code: def test_check_grad():
      shape = (10, 10)
      dtype = "float32"
      t = relay.TensorType(shape, dtype)
      x = relay.var("x", t)
      y = relay.var("y", t)
      func = relay.Function([x, y], x + y)
      check_grad(func)
  
imports: import collections
  import numpy
  import pytest
  import tvm
  from tvm import te
  from tvm import relay
  from tvm.relay import GlobalVar
  from tvm.relay.analysis import free_vars, free_type_vars
  from tvm.relay import create_executor, transform
  from tvm.relay.transform import gradient
  from tvm.relay.prelude import Prelude
  from tvm.relay.testing import make_nat_expr, run_infer_type, check_grad, rand, count_ops
  import tvm.relay.op
label_desc: Use image node_id 5 for calling a global function with example usage: test_check_grad() without return types