code: def __init__(self, parameters):
      if "path_to_model" not in parameters:
          parameters["path_to_model"] = parameters["bert_model"]
  
      self.parameters = parameters
  
      self.device = torch.device(
          "cuda"
          if torch.cuda.is_available() and not parameters["no_cuda"]
          else "cpu"
      )
      self.n_gpu = torch.cuda.device_count()
  
      # Load the fine-tuned model and the tokenizer used by it
      self.model = BertReranker.get_model(parameters)
      self.model.to(self.device)
      self.tokenizer = BertReranker.get_tokenizer(parameters)
  
      print("The reranking model is loaded")
  
imports: import torch
  import os
  import numpy
  from pytorch_transformers.modeling_bert import BertPreTrainedModel, BertConfig, BertModel
  from pytorch_transformers.tokenization_bert import BertTokenizer
  from torch.utils.data import DataLoader, SequentialSampler, TensorDataset
  from torch import nn
  from torch.nn import CrossEntropyLoss, MSELoss
  from tqdm import tqdm
  from pytorch_transformers.optimization import AdamW, WarmupLinearSchedule
  from pytorch_transformers.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
label_desc: Use image node_id 1 to create a new BertReranker object  with example: obj = BertReranker(parameters)