code: def verify_matmul(
      model,
      name="",
      rtol=1e-5,
      atol=1e-5,
      inputs1=flow.tensor(np.random.randn(2, 5), dtype=flow.float32),
      inputs2=flow.tensor(np.random.randn(5, 2), dtype=flow.float32),
      device="llvm",
  ):
      """verify_matmul"""
      if device == "cuda":
          model.to(device)
          inputs1 = inputs1.to(device)
          inputs2 = inputs2.to(device)
  
      graph = OneFlowGraphV3(model)
      graph._compile(inputs1, inputs2)
      mkdir(MODEL_HOME)
      flow.save(model.state_dict(), MODEL_HOME)
  
      out_flow = get_oneflow_elementwise_output(graph, inputs1, inputs2)
      out_tvm = get_tvm_elementwise_output(
          graph, MODEL_HOME, inputs1, inputs2, target=device
      )
      rmdir(MODEL_HOME)
  
      assert_shape(out_flow, out_tvm)
      tvm.testing.assert_allclose(
          out_flow, out_tvm, rtol=rtol, atol=atol
      )
  
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 17 for calling a global function with example usage: verify_matmul(model, name, rtol, atol, inputs1, inputs2, device) without return types