code: def test_if_positive(ctx_factory):
      context = ctx_factory()
      queue = cl.CommandQueue(context)
  
      from pyopencl.clrandom import rand as clrand
  
      ary_len = 20000
      a_gpu = clrand(queue, (ary_len,), np.float32)
      b_gpu = clrand(queue, (ary_len,), np.float32)
      a = a_gpu.get()
      b = b_gpu.get()
  
      max_a_b_gpu = cl.array.maximum(a_gpu, b_gpu)
      min_a_b_gpu = cl.array.minimum(a_gpu, b_gpu)
  
      print(max_a_b_gpu)
      print(np.maximum(a, b))
  
      assert la.norm(max_a_b_gpu.get() - np.maximum(a, b)) == 0
      assert la.norm(min_a_b_gpu.get() - np.minimum(a, b)) == 0
  
imports: import numpy
  import numpy.linalg
  import sys
  from pytools import memoize
  from test_array import general_clrand
  import pytest
  import pyopencl
  import pyopencl.array
  from pyopencl.tools import pytest_generate_tests_for_pyopencl
  from pyopencl.characterize import has_double_support, has_struct_arg_count_bug
  from pyopencl.scan import InclusiveScanKernel, ExclusiveScanKernel, GenericScanKernel, GenericDebugScanKernel
  from pyopencl.characterize import get_pocl_version
label_desc: Use image node_id 7 for calling a global function with example usage: test_if_positive(ctx_factory) without return types