code: def test_basic_addbmm(self):
      class SimpleOp(nn.Module):
          def forward(self, x, y, z, m):
              out1 = x.addbmm(y, z, beta=2, alpha=3)
              out2 = torch.addbmm(x, y, z, beta=2, alpha=3)
              # out3 = x.addbmm_(y, z, beta=2, alpha=3)
              out3 = m.baddbmm(y, z, beta=2, alpha=3)
              out4 = torch.baddbmm(m, y, z, beta=2, alpha=3)
              out5 = torch.bmm(
                  y, z
              )  # deterministic is not supported by jit
              return out1, out2, out3, out4, out5
  
      self.checkExportImport(
          SimpleOp(),
          (
              torch.randn(3, 5),
              torch.randn(10, 3, 4),
              torch.randn(10, 4, 5),
              torch.randn(10, 3, 5),
          ),
      )
  
imports: import unittest
  import torch
  import nni.nas.nn.pytorch.layers
  from .convert_mixin import ConvertMixin, ConvertWithShapeMixin
label_desc: Use image node_id 8 for calling the TestConvert obj's underlying member method code with example usage: obj.test_basic_addbmm() and returns: out1,  out2,  out3,  out4,  out5