"self.m.size() == 2",
				"'a' in self.m",
				"type(self.m['a']) == null_type", // null check using runtime type checking
				//"self.m['a'] == null",

				"self.l.size() == 2",
				"type(self.l[0]) == null_type",
				//"self.l[0] == null",

				"self.s.size() == 2",
				"type(self.s[0]) == null_type",
				//"self.s[0] == null",
			},
			errors: map[string]string{

					Key:             "something",
					ValueExpression: "true",
				}},
			},
		},
		expectedError: `spec.auditAnnotations[0].valueExpression: Invalid value: "true": must evaluate to one of [string null_type]`,
	}, {
		name: "invalid auditAnnotations valueExpression",
		config: &admissionregistration.ValidatingAdmissionPolicy{
			ObjectMeta: metav1.ObjectMeta{
				Name: "config",
			},

  auto tail_type = mlir::dyn_cast<ShapedType>(type1);
  auto full_type = mlir::dyn_cast<ShapedType>(type2);
  if (!tail_type || !full_type || !tail_type.hasRank() ||
      !full_type.hasRank() || tail_type.getRank() > full_type.getRank())
    return false;
  auto i1 = tail_type.getShape().rbegin(), e1 = tail_type.getShape().rend();
  auto i2 = full_type.getShape().rbegin();
  return std::equal(i1, e1, i2);
}

  using tensorflow::RecordMutation;
  mutex_lock l(graph->mu);
  FullTypeDef full_type;
  full_type.ParseFromArray(full_type_proto->data, full_type_proto->length);
  *op->node.mutable_def()->mutable_experimental_type() = full_type;
  RecordMutation(graph, *op, "setting fulltype");
}

void TF_SetRequestedDevice(TF_Graph* graph, TF_Operation* op,

		t.Errorf("error = %q; want %q", err, want)
	}
}

type nullTestRow struct {
	nullParam    any
	notNullParam any
	scanNullVal  any
}

type nullTestSpec struct {
	nullType    string
	notNullType string
	rows        [6]nullTestRow
}

func TestNullStringParam(t *testing.T) {
	spec := nullTestSpec{"nullstring", "string", [6]nullTestRow{