code: def init_hidden_cell(self, batch_size, layer_hidden_dim):
      return (
          torch.randn(2, batch_size, layer_hidden_dim // 2),
          torch.randn(2, batch_size, layer_hidden_dim // 2),
      )
  
file_path: DeepKE/src/deepke/event_extraction/standard/bertcrf/crf.py
imports: import torch
  import torch.autograd
  import torch.nn
label_desc: Use image node_id 2 for calling the CRF obj's underlying member method code with example usage: obj.init_hidden_cell(batch_size, layer_hidden_dim) and returns: torch,  torch