code: def LSTMCell(input_dim, hidden_dim, **kwargs):
      m = nn.LSTMCell(input_dim, hidden_dim, **kwargs)
      for name, param in m.named_parameters():
          if "weight" in name or "bias" in name:
              param.data.uniform_(-0.1, 0.1)
      return m
  
file_path: translate/pytorch_translate/rnn_cell.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 for calling a global function with example usage: LSTMCell(input_dim, hidden_dim) and returns: m