code: def test_vectorized_intrin2(dtype="float32"):
      c2 = tvm.tir.const(2, dtype=dtype)
      test_funcs = [
          (tvm.tir.power, lambda x: np.power(x, 2.0)),
          (tvm.tir.fmod, lambda x: np.fmod(x, 2.0)),
      ]
  
      def run_test(tvm_intrin, np_func):
          n = 128
          A = te.placeholder((n,), dtype=dtype, name="A")
          B = te.compute((n,), lambda i: tvm_intrin(A[i], c2), name="B")
          s = sched(B)
          f = tvm.build(s, [A, B], "cuda")
          dev = tvm.cuda(0)
          a = tvm.nd.array(
              np.random.uniform(0, 1, size=n).astype(A.dtype), dev
          )
          b = tvm.nd.array(np.zeros(shape=(n,)).astype(A.dtype), dev)
          f(a, b)
          tvm.testing.assert_allclose(
              b.numpy(), np_func(a.numpy()), atol=1e-3, rtol=1e-3
          )
  
      for func in test_funcs:
          run_test(*func)
  
imports: import os
  import re
  import tvm
  from tvm import te
  import numpy
  from tvm import topi
  from tvm.contrib.nvcc import have_fp16, have_int8, have_bf16
  from tvm.contrib import utils
  from tvm.script import tir
  import tvm.testing
  import pytest
label_desc: Use image node_id 21 for calling a global function with example usage: test_vectorized_intrin2(dtype) without return types