code: def test_numpy_spacing(
      dtypes_values_casting,
      where,
      frontend,
      test_flags,
      backend_fw,
      fn_tree,
      on_device,
  ):
      input_dtypes, xs, casting, dtype = dtypes_values_casting
      (
          where,
          input_dtypes,
          test_flags,
      ) = np_frontend_helpers.handle_where_and_array_bools(
          where=where,
          input_dtype=input_dtypes,
          test_flags=test_flags,
      )
      np_frontend_helpers.test_frontend_function(
          input_dtypes=input_dtypes,
          frontend=frontend,
          test_flags=test_flags,
          backend_to_test=backend_fw,
          fn_tree=fn_tree,
          on_device=on_device,
          rtol=1e-02,
          atol=1e-03,
          x=xs[0],
          out=None,
          where=where,
          casting=casting,
          order="K",
          dtype=dtype,
          subok=True,
      )
  
imports: import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  import ivy_tests.test_ivy.test_frontends.test_numpy.helpers
label_desc: Use image node_id 3 for calling a global function with example usage: test_numpy_spacing(dtypes_values_casting, where, frontend, test_flags, backend_fw, fn_tree, on_device) without return types