code: def test_tc():
      """Simple testcase, check that transformation typechecks."""
      mod = tvm.IRModule()
  
      shape = (20, 20)
      dtype = "float32"
      t = relay.TensorType(shape, dtype)
  
      x1 = relay.var("x1", t)
      x2 = relay.var("x2", t)
      # f(x1,x2) = (x1-x2)*x2
      y = relay.Function([x1, x2], (x1 - x2) * x2)
  
      mod["main"] = y
      mod = transform.InferType()(mod)
      mod = transform.LazyGradientInit()(mod)
  
      # function input/output types should remain the same
      assert mod["main"].checked_type == relay.FuncType([t, t], t)
  
imports: import numpy
  import tvm
  from tvm import relay
  from tvm.relay import create_executor, transform
  from tvm.relay.testing import rand, run_infer_type
  import tvm.testing
  from tvm.testing import assert_allclose
label_desc: Use image node_id 1 for calling a global function with example usage: test_tc() without return types