8000 BUG: Fix use and errorchecking of ObjectType use by seberg · Pull Request #22566 · numpy/numpy · GitHub
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Merged
merged 2 commits into from
Nov 10, 2022
Merged

BUG: Fix use and errorchecking of ObjectType use #22566

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eae88ff
BUG: Fix use and errorchecking of ObjectType use
seberg Nov 9, 2022
7c317d9
MAINT: Ensure that datetime dot, correlate, and vdot cannot happen
seberg Nov 9, 2022
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BUG: Fix use and errorchecking of ObjectType use 
This should be replaced really, it is pretty bad API use, and doesn't
work well (up to being incorrect probably).

But working on other things (trying to make promotion strict and thus
saner), I realized that the use was always wrong: we cannot pass 0
since 0 means `bool`, what was always meant was passing no-type.

So fixing this, and adding the error check everywhere.  Checking
for `PyErr_Occurred()` may have been necessary at some point, but
is not anymore.
  • Loading branch information
@seberg
seberg committed Nov 9, 2022
commit eae88ff5f9cc3e3caea5e849600e0f8db52a67db
13 changes: 11 additions & 2 deletions numpy/core/src/multiarray/_multiarray_tests.c.src
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Original file line number Diff line number Diff line change
Expand Up @@ -177,8 +177,14 @@ test_neighborhood_iterator(PyObject* NPY_UNUSED(self), PyObject* args)
return NULL;
}

typenum = PyArray_ObjectType(x, 0);
typenum = PyArray_ObjectType(x, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(fill, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

ax = (PyArrayObject*)PyArray_FromObject(x, typenum, 1, 10);
if (ax == NULL) {
Expand Down Expand Up @@ -343,7 +349,10 @@ test_neighborhood_iterator_oob(PyObject* NPY_UNUSED(self), PyObject* args)
return NULL;
}

typenum = PyArray_ObjectType(x, 0);
typenum = PyArray_ObjectType(x, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}

ax = (PyArrayObject*)PyArray_FromObject(x, typenum, 1, 10);
if (ax == NULL) {
Expand Down
40 changes: 33 additions & 7 deletions numpy/core/src/multiarray/multiarraymodule.c
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Expand Up @@ -899,11 +899,15 @@ PyArray_InnerProduct(PyObject *op1, PyObject *op2)
int i;
PyObject* ret = NULL;

typenum = PyArray_ObjectType(op1, 0);
if (typenum == NPY_NOTYPE && PyErr_Occurred()) {
typenum = PyArray_ObjectType(op1, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(op2, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

typec = PyArray_DescrFromType(typenum);
if (typec == NULL) {
if (!PyErr_Occurred()) {
Expand Down Expand Up @@ -991,11 +995,15 @@ PyArray_MatrixProduct2(PyObject *op1, PyObject *op2, PyArrayObject* out)
PyArray_Descr *typec = NULL;
NPY_BEGIN_THREADS_DEF;

typenum = PyArray_ObjectType(op1, 0);
if (typenum == NPY_NOTYPE && PyErr_Occurred()) {
typenum = PyArray_ObjectType(op1, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(op2, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

typec = PyArray_DescrFromType(typenum);
if (typec == NULL) {
if (!PyErr_Occurred()) {
Expand Down Expand Up @@ -1373,8 +1381,14 @@ PyArray_Correlate2(PyObject *op1, PyObject *op2, int mode)
int inverted;
int st;

typenum = PyArray_ObjectType(op1, 0);
typenum = PyArray_ObjectType(op1, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(op2, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

typec = PyArray_DescrFromType(typenum);
Py_INCREF(typec);
Expand Down Expand Up @@ -1440,8 +1454,14 @@ PyArray_Correlate(PyObject *op1, PyObject *op2, int mode)
int unused;
PyArray_Descr *typec;

typenum = PyArray_ObjectType(op1, 0);
typenum = PyArray_ObjectType(op1, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(op2, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

typec = PyArray_DescrFromType(typenum);
Py_INCREF(typec);
Expand Down Expand Up @@ -2541,8 +2561,14 @@ array_vdot(PyObject *NPY_UNUSED(dummy), PyObject *args)
* Conjugating dot product using the BLAS for vectors.
* Flattens both op1 and op2 before dotting.
*/
typenum = PyArray_ObjectType(op1, 0);
typenum = PyArray_ObjectType(op1, NPY_NOTYPE);
if (typenum == NPY_NOTYPE) {
return NULL;
}
typenum = PyArray_ObjectType(op2, typenum);
if (typenum == NPY_NOTYPE) {
return NULL;
}

type = PyArray_DescrFromType(typenum);
Py_INCREF(type);
Expand Down
24 changes: 18 additions & 6 deletions numpy/core/tests/test_multiarray.py
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Expand Up @@ -1257,9 +1257,9 @@ def test_subarray_comparison(self):
# The main importance is that it does not return True:
with pytest.raises(TypeError):
x == y

def test_empty_structured_array_comparison(self):
# Check that comparison works on empty arrays with nontrivially
# Check that comparison works on empty arrays with nontrivially
# shaped fields
a = np.zeros(0, [('a', '<f8', (1, 1))])
assert_equal(a, a)
Expand Down Expand Up @@ -2232,7 +2232,7 @@ def assert_c(arr):
assert_c(a.copy('C'))
assert_fortran(a.copy('F'))
assert_c(a.copy('A'))

@pytest.mark.parametrize("dtype", ['O', np.int32, 'i,O'])
def test__deepcopy__(self, dtype):
# Force the entry of NULLs into array
Expand Down Expand Up @@ -2441,7 +2441,7 @@ def test_sort_unicode_kind(self):
np.array([0, 1, np.nan]),
])
def test_searchsorted_floats(self, a):
# test for floats arrays containing nans. Explicitly test
# test for floats arrays containing nans. Explicitly test
# half, single, and double precision floats to verify that
# the NaN-handling is correct.
msg = "Test real (%s) searchsorted with nans, side='l'" % a.dtype
Expand All @@ -2457,7 +2457,7 @@ def test_searchsorted_floats(self, a):
assert_equal(y, 2)

def test_searchsorted_complex(self):
# test for complex arrays containing nans.
# test for complex arrays containing nans.
# The search sorted routines use the compare functions for the
# array type, so this checks if that is consistent with the sort
# order.
Expand All @@ -2479,7 +2479,7 @@ def test_searchsorted_complex(self):
a = np.array([0, 128], dtype='>i4')
b = a.searchsorted(np.array(128, dtype='>i4'))
assert_equal(b, 1, msg)

def test_searchsorted_n_elements(self):
# Check 0 elements
a = np.ones(0)
Expand Down Expand Up @@ -6731,6 +6731,18 @@ def test_huge_vectordot(self, dtype):
res = np.dot(data, data)
assert res == 2**30+100

def test_dtype_discovery_fails(self):
# See gh-14247, error checking was missing for failed dtype discovery
class BadObject(object):
def __array__(self):
raise TypeError("just this tiny mint leaf")

with pytest.raises(TypeError):
np.dot(BadObject(), BadObject())

with pytest.raises(TypeError):
np.dot(3.0, BadObject())


class MatmulCommon:
"""Common tests for '@' operator and numpy.matmul.
Expand Down
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