code: def __init__(self, queries, corpus, ce_scores):
      self.queries = queries
      self.queries_ids = list(queries.keys())
      self.corpus = corpus
      self.ce_scores = ce_scores
  
      for qid in self.queries:
          self.queries[qid]["pos"] = list(self.queries[qid]["pos"])
          self.queries[qid]["neg"] = list(self.queries[qid]["neg"])
          random.shuffle(self.queries[qid]["neg"])
  
file_path: sentence-transformers/examples/training/ms_marco/train_bi-encoder_margin-mse.py
imports: import sys
  import json
  from torch.utils.data import DataLoader
  from sentence_transformers import SentenceTransformer, LoggingHandler, util, models, losses, InputExample
  import logging
  from datetime import datetime
  import gzip
  import os
  import tarfile
  import tqdm
  from torch.utils.data import Dataset
  import random
  from shutil import copyfile
  import pickle
  import argparse
label_desc: Use image node_id 1 to create a new MSMARCODataset object from inherited base classes: Dataset with example: obj = MSMARCODataset(queries, corpus, ce_scores)