code: def test_lstm(self):
      B, C, T = 4, 2, random.randint(1, 100)
  
      lstm = StreamableLSTM(C, 3, skip=False)
      x = torch.randn(B, C, T)
      y = lstm(x)
  
      print(y.shape)
      assert y.shape == torch.Size([B, C, T])
  
imports: import random
  import torch
  from audiocraft.modules.lstm import StreamableLSTM
label_desc: Use image node_id 1 for calling the TestStreamableLSTM obj's underlying member method code with example usage: obj.test_lstm() without return types