code: def __init__(self, bert_encoder, config):
      super(BertRegressionLoss, self).__init__(config)
      self.bert = bert_encoder
      self.dropout = nn.Dropout(config.hidden_dropout_prob)
      self.classifier = nn.Linear(config.hidden_size, 1)
      self.classifier.apply(self.init_bert_weights)
  
imports: import torch
  import torch.nn
  from torch.nn import CrossEntropyLoss, MSELoss
  from turing.utils import TorchTuple
  from pytorch_pretrained_bert.modeling import BertModel
  from pytorch_pretrained_bert.modeling import BertPreTrainingHeads, PreTrainedBertModel, BertPreTrainingHeads
  from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
label_desc: Use image node_id 1 to create a new BertRegressionLoss object from inherited base classes: PreTrainedBertModel with example: obj = BertRegressionLoss(bert_encoder, config)