code: def forward(self, inputs):
      if isinstance(inputs, list):
          real, imag = inputs
      elif isinstance(inputs, torch.Tensor):
          real, imag = torch.chunk(inputs, -1)
      r2r_out = self.real_lstm(real)[0]
      r2i_out = self.imag_lstm(real)[0]
      i2r_out = self.real_lstm(imag)[0]
      i2i_out = self.imag_lstm(imag)[0]
      real_out = r2r_out - i2i_out
      imag_out = i2r_out + r2i_out
      if self.projection_dim is not None:
          real_out = self.r_trans(real_out)
          imag_out = self.i_trans(imag_out)
      return [real_out, imag_out]
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the NavieComplexLSTM obj's underlying member method code with example usage: obj.forward(inputs) and returns: list