code: def test_matmul():
      """MatMul"""
  
      class MatMul(flow.nn.Module):
          def forward(self, x, y):
              return flow._C.matmul(x, y)
  
      class MatMulTranspose(flow.nn.Module):
          def forward(self, x, y):
              return flow._C.matmul(x, y, transpose_b=True)
  
      class BatchMatMul(flow.nn.Module):
          def forward(self, x, y):
              return flow._C.batch_matmul(x, y)
  
      class BroadCastMatMul(flow.nn.Module):
          def forward(self, x, y):
              return flow._C.matmul(x, y)
  
      model1 = MatMul().eval()
      model2 = MatMulTranspose().eval()
      model3 = BatchMatMul().eval()
      model4 = BroadCastMatMul().eval()
  
      for device in ["llvm"]:
          verify_matmul(
              model1,
              device=device,
              inputs1=flow.tensor(
                  np.random.randn(2, 3).astype(np.float32)
              ),
              inputs2=flow.tensor(
                  np.random.randn(3, 3).astype(np.float32)
              ),
          )
          verify_matmul(
              model2,
              device=device,
              inputs1=flow.tensor(
                  np.random.randn(1, 2).astype(np.float32)
              ),
              inputs2=flow.tensor(
                  np.random.randn(3, 2).astype(np.float32)
              ),
          )
          verify_matmul(
              model3,
              device=device,
              inputs1=flow.tensor(
                  np.random.randn(2, 1, 2).astype(np.float32)
              ),
              inputs2=flow.tensor(
                  np.random.randn(2, 2, 3).astype(np.float32)
              ),
          )
          verify_matmul(
              model4,
              device=device,
              inputs1=flow.tensor(
                  np.random.randn(3, 8, 8, 16).astype(np.float32)
              ),
              inputs2=flow.tensor(
                  np.random.randn(16, 8).astype(np.float32)
              ),
          )
  
imports: import os
  import numpy
  import oneflow
  from packaging import version
  import tvm
  import tvm.testing
  import tvm.topi.testing
  from tvm import relay
label_desc: Use image node_id 31 for calling a global function with example usage: test_matmul() and returns: flow, flow, flow, flow