
label_desc: Use image node_id 2 for calling the MTBenchDataset obj's underlying member method code with example usage: obj.load(path, logger, few_shot) and returns: dataset