code: def test_tensor_expand_dims():
      def run(dtype):
          x = relay.var("x")
          mod = tvm.IRModule()
          p = Prelude(mod)
          expand_dims_func = p.get_global_var(
              "tensor_expand_dims", dtype
          )
          tensor1 = p.get_tensor_ctor("tensor1", dtype)
          mod["main"] = relay.Function(
              [x], expand_dims_func(tensor1(x))
          )
          x_np = np.random.uniform(low=0.0, high=8.0, size=(1,)).astype(
              dtype
          )
          expected = [np.expand_dims(x_np, axis=0)]
          check_tensor_array(mod, expected, x_np)
  
      run("float32")
      run("int32")
  
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 3 for calling a global function with example usage: test_tensor_expand_dims() without return types