class_docstr: Wrapper for normal RNN Cells, make it support variational dropout
class_docstr_tok: ["Wrapper","for","normal","RNN","Cells",",","make","it","support","variational","dropout"]
code: def __init__(self, cell, hidden_size, input_p, hidden_p):
      super(VarRnnCellWrapper, self).__init__()
      self.cell = cell
      self.hidden_size = hidden_size
      self.input_p = input_p
      self.hidden_p = hidden_p
  
imports: import torch
  import torch.nn
  from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence, pad_packed_sequence
label_desc: Use image node_id 1 to create a new VarRnnCellWrapper object from inherited base classes: nn with example: obj = VarRnnCellWrapper(cell, hidden_size, input_p, hidden_p)