code: def forward(self, x):
      x = x.permute(2, 0, 1)
      y, _ = self.lstm(x)
      if self.skip:
          y = y + x
      y = y.permute(1, 2, 0)
      return y
  
imports: from torch import nn
label_desc: Use image node_id 2 for calling the StreamableLSTM obj's underlying member method code with example usage: obj.forward(x) and returns: y