code: def __init__(
      self, hidden_size, bidirectional=True, return_sequences=True
  ):
      super(QAModel_mean, self).__init__()
      self.hidden_size = hidden_size
      self.lstm_q = layer.CudnnRNN(
          hidden_size=hidden_size,
          batch_first=True,
          bidirectional=bidirectional,
          return_sequences=return_sequences,
      )
      self.lstm_a = layer.CudnnRNN(
          hidden_size=hidden_size,
          batch_first=True,
          bidirectional=bidirectional,
          return_sequences=return_sequences,
      )
  
file_path: singa/examples/qabot/qabot_model.py
imports: from singa import autograd, layer, model
label_desc: Use image node_id 1 to create a new QAModel_mean object from inherited base classes: model with example: obj = QAModel_mean(hidden_size, bidirectional, return_sequences)