class_docstr: Mixture Density Network - Recurrent Neural Network
code: def get_initial_hidden_state(self, batch_size=1):
      hidden = (
          torch.zeros(
              self.num_hidden_layers, batch_size, self.num_hiddens
          ),
          torch.zeros(
              self.num_hidden_layers, batch_size, self.num_hiddens
          ),
      )
      return hidden
  
imports: import logging
  from collections import deque
  from typing import NamedTuple
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import types
  from reagent.core.torch_utils import stack
  from torch.distributions.normal import Normal
label_desc: Use image node_id 3 for calling the MDNRNN obj's underlying member method code with example usage: obj.get_initial_hidden_state(batch_size) and returns: hidden