code: def verify_dense_grad(d_shape, w_shape, executor_kind):
      data = relay.var("data", relay.TensorType(d_shape, "float32"))
      weight = relay.var("weight", relay.TensorType(w_shape, "float32"))
      fwd_func = relay.Function(
          [data, weight], relay.nn.dense(data, weight)
      )
      check_grad(fwd_func, executor_kind=executor_kind)
  
imports: import numpy
  import pytest
  from tvm import topi
  import tvm.topi.testing
  import tvm
  from tvm import te
  from tvm import relay
  from tvm.relay.testing import check_grad, run_infer_type, run_opt_pass
  from tvm.relay.transform import gradient
  import tvm.testing
label_desc: Use image node_id 9 for calling a global function with example usage: verify_dense_grad(d_shape, w_shape, executor_kind) without return types