code: def test_static_tensor_expand_dims():
      def run(dtype, shape):
          x = relay.var("x")
          mod = tvm.IRModule()
          p = Prelude(mod)
          static_tensor_array_ops = StaticTensorArrayOps(
              p, dtype, shape
          )
          static_tensor_array_ops.register()
  
          expand_dims_func = p.get_global_var_static(
              "tensor_expand_dims", dtype, shape
          )
          tensor = p.get_tensor_ctor_static(
              "tensor_constructor", dtype, shape
          )
          mod["main"] = relay.Function([x], expand_dims_func(tensor(x)))
          x_np = np.random.uniform(
              low=0.0, high=8.0, size=shape
          ).astype(dtype)
          expected = [np.expand_dims(x_np, axis=0)]
          check_tensor_array(mod, expected, x_np)
  
      run("float32", [])
      run(
          "int32",
          [
              2,
          ],
      )
  
imports: import pytest
  import tvm
  from tvm import relay
  from tvm.relay import testing
  from tvm.relay.backend.interpreter import ConstructorValue
  from tvm.relay import create_executor
  from tvm.relay.prelude import Prelude, StaticTensorArrayOps
  from tvm.relay.testing import count, make_nat_value, make_nat_expr
  import numpy
label_desc: Use image node_id 16 for calling a global function with example usage: test_static_tensor_expand_dims() without return types