code: def test_fp16_fp32_conversions(feature_string):
      relay_model = textwrap.dedent(
          """
          #[version = "0.0.5"]
          def @main(%inp : Tensor[(3), float32], %cst : Tensor[(3), float32]) {
              %1 = cast(%inp, dtype="float16");
              %2 = cast(%cst, dtype="float16");
              %3 = add(%1, %2);
              %4 = cast(%3, dtype="float32");
              %4
          }
          """
      )
  
      ir_mod = tvm.relay.fromtext(relay_model)
  
      arch = "i386" if machine == "i386" else "x86_64"
      aot_factory = tvm.relay.build(
          ir_mod,
          params={"cst": np.array([1.0, 2.0, 3.0], dtype="float32")},
          target=f"llvm --mtriple={arch} --mattr={feature_string}",
          executor=tvm.relay.backend.Executor(
              "aot", {"interface-api": "packed", "unpacked-api": False}
          ),
      )
  
      mod_name = aot_factory["list_module_names"]()[0]
      executor = aot_factory[mod_name]
      mod = executor(tvm.cpu(0))
  
      inp = tvm.nd.array(
          np.array([1.1, 2.1, 3.1], dtype="float32"), device=tvm.cpu(0)
      )
  
      mod.get_function("set_input")(0, inp)
      mod.get_function("run")()
      out = mod.get_function("get_output")(0)
  
      expected = np.array([2.1, 4.1, 6.1], dtype="float32")
      np.testing.assert_allclose(out.asnumpy(), expected, rtol=1e-3)
  
file_path: tvm/tests/python/codegen/test_target_codegen_x86.py
imports: import numpy
  import platform
  import pytest
  import re
  import textwrap
  import tvm
  from tvm import te
label_desc: Use image node_id 2 for calling a global function with example usage: test_fp16_fp32_conversions(feature_string) without return types