code: def verify_matmul_grad(
      a_shape, b_shape, transpose_a, transpose_b, executor_kind
  ):
      tensor_a = relay.var(
          "tensor_a", relay.TensorType(a_shape, "float32")
      )
      tensor_b = relay.var(
          "tensor_b", relay.TensorType(b_shape, "float32")
      )
      fwd_func = relay.Function(
          [tensor_a, tensor_b],
          relay.nn.matmul(
              tensor_a,
              tensor_b,
              transpose_a=transpose_a,
              transpose_b=transpose_b,
          ),
      )
      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 11 for calling a global function with example usage: verify_matmul_grad(a_shape, b_shape, transpose_a, transpose_b, executor_kind) without return types