code: def init_weights(self):
      for name, param in self.lstm.named_parameters():
          if "bias" in name:
              nn.init.constant_(param, 0.0)
          elif "weight_ih" in name:
              nn.init.xavier_normal_(param)
          elif "weight_hh" in name:
              nn.init.orthogonal_(param)
  
file_path: BigDL/python/chronos/src/bigdl/chronos/model/VanillaLSTM_pytorch.py
imports: import torch
  import torch.nn
  from pytorch_lightning import seed_everything
  from bigdl.chronos.pytorch.model_wrapper.normalization import NormalizeTSModel
  from bigdl.chronos.pytorch.model_wrapper.decomposition import DecompositionTSModel
label_desc: Use image node_id 2 for calling the LSTMModel obj's underlying member method code with example usage: obj.init_weights() without return types