code: def load(self) -> None:
      if self.pretrained_bert:
          log.debug(f"From pretrained {self.pretrained_bert}.")
          self.config = AutoConfig.from_pretrained(
              self.pretrained_bert,
              num_labels=self.n_classes,
              output_attentions=True,
              output_hidden_states=True,
          )
          self.model = BertModel.from_pretrained(
              self.pretrained_bert, config=self.config
          )
  
      elif (
          self.bert_config_file
          and Path(self.bert_config_file).is_file()
      ):
          self.config = AutoConfig.from_json_file(
              str(expand_path(self.bert_config_file))
          )
          self.model = BertModel.from_config(config=self.bert_config)
      else:
          raise ConfigError("No pre-trained BERT model is given.")
  
      self.model.to(self.device)
  
file_path: DeepPavlov/deeppavlov/models/classifiers/re_bert.py
imports: import logging
  from pathlib import Path
  from typing import Tuple, Union, Any, List
  import torch
  from torch import Tensor
  import torch.nn
  from opt_einsum import contract
  from transformers import AutoConfig, BertModel, BertTokenizer
  from deeppavlov.core.commands.utils import expand_path
  from deeppavlov.core.common.errors import ConfigError
  from deeppavlov.models.relation_extraction.losses import ATLoss
label_desc: Use image node_id 4 for calling the BertWithAdaThresholdLocContextPooling obj's underlying member method code with example usage: obj.load() without return types