code: def __init__(self, sentences, batch_size, pos_neg_ratio=8):
      self.sentences = sentences
      self.batch_size = batch_size
      self.pos_neg_ratio = pos_neg_ratio
      self.collate_fn = None
  
      if self.batch_size % self.pos_neg_ratio != 0:
          raise ValueError(
              f"ContrastiveTensionDataLoader was loaded with a pos_neg_ratio of {pos_neg_ratio} and a batch size of {batch_size}. The batch size must be devisable by the pos_neg_ratio"
          )
  
imports: import torch
  from torch import nn, Tensor
  from typing import Iterable, Dict
  from ..SentenceTransformer import SentenceTransformer
  from ..None import util
  import copy
  import random
  import math
  from ..None import InputExample
  import numpy
label_desc: Use image node_id 1 to create a new ContrastiveTensionDataLoader object  with example: obj = ContrastiveTensionDataLoader(sentences, batch_size, pos_neg_ratio)