class_docstr: mLSTMRNNCell
code: def __init__(
      self, input_size, hidden_size, bias=False, output_size=None
  ):
      gate_multiplier = 4
      super(mLSTMRNNCell, self).__init__(
          gate_multiplier,
          input_size,
          hidden_size,
          mLSTMCell,
          n_hidden_states=2,
          bias=bias,
          output_size=output_size,
      )
  
      self.w_mih = nn.Parameter(
          torch.empty(self.output_size, self.input_size)
      )
      self.w_mhh = nn.Parameter(
          torch.empty(self.output_size, self.output_size)
      )
  
      self.reset_parameters()
  
file_path: apex/apex/RNN/cells.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .RNNBackend import RNNCell
  from torch.nn._functions.thnn import rnnFusedPointwise
  import math
label_desc: Use image node_id 1 to create a new mLSTMRNNCell object from inherited base classes: RNNCell with example: obj = mLSTMRNNCell(input_size, hidden_size, bias, output_size)