code: def verify_math(
      model,
      name="",
      rtol=1e-5,
      atol=1e-5,
      inputs=flow.tensor(
          np.random.rand(100, 1),
          dtype=flow.float32,
      ),
      device="llvm",
  ):
      """verify_math"""
      if device == "cuda":
          model.to(device)
          inputs = inputs.to(device)
  
      graph = OneFlowGraph(model)
      graph._compile(inputs)
  
      mkdir(MODEL_HOME)
      flow.save(model.state_dict(), MODEL_HOME)
  
      out_flow = get_oneflow_output(graph, inputs)
      out_tvm = get_tvm_output(graph, MODEL_HOME, inputs, 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 16 for calling a global function with example usage: verify_math(model, name, rtol, atol, inputs, device) without return types