code: def test_rnn_attractor(encoder_output_size, layer, unit, dropout):
      eda = RnnAttractor(
          encoder_output_size=encoder_output_size,
          layer=layer,
          unit=unit,
          dropout=dropout,
      )
      enc_input = torch.rand(5, 100, encoder_output_size)
      ilens = torch.tensor([100, 100, 100, 100, 100])
      dec_input = torch.zeros(5, 3, encoder_output_size)
      attractor, att_prob = eda.forward(
          enc_input=enc_input,
          ilens=ilens,
          dec_input=dec_input,
      )
      assert attractor.shape == (5, 3, encoder_output_size)
      assert att_prob.shape == (5, 3, 1)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_rnn_attractor(encoder_output_size, layer, unit, dropout) without return types