code: def forward(self, input, *fargs, **fkwargs):
      output, (hidden, cell) = nn.LSTM.forward(
          self, input, *fargs, **fkwargs
      )
      return output, hidden, cell
  
file_path: pytorch/test/onnx/model_defs/lstm_flattening_result.py
imports: from torch import nn
  from torch.nn.utils.rnn import PackedSequence
label_desc: Use image node_id 1 for calling the LstmFlatteningResult obj's underlying member method code with example usage: obj.forward(input) and returns: output,  hidden,  cell