diff options
| -rw-r--r-- | numpy/core/src/multiarray/array_method.c | 2 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/arrayobject.c | 4 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/convert_datatype.c | 33 | ||||
| -rw-r--r-- | numpy/core/tests/test_casting_unittests.py | 24 | ||||
| -rw-r--r-- | numpy/core/tests/test_dtype.py | 11 |
5 files changed, 42 insertions, 32 deletions
diff --git a/numpy/core/src/multiarray/array_method.c b/numpy/core/src/multiarray/array_method.c index a56781527..b8a190f83 100644 --- a/numpy/core/src/multiarray/array_method.c +++ b/numpy/core/src/multiarray/array_method.c @@ -588,7 +588,7 @@ boundarraymethod__resolve_descripors( return NULL; } else if (casting < 0) { - return Py_BuildValue("iO", casting, Py_None, Py_None); + return Py_BuildValue("iOO", casting, Py_None, Py_None); } PyObject *result_tuple = PyTuple_New(nin + nout); diff --git a/numpy/core/src/multiarray/arrayobject.c b/numpy/core/src/multiarray/arrayobject.c index 0cbbc44e7..b01d87216 100644 --- a/numpy/core/src/multiarray/arrayobject.c +++ b/numpy/core/src/multiarray/arrayobject.c @@ -1396,8 +1396,6 @@ array_richcompare(PyArrayObject *self, PyObject *other, int cmp_op) */ if (PyArray_TYPE(self) == NPY_VOID) { - int _res; - array_other = (PyArrayObject *)PyArray_FROM_O(other); /* * If not successful, indicate that the items cannot be compared @@ -1430,8 +1428,6 @@ array_richcompare(PyArrayObject *self, PyObject *other, int cmp_op) */ if (PyArray_TYPE(self) == NPY_VOID) { - int _res; - array_other = (PyArrayObject *)PyArray_FROM_O(other); /* * If not successful, indicate that the items cannot be compared diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c index cf8a20db2..557bb913b 100644 --- a/numpy/core/src/multiarray/convert_datatype.c +++ b/numpy/core/src/multiarray/convert_datatype.c @@ -1074,7 +1074,10 @@ PyArray_PromoteTypes(PyArray_Descr *type1, PyArray_Descr *type2) PyArray_Descr *res; /* Fast path for identical inputs (NOTE: This path preserves metadata!) */ - if (type1 == type2 && PyArray_ISNBO(type1->byteorder)) { + if (type1 == type2 + /* Use for builtin except void, void has no reliable byteorder */ + && type1->type_num > 0 && type1->type_num < NPY_NTYPES + && PyArray_ISNBO(type1->byteorder) && type1->type_num != NPY_VOID) { Py_INCREF(type1); return type1; } @@ -2973,7 +2976,7 @@ nonstructured_to_structured_resolve_descriptors( *view_offset = field_view_off - to_off; } } - if (PyTuple_Size(given_descrs[1]->names) != 1) { + if (PyTuple_Size(given_descrs[1]->names) != 1 || *view_offset < 0) { /* * Assume that a view is impossible when there is more than one * field. (Fields could overlap, but that seems weird...) @@ -3359,23 +3362,19 @@ can_cast_fields_safety( } } - /* - * If the itemsize (includes padding at the end), does not match, - * this is not a "no" cast (identical dtypes) and may not be viewable. - */ - if (from->elsize != to->elsize) { - /* - * The itemsize may mismatch even if all fields and formats match - * (due to additional padding). - */ + if (*view_offset != 0 || from->elsize != to->elsize) { + /* Can never be considered "no" casting. */ casting = PyArray_MinCastSafety(casting, NPY_EQUIV_CASTING); - if (from->elsize < to->elsize) { - *view_offset = NPY_MIN_INTP; - } } - else if (*view_offset != 0) { - /* If the calculated `view_offset` is not 0, it can only be "equiv" */ - casting = PyArray_MinCastSafety(casting, NPY_EQUIV_CASTING); + + /* The new dtype may have access outside the old one due to padding: */ + if (*view_offset < 0) { + /* negative offsets would give indirect access before original dtype */ + *view_offset = NPY_MIN_INTP; + } + if (from->elsize < to->elsize + *view_offset) { + /* new dtype has indirect access outside of the original dtype */ + *view_offset = NPY_MIN_INTP; } return casting; diff --git a/numpy/core/tests/test_casting_unittests.py b/numpy/core/tests/test_casting_unittests.py index a57e46fd0..5c5ff55b4 100644 --- a/numpy/core/tests/test_casting_unittests.py +++ b/numpy/core/tests/test_casting_unittests.py @@ -715,23 +715,25 @@ class TestCasting: @pytest.mark.parametrize(["to_dt", "expected_off"], [ # Same as `from_dt` but with both fields shifted: (np.dtype({"names": ["a", "b"], "formats": ["i4", "f4"], - "offsets": [2, 6]}), -2), + "offsets": [0, 4]}), 2), # Additional change of the names - # TODO: Tests will need changing for order vs. name based casting: - (np.dtype({"names": ["b", "a"], "formats": ["f4", "i4"], - "offsets": [6, 2]}), -2), - # Incompatible field offset change (offsets -2 and 0) - (np.dtype({"names": ["b", "a"], "formats": ["f4", "i4"], - "offsets": [6, 0]}), None)]) + (np.dtype({"names": ["b", "a"], "formats": ["i4", "f4"], + "offsets": [0, 4]}), 2), + # Incompatible field offset change + (np.dtype({"names": ["b", "a"], "formats": ["i4", "f4"], + "offsets": [0, 6]}), None)]) def test_structured_field_offsets(self, to_dt, expected_off): # This checks the cast-safety and view offset for swapped and "shifted" # fields which are viewable from_dt = np.dtype({"names": ["a", "b"], "formats": ["i4", "f4"], - "offsets": [0, 4]}) + "offsets": [2, 6]}) cast = get_castingimpl(type(from_dt), type(to_dt)) safety, _, view_off = cast._resolve_descriptors((from_dt, to_dt)) - assert safety == Casting.equiv + if from_dt.names == to_dt.names: + assert safety == Casting.equiv + else: + assert safety == Casting.safe # Shifting the original data pointer by -2 will align both by # effectively adding 2 bytes of spacing before `from_dt`. assert view_off == expected_off @@ -742,7 +744,9 @@ class TestCasting: ("(1,1)i", "i", 0), ("(2,1)i", "(2,1)i", 0), # field cases (field to field is tested explicitly also): - ("i", dict(names=["a"], formats=["i"], offsets=[2]), -2), + # Not considered viewable, because a negative offset would allow + # may structured dtype to indirectly access invalid memory. + ("i", dict(names=["a"], formats=["i"], offsets=[2]), None), (dict(names=["a"], formats=["i"], offsets=[2]), "i", 2), # Currently considered not viewable, due to multiple fields # even though they overlap (maybe we should not allow that?) diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py index c98297a04..e91aeeb3f 100644 --- a/numpy/core/tests/test_dtype.py +++ b/numpy/core/tests/test_dtype.py @@ -1157,6 +1157,9 @@ class TestDTypeMakeCanonical: def test_make_canonical_hypothesis(self, dtype): canonical = np.result_type(dtype) self.check_canonical(dtype, canonical) + # np.result_type with two arguments should always identical results: + two_arg_result = np.result_type(dtype, dtype) + assert np.can_cast(two_arg_result, canonical, casting="no") @pytest.mark.slow @hypothesis.given( @@ -1171,6 +1174,10 @@ class TestDTypeMakeCanonical: assert dtype_with_empty_space.itemsize == dtype.itemsize canonicalized = np.result_type(dtype_with_empty_space) self.check_canonical(dtype_with_empty_space, canonicalized) + # np.promote_types with two arguments should always identical results: + two_arg_result = np.promote_types( + dtype_with_empty_space, dtype_with_empty_space) + assert np.can_cast(two_arg_result, canonicalized, casting="no") # Ensure that we also check aligned struct (check the opposite, in # case hypothesis grows support for `align`. Then repeat the test: @@ -1179,6 +1186,10 @@ class TestDTypeMakeCanonical: assert dtype_with_empty_space.itemsize == dtype_aligned.itemsize canonicalized = np.result_type(dtype_with_empty_space) self.check_canonical(dtype_with_empty_space, canonicalized) + # np.promote_types with two arguments should always identical results: + two_arg_result = np.promote_types( + dtype_with_empty_space, dtype_with_empty_space) + assert np.can_cast(two_arg_result, canonicalized, casting="no") class TestPickling: |