code: def __init__(self, hidden_size, tag_size, dropout_rate):
      super(SequenceLabelForSO, self).__init__()
      self.tag_size = tag_size
      self.linear = nn.Linear(hidden_size, int(hidden_size / 2))
      self.hidden2tag_sub = nn.Linear(
          int(hidden_size / 2), self.tag_size
      )
      self.hidden2tag_obj = nn.Linear(
          int(hidden_size / 2), self.tag_size
      )
      self.dropout = nn.Dropout(dropout_rate)
  
file_path: DeepKE/example/triple/PRGC/model.py
imports: from collections import Counter
  import torch
  import torch.nn
  from transformers import BertPreTrainedModel, BertModel
label_desc: Use image node_id 1 to create a new SequenceLabelForSO object from inherited base classes: nn with example: obj = SequenceLabelForSO(hidden_size, tag_size, dropout_rate)