DEP: Expire deprecation to ignore bad dtype= in logical ufuncs (#22541)

* DEP: Expire deprecation to ignore bad dtype= in logical ufuncs

Basically only `bool` and `object dtype make sense, but they did
not work correctly.  The dtype argument was rather ignored often.

The offending behavior was deprecated in 1.20 and is now removed.

Co-authored-by: Sebastian Berg <sebastianb@nvidia.com>
Co-authored-by: Charles Harris <charlesr.harris@gmail.com>

doc/release/upcoming_changes/22541.expired.rst

@@ -0,0 +1,3 @@
+* The ``dtype=`` argument to comparison ufuncs is now applied
+  correctly.  That means that only ``bool`` and ``object`` are valid
+  values and ``dtype=object`` is enforced.

numpy/core/src/umath/dispatching.c

@@ -667,12 +667,9 @@ legacy_promote_using_legacy_type_resolver(PyUFuncObject *ufunc,
         Py_DECREF(out_descrs[i]);
     }
     /*
-     * The PyUFunc_SimpleBinaryComparisonTypeResolver has a deprecation
-     * warning (ignoring `dtype=`) and cannot be cached.
-     * All datetime ones *should* have a warning, but currently don't,
-     * but ignore all signature passing also.  So they can also
-     * not be cached, and they mutate the signature which of course is wrong,
-     * but not doing it would confuse the code later.
+     * datetime legacy resolvers ignore the signature, which should be
+     * warn/raise (when used).  In such cases, the signature is (incorrectly)
+     * mutated, and caching is not possible.
      */
     for (int i = 0; i < nargs; i++) {
         if (signature[i] != NULL && signature[i] != operation_DTypes[i]) {
@@ -1042,13 +1039,6 @@ default_ufunc_promoter(PyUFuncObject *ufunc,
         PyArray_DTypeMeta *op_dtypes[], PyArray_DTypeMeta *signature[],
         PyArray_DTypeMeta *new_op_dtypes[])
 {
-    if (ufunc->type_resolver == &PyUFunc_SimpleBinaryComparisonTypeResolver
-            && signature[0] == NULL && signature[1] == NULL
-            && signature[2] != NULL && signature[2]->type_num != NPY_BOOL) {
-        /* bail out, this is _only_ to give future/deprecation warning! */
-        return -1;
-    }
-
     /* If nin < 2 promotion is a no-op, so it should not be registered */
     assert(ufunc->nin > 1);
     if (op_dtypes[0] == NULL) {

numpy/core/src/umath/ufunc_type_resolution.c

@@ -382,53 +382,9 @@ PyUFunc_SimpleBinaryComparisonTypeResolver(PyUFuncObject *ufunc,
         }
     }
     else {
-        PyArray_Descr *descr;
-        /*
-         * DEPRECATED 2021-03, NumPy 1.20
-         *
-         * If the type tuple was originally a single element (probably),
-         * issue a deprecation warning, but otherwise accept it.  Since the
-         * result dtype is always boolean, this is not actually valid unless it
-         * is `object` (but if there is an object input we already deferred).
-         *
-         * TODO: Once this deprecation is gone, the special case for
-         *       `PyUFunc_SimpleBinaryComparisonTypeResolver` in dispatching.c
-         *       can be removed.
-         */
-        if (PyTuple_Check(type_tup) && PyTuple_GET_SIZE(type_tup) == 3 &&
-                PyTuple_GET_ITEM(type_tup, 0) == Py_None &&
-                PyTuple_GET_ITEM(type_tup, 1) == Py_None &&
-                PyArray_DescrCheck(PyTuple_GET_ITEM(type_tup, 2))) {
-            descr = (PyArray_Descr *)PyTuple_GET_ITEM(type_tup, 2);
-            if (descr->type_num == NPY_OBJECT) {
-                if (DEPRECATE_FUTUREWARNING(
-                        "using `dtype=object` (or equivalent signature) will "
-                        "return object arrays in the future also when the "
-                        "inputs do not already have `object` dtype.") < 0) {
-                    return -1;
-                }
-            }
-            else if (descr->type_num != NPY_BOOL) {
-                if (DEPRECATE(
-                        "using `dtype=` in comparisons is only useful for "
-                        "`dtype=object` (and will do nothing for bool). "
-                        "This operation will fail in the future.") < 0) {
-                    return -1;
-                }
-            }
-        }
-        else {
-            /* Usually a failure, but let the default version handle it */
-            return PyUFunc_DefaultTypeResolver(ufunc, casting,
-                    operands, type_tup, out_dtypes);
-        }
-
-        out_dtypes[0] = NPY_DT_CALL_ensure_canonical(descr);
-        if (out_dtypes[0] == NULL) {
-            return -1;
-        }
-        out_dtypes[1] = out_dtypes[0];
-        Py_INCREF(out_dtypes[1]);
+        /* Usually a failure, but let the default version handle it */
+        return PyUFunc_DefaultTypeResolver(ufunc, casting,
+                operands, type_tup, out_dtypes);
     }
 
     /* Output type is always boolean */

numpy/core/tests/test_deprecations.py

@@ -1000,31 +1000,6 @@ def test_deprecated(self):
         self.assert_deprecated(lambda: np.add(1, 2, sig=(np.dtype("l"),)))
 
 
-class TestComparisonBadDType(_DeprecationTestCase):
-    # Deprecated 2021-04-01, NumPy 1.21
-    message = r"using `dtype=` in comparisons is only useful for"
-
-    def test_deprecated(self):
-        self.assert_deprecated(lambda: np.equal(1, 1, dtype=np.int64))
-        # Not an error only for the transition
-        self.assert_deprecated(lambda: np.equal(1, 1, sig=(None, None, "l")))
-
-    def test_not_deprecated(self):
-        np.equal(True, False, dtype=bool)
-        np.equal(3, 5, dtype=bool, casting="unsafe")
-        np.equal([None], [4], dtype=object)
-
-class TestComparisonBadObjectDType(_DeprecationTestCase):
-    # Deprecated 2021-04-01, NumPy 1.21  (different branch of the above one)
-    message = r"using `dtype=object` \(or equivalent signature\) will"
-    warning_cls = FutureWarning
-
-    def test_deprecated(self):
-        self.assert_deprecated(lambda: np.equal(1, 1, dtype=object))
-        self.assert_deprecated(
-                lambda: np.equal(1, 1, sig=(None, None, object)))
-
-
 class TestCtypesGetter(_DeprecationTestCase):
     # Deprecated 2021-05-18, Numpy 1.21.0
     warning_cls = DeprecationWarning

numpy/core/tests/test_umath.py

@@ -338,6 +338,21 @@ def test_error_in_equal_reduce(self):
         assert_equal(np.equal.reduce(a, dtype=bool), True)
         assert_raises(TypeError, np.equal.reduce, a)
 
+    def test_object_dtype(self):
+        assert np.equal(1, [1], dtype=object).dtype == object
+        assert np.equal(1, [1], signature=(None, None, "O")).dtype == object
+
+    def test_object_nonbool_dtype_error(self):
+        # bool output dtype is fine of course:
+        assert np.equal(1, [1], dtype=bool).dtype == bool
+
+        # but the following are examples do not have a loop:
+        with pytest.raises(TypeError, match="No loop matching"):
+            np.equal(1, 1, dtype=np.int64)
+
+        with pytest.raises(TypeError, match="No loop matching"):
+            np.equal(1, 1, sig=(None, None, "l"))
+
 
 class TestAdd:
     def test_reduce_alignment(self):
@@ -1095,7 +1110,7 @@ def test_integer_to_negative_power(self):
             assert_raises(ValueError, np.power, a, minusone)
             assert_raises(ValueError, np.power, one, b)
             assert_raises(ValueError, np.power, one, minusone)
-    
+
     def test_float_to_inf_power(self):
         for dt in [np.float32, np.float64]:
             a = np.array([1, 1, 2, 2, -2, -2, np.inf, -np.inf], dt)
@@ -1348,7 +1363,7 @@ def test_sincos_values(self):
                 yf = np.array(y, dtype=dt)
                 assert_equal(np.sin(yf), xf)
                 assert_equal(np.cos(yf), xf)
-        
+
 
         with np.errstate(invalid='raise'):
             for callable in [np.sin, np.cos]: