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fixes from compiling with warnings #17

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fixes from compiling with warnings #17

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9653fe5
fixes from compiling with warnings
mattip Nov 15, 2023
47ab51b
fix error in check
mattip Nov 26, 2023
37986b0
add tp-traverse to dtype_legacy_defines
mattip Dec 7, 2023
01829b6
use legacy builtin_shape for abstract dtypes
mattip Dec 8, 2023
d82d3a0
PyArrayFlagsObject is a legacy struct
mattip Dec 10, 2023
cb60cf6
error check, add tp_traverse to flagsobject
mattip Dec 12, 2023
ccac6a1
use HPyErr_Format instead of HPyErr_SetString
mattip Dec 16, 2023
6c3201b
make PyBoundArrayMethodObject a legacy type
mattip Dec 16, 2023
1fa8ee7
remove unneeded comment
mattip Dec 23, 2023
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2 changes: 1 addition & 1 deletion numpy/core/include/numpy/ndarraytypes.h
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Expand Up @@ -930,7 +930,7 @@ typedef struct PyArrayFlagsObject {
int flags;
} PyArrayFlagsObject;

HPyType_HELPERS(PyArrayFlagsObject);
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Do you know from the top of your head if PyArrayFlagsObject still needs to be legacy? It looks like it could be a pure HPy type but we just forgot to remove PyObject_HEAD.

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No, I don't know. We could check it in a follow-up PR

HPyType_LEGACY_HELPERS(PyArrayFlagsObject);

/* Mirrors buffer object to ptr */

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2 changes: 1 addition & 1 deletion numpy/core/src/common/npy_hashtable.c
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Expand Up @@ -257,7 +257,7 @@ PyArrayIdentityHash_SetItem(PyArrayIdentityHash *tb, PyObject *cache_owner,


NPY_NO_EXPORT PyObject *
PyArrayIdentityHash_GetItem(PyObject *cache_owner, PyArrayIdentityHash const *tb, PyObject *const *key)
PyArrayIdentityHash_GetItem(PyArrayIdentityHash const *tb, PyObject *cache_owner, PyObject *const *key)
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This seems wrong? The argument order should be the same as PyArrayIdentityHash_SetItem

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Okay, makes sense. Seems that I was just not consistent in adding the cache_owner argument.

{
HPyContext *ctx = npy_get_context();
HPy h_cache_owner = HPy_FromPyObject(ctx, cache_owner);
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4 changes: 2 additions & 2 deletions numpy/core/src/common/npy_hashtable.h
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Expand Up @@ -21,8 +21,8 @@ PyArrayIdentityHash_SetItem(PyArrayIdentityHash *tb, PyObject *cache_owner,
PyObject *const *key, PyObject *value, int replace);

NPY_NO_EXPORT PyObject *
PyArrayIdentityHash_GetItem(PyObject *cache_owner,
PyArrayIdentityHash const *tb, PyObject *const *key);
PyArrayIdentityHash_GetItem(PyArrayIdentityHash const *tb, PyObject *cache_owner,
PyObject *const *key);

NPY_NO_EXPORT PyArrayIdentityHash *
PyArrayIdentityHash_New(int key_len);
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3 changes: 3 additions & 0 deletions numpy/core/src/multiarray/abstractdtypes.c
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Expand Up @@ -108,18 +108,21 @@ NPY_NO_EXPORT HPyType_Spec HPyArray_PyIntAbstractDType_spec = {
.name = "numpy._IntegerAbstractDType",
.basicsize = sizeof(PyArray_Descr),
.flags = Py_TPFLAGS_DEFAULT,
.builtin_shape = HPyType_BuiltinShape_Legacy
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If there is a HPyType(_LEGACY)_HELPERS(PyArray_Descr), we should use SHAPE(PyArray_Descr) here.

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right, but as far as I can tell there is no such use of the HEPLERS.

};

NPY_NO_EXPORT HPyType_Spec HPyArray_PyFloatAbstractDType_spec = {
.name = "numpy._FloatAbstractDType",
.basicsize = sizeof(PyArray_Descr),
.flags = HPy_TPFLAGS_DEFAULT,
.builtin_shape = HPyType_BuiltinShape_Legacy
};

NPY_NO_EXPORT HPyType_Spec HPyArray_PyComplexAbstractDType_spec = {
.name = "numpy._ComplexAbstractDType",
.basicsize = sizeof(PyArray_Descr),
.flags = HPy_TPFLAGS_DEFAULT,
.builtin_shape = HPyType_BuiltinShape_Legacy
};

// "forward" declarations:
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1 change: 1 addition & 0 deletions numpy/core/src/multiarray/array_method.c
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Expand Up @@ -1154,4 +1154,5 @@ NPY_NO_EXPORT HPyType_Spec PyBoundArrayMethod_Type_Spec = {
.basicsize = sizeof(PyBoundArrayMethodObject),
.flags = HPy_TPFLAGS_DEFAULT,
.defines = boundarraymethod_defines,
.builtin_shape = SHAPE(PyBoundArrayMethodObject),
};
3 changes: 2 additions & 1 deletion numpy/core/src/multiarray/array_method.h
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Expand Up @@ -224,12 +224,13 @@ HPyType_LEGACY_HELPERS(PyArrayMethodObject)
* on the `ArrayMethod` itself.
*/
typedef struct {
PyObject_HEAD
HPyField *dtypes; /* PyArray_DTypeMeta **dtypes */
HPyField method; /* PyArrayMethodObject *method */
int nargs; /* method->nin + method->nout */
} PyBoundArrayMethodObject;

HPyType_HELPERS(PyBoundArrayMethodObject)
HPyType_LEGACY_HELPERS(PyBoundArrayMethodObject)
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I guess this had to become a legacy type so that someone could call HPy_AsPyObject on it?

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🤔 good point. I don't think we ever specified that.
It is not required on CPython because any object is a PyObject anyway. So, it is always possible to convert.
It is not required for GraalPy because we would return a wrapper that emulates the PyObject.
Is it required for PyPy? If so, we should discuss that and maybe properly specify (and enforce spec in debug mode).

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PyPy works around it but it would be more efficient if the HELPER was correct.



extern NPY_NO_EXPORT PyTypeObject *PyArrayMethod_Type;
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2 changes: 1 addition & 1 deletion numpy/core/src/multiarray/arraytypes.c.src
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Expand Up @@ -630,7 +630,7 @@ static NPY_INLINE npy_longdouble
hpy_string_to_long_double(HPyContext *ctx, HPy op)
{
const char *s;
const char *end;
char *end;
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this caused many warnings, so either my change or all the uses of end must be const char

npy_longdouble temp;
HPy b;

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4 changes: 2 additions & 2 deletions numpy/core/src/multiarray/ctors.c
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Expand Up @@ -2331,7 +2331,7 @@ HPyArray_FromAny(HPyContext *ctx, HPy op, HPy newtype, int min_depth,
}

// TODO HPY LABS PORT
PyArrayObject *py_ret = HPy_AsPyObject(ctx, ret);
PyArrayObject *py_ret = (PyArrayObject *)HPy_AsPyObject(ctx, ret);
PyObject *py_op = HPy_AsPyObject(ctx, op);
if (setArrayFromSequence(py_ret, py_op, 0, NULL) < 0) {
Py_DECREF(py_ret);
Expand Down Expand Up @@ -4986,7 +4986,7 @@ HPyArray_ArangeObj(HPyContext *ctx, HPy start, HPy stop, HPy step, HPy /* PyArra
PyObject *new;
PyObject *py_range = HPy_AsPyObject(ctx, range);
CAPI_WARN("calling PyArray_Byteswap");
new = PyArray_Byteswap(py_range, 1);
new = PyArray_Byteswap((PyArrayObject *)py_range, 1);
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Should we perhaps do PyArrayObject *py_range = (PyArrayObject *) HPy_AsPyObject(ctx, range) where pyrange is defined?

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I think this was has fewer casts, since most places this is used prefer a PyObject*

Py_DECREF(py_range);
Py_DECREF(new);
_hpy_set_descr(ctx, range, range_struct, dtype);
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2 changes: 1 addition & 1 deletion numpy/core/src/multiarray/datetime_strings.c
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Expand Up @@ -1533,7 +1533,7 @@ datetime_as_string_impl(HPyContext *ctx, HPy NPY_UNUSED(ignored), const HPy *arg
op_flags[1] = NPY_ITER_WRITEONLY|
NPY_ITER_ALLOCATE;

iter = NpyIter_MultiNew(2, op, flags, NPY_KEEPORDER, NPY_UNSAFE_CASTING,
iter = HNpyIter_MultiNew(ctx, 2, op, flags, NPY_KEEPORDER, NPY_UNSAFE_CASTING,
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typo?

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Since op seems to contain handles, calling the new function seems to make sense.

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Yes, we probably just overlooked that.

op_flags, op_dtypes);
if (iter == NULL) {
goto fail;
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10 changes: 5 additions & 5 deletions numpy/core/src/multiarray/descriptor.c
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Expand Up @@ -425,7 +425,7 @@ _hpy_convert_from_tuple(HPyContext *ctx, HPy obj, int align)
}
newdescr_struct->flags = type_struct->flags;
newdescr_struct->alignment = type_struct->alignment;
newdescr_struct->subarray->base = HPy_AsPyObject(ctx, type);
newdescr_struct->subarray->base = (PyArray_Descr*)HPy_AsPyObject(ctx, type);
HPy_Close(ctx, type);
Py_XDECREF(newdescr_struct->fields);
HPyField_Store(ctx, newdescr, &newdescr_struct->names, HPy_NULL);
Expand Down Expand Up @@ -2230,7 +2230,7 @@ arraydescr_base_get(HPyContext *ctx, HPy /* PyArray_Descr * */ self, void *NPY_U
return HPy_Dup(ctx, self);
}
// Py_INCREF(self->subarray->base);
return HPy_FromPyObject(ctx, self_struct->subarray->base);
return HPy_FromPyObject(ctx, (PyObject*)self_struct->subarray->base);
}

HPyDef_GET(arraydescr_shape, "shape")
Expand Down Expand Up @@ -2585,7 +2585,7 @@ arraydescr_new_impl(HPyContext *ctx, HPy subtype, const HPy *args,
if (!HPyGlobal_Is(ctx, subtype, HPyArrayDescr_Type)) {
HPy subtype_type = HPy_Type(ctx, subtype);
PyArray_DTypeMeta *DType = PyArray_DTypeMeta_AsStruct(ctx, subtype);
PyTypeObject *subtype_typeobj = HPy_AsPyObject(ctx, subtype);
PyTypeObject *subtype_typeobj = (PyTypeObject*)HPy_AsPyObject(ctx, subtype);
if (HPyGlobal_Is(ctx, subtype_type, HPyArrayDTypeMeta_Type) &&
(HNPY_DT_SLOTS(ctx, subtype)) != NULL &&
!NPY_DT_is_legacy(DType) &&
Expand Down Expand Up @@ -3626,10 +3626,10 @@ HPyArray_DescrNewByteorder(HPyContext *ctx, HPy /* PyArray_Descr * */ self, char
Py_DECREF(new_data->subarray->base);
PyArray_Descr *self_data = PyArray_Descr_AsStruct(ctx, self);
CAPI_WARN("using subarray->base");
HPy base = HPy_FromPyObject(ctx, self_data->subarray->base);
HPy base = HPy_FromPyObject(ctx, (PyObject*)(self_data->subarray->base));
HPy byteorder = HPyArray_DescrNewByteorder(ctx, base, newendian);
HPy_Close(ctx, base);
new_data->subarray->base = HPy_AsPyObject(ctx, byteorder);
new_data->subarray->base = (PyArray_Descr*)HPy_AsPyObject(ctx, byteorder);
if (new_data->subarray->base == NULL) {
HPy_Close(ctx, new);
return HPy_NULL;
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4 changes: 2 additions & 2 deletions numpy/core/src/multiarray/dlpack.c
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Expand Up @@ -106,7 +106,7 @@ hpy_array_get_dl_device(HPyContext *ctx, HPy /* PyArrayObject * */ self) {
static DLDevice
array_get_dl_device(PyArrayObject *self) {
HPyContext *ctx = npy_get_context();
HPy h_self = HPy_FromPyObject(ctx, self);
HPy h_self = HPy_FromPyObject(ctx, (PyObject *)self);
DLDevice ret = hpy_array_get_dl_device(ctx, h_self);
HPy_Close(ctx, h_self);
return ret;
Expand Down Expand Up @@ -419,7 +419,7 @@ _from_dlpack_impl(HPyContext *ctx, HPy NPY_UNUSED(self), HPy obj) {

HPy new_capsule = HPyCapsule_New(ctx, managed,
NPY_DLPACK_INTERNAL_CAPSULE_NAME,
array_dlpack_internal_capsule_deleter);
(HPyCapsule_Destructor*)array_dlpack_internal_capsule_deleter);
if (HPy_IsNull(new_capsule)) {
HPy_Close(ctx, capsule);
HPy_Close(ctx, ret);
Expand Down
6 changes: 3 additions & 3 deletions numpy/core/src/multiarray/dtype_transfer.c
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Expand Up @@ -2920,7 +2920,7 @@ hpy_get_decref_transfer_function(HPyContext *ctx, int aligned,
}
src_size = PyArray_MultiplyList(src_shape.ptr, src_shape.len);
npy_free_cache_dim_obj(src_shape);
HPy h_base = HPy_FromPyObject(ctx, src_dtype_data->subarray->base);
HPy h_base = HPy_FromPyObject(ctx, (PyObject *)(src_dtype_data->subarray->base));
PyArray_Descr *base_data = src_dtype_data->subarray->base;
if (get_n_to_n_transfer_function(ctx, aligned,
src_stride, 0,
Expand Down Expand Up @@ -3669,13 +3669,13 @@ wrap_aligned_transferfunction(
HPyContext *ctx = npy_get_context();
/* These are always legacy casts that only support native-byte-order: */
// Py_INCREF(src_wrapped_dtype); // HPy_FromPyObject will incref
castdata.main.descriptors[0] = HPy_FromPyObject(ctx, src_wrapped_dtype);
castdata.main.descriptors[0] = HPy_FromPyObject(ctx, (PyObject *)src_wrapped_dtype);
if (HPy_IsNull(castdata.main.descriptors[0])) {
castdata.main.descriptors[1] = HPy_NULL;
goto fail;
}
// Py_INCREF(dst_wrapped_dtype); // HPy_FromPyObject will incref
castdata.main.descriptors[1] = HPy_FromPyObject(ctx, dst_wrapped_dtype);
castdata.main.descriptors[1] = HPy_FromPyObject(ctx, (PyObject *)dst_wrapped_dtype);
if (HPy_IsNull(castdata.main.descriptors[1])) {
goto fail;
}
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10 changes: 10 additions & 0 deletions numpy/core/src/multiarray/dtypemeta.c
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Expand Up @@ -107,6 +107,15 @@ legacy_dtype_default_new_impl(HPyContext *ctx, HPy h_self,
return HPyField_Load(ctx, h_self, self->singleton);
}

HPyDef_SLOT(legacy_dtype_tp_traverse, HPy_tp_traverse)
static int legacy_dtype_tp_traverse_impl(void *self_p, HPyFunc_visitproc visit, void *arg) {
PyArray_Descr *self = (PyArray_Descr*) self_p;
if (&self->typeobj)
HPy_VISIT(&self->typeobj);
if (&self->names)
HPy_VISIT(&self->names);
return 0;
}

//static PyArray_Descr *
//nonparametric_discover_descr_from_pyobject(
Expand Down Expand Up @@ -599,6 +608,7 @@ hpy_object_common_dtype(HPyContext *ctx, HPy /* PyArray_DTypeMeta * */ cls,

static HPyDef *new_dtype_legacy_defines[] = {
&legacy_dtype_default_new,
&legacy_dtype_tp_traverse,
NULL
};
static HPyType_Spec New_PyArrayDescr_spec_prototype = {
Expand Down
13 changes: 12 additions & 1 deletion numpy/core/src/multiarray/flagsobject.c
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Expand Up @@ -741,7 +741,7 @@ static int
arrayflags_setitem_impl(HPyContext *ctx, HPy self, HPy ind, HPy item)
{
const char *key;
const char buf[16];
char buf[16];
int n;
if (HPyUnicode_Check(ctx, ind)) {
HPy tmp_str;
Expand Down Expand Up @@ -900,6 +900,15 @@ arrayflags_new_impl(HPyContext *ctx, HPy self, const HPy *args, HPy_ssize_t narg
return HPyArray_NewFlagsObject(ctx, self, arg);
}

HPyDef_SLOT(arrayflags_traverse, HPy_tp_traverse)
static int
arrayflags_traverse_impl(void *self, HPyFunc_visitproc visit, void *arg)
{
PyArrayFlagsObject *flags = (PyArrayFlagsObject *)self;
HPy_VISIT(&flags->arr);
return 0;
}

/*
static PyType_Slot arrayflags_slots[] = {
//{Py_tp_str, arrayflags_print},
Expand Down Expand Up @@ -929,6 +938,7 @@ static HPyDef *arrayflags_defines[] = {
&arrayflags_carray,
&arrayflags_farray,
&arrayflags_num,
&arrayflags_traverse,
NULL
};

Expand All @@ -937,6 +947,7 @@ NPY_NO_EXPORT HPyType_Spec PyArrayFlags_Type_Spec = {
.basicsize = sizeof(PyArrayFlagsObject),
.flags = HPy_TPFLAGS_DEFAULT,
.defines = arrayflags_defines,
.builtin_shape = HPyType_BuiltinShape_Legacy,
};

NPY_NO_EXPORT PyTypeObject *_PyArrayFlags_Type_p;
4 changes: 2 additions & 2 deletions numpy/core/src/multiarray/item_selection.c
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Expand Up @@ -1133,7 +1133,7 @@ _new_sortlike(PyArrayObject *op, int axis, PyArray_SortFunc *sort,
size = it->size;

HPyContext *ctx = npy_get_context();
HPy h_op = HPy_FromPyObject(ctx, op);
HPy h_op = HPy_FromPyObject(ctx, (PyObject *)op);

if (needcopy) {
buffer = PyDataMem_UserNEW(N * elsize, mem_handler);
Expand Down Expand Up @@ -1205,7 +1205,7 @@ _new_sortlike(PyArrayObject *op, int axis, PyArray_SortFunc *sort,
if (needcopy) {
if (hasrefs) {
if (swap) {
HPy h_op = HPy_FromPyObject(ctx, op);
HPy h_op = HPy_FromPyObject(ctx, (PyObject *)op);
copyswapn(ctx, buffer, elsize, NULL, 0, N, swap, h_op);
}
_unaligned_strided_byte_copy(it->dataptr, astride,
Expand Down
18 changes: 11 additions & 7 deletions numpy/core/src/multiarray/mapping.c
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Expand Up @@ -1414,11 +1414,12 @@ hpy_prepare_index(HPyContext *ctx, HPy h_self, PyArrayObject *self, HPy h_index,
}
}
else if (used_ndim > PyArray_NDIM(self)) {
HPyErr_SetString(ctx, ctx->h_IndexError,
// HPyErr_SetString does not take extra arguments
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HPyErr_Format(ctx, ctx->h_IndexError,
"too many indices for array: "
"array is %d-dimensional, but %d were indexed"
/*,PyArray_NDIM(self),
used_ndim*/);
"array is %d-dimensional, but %d were indexed",
PyArray_NDIM(self),
used_ndim);
goto failed_building_indices;
}
else if (index_ndim == 0) {
Expand Down Expand Up @@ -2641,6 +2642,7 @@ NPY_NO_EXPORT int
array_assign_item_slot_impl(HPyContext *ctx, HPy /* PyArrayObject * */ self, HPy_ssize_t i, HPy op)
{
npy_index_info indices[2];
hpy_npy_index_info hpy_indices[2];

if (HPy_IsNull(op)) {
HPyErr_SetString(ctx, ctx->h_ValueError,
Expand All @@ -2664,6 +2666,8 @@ array_assign_item_slot_impl(HPyContext *ctx, HPy /* PyArrayObject * */ self, HPy

indices[0].value = i;
indices[0].type = HAS_INTEGER;
hpy_indices[0].value = i;
hpy_indices[0].type = HAS_INTEGER;
if (PyArray_NDIM(self_struct) == 1) {
char *item;
if (get_item_pointer(self_struct, &item, indices, 1) < 0) {
Expand All @@ -2677,9 +2681,9 @@ array_assign_item_slot_impl(HPyContext *ctx, HPy /* PyArrayObject * */ self, HPy
else {
HPy view; // PyArrayObject *

indices[1].value = PyArray_NDIM(self_struct) - 1;
indices[1].type = HAS_ELLIPSIS;
if (hpy_get_view_from_index(ctx, self, self_struct, &view, indices, 2, 0) < 0) {
hpy_indices[1].value = PyArray_NDIM(self_struct) - 1;
hpy_indices[1].type = HAS_ELLIPSIS;
if (hpy_get_view_from_index(ctx, self, self_struct, &view, hpy_indices, 2, 0) < 0) {
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I needed to duplicate the indices struct, since there is a call to legacy get_item_pointer for struct dtypes on line 2672 above

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Should indices be updated here too since both are being maintained?

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No. Only hpy_indices is being maintained. indices is used only in get_item_pointer in a read-only fashion.

return -1;
}
PyArrayObject *view_struct = PyArrayObject_AsStruct(ctx, view);
Expand Down
8 changes: 4 additions & 4 deletions numpy/core/src/multiarray/multiarraymodule.c
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Expand Up @@ -4226,13 +4226,13 @@ array_einsum_impl(HPyContext *ctx, HPy NPY_UNUSED(dummy), const HPy *args, size_
}
}
CAPI_WARN("calling PyArray_EinsteinSum");
PyArrayObject **py_op_in = HPy_AsPyObjectArray(ctx, op, nop);
PyArray_Descr *py_dtype = HPy_AsPyObject(ctx, dtype);
PyArrayObject *py_out = HPy_AsPyObject(ctx, out);
PyArrayObject **py_op_in = (PyArrayObject **)HPy_AsPyObjectArray(ctx, op, nop);
PyArray_Descr *py_dtype = (PyArray_Descr *)HPy_AsPyObject(ctx, dtype);
PyArrayObject *py_out = (PyArrayObject *)HPy_AsPyObject(ctx, out);
PyObject *py_ret = (PyObject *)PyArray_EinsteinSum(subscripts, nop, py_op_in, py_dtype,
order, casting, py_out);
ret = HPy_FromPyObject(ctx, py_ret);
HPy_DecrefAndFreeArray(ctx, py_op_in, nop);
HPy_DecrefAndFreeArray(ctx, (PyObject**)py_op_in, nop);
Py_XDECREF(py_dtype);
Py_XDECREF(py_out);
Py_XDECREF(py_ret);
Expand Down
2 changes: 1 addition & 1 deletion numpy/core/src/multiarray/nditer_pywrap.c
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Expand Up @@ -1644,7 +1644,7 @@ static PyObject *
npyiter_next(NewNpyArrayIterObject *self)
{
HPyContext *ctx = npy_get_context();
HPy h_self = HPy_FromPyObject(ctx, self);
HPy h_self = HPy_FromPyObject(ctx, (PyObject *)self);
HPy h_ret = hpy_npyiter_next(ctx, h_self);
PyObject *ret = HPy_AsPyObject(ctx, h_ret);
HPy_Close(ctx, h_ret);
Expand Down
6 changes: 3 additions & 3 deletions numpy/core/src/multiarray/number.c
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Expand Up @@ -505,11 +505,11 @@ is_scalar_with_conversion(HPyContext *ctx, HPy h_o2, double* out_exponent)
// NOTE: do partial porting approach, this looked small, but it isn't!
else if (PyArray_IsScalar(o2, Integer) ||
(optimize_fpexps && PyArray_IsScalar(o2, Floating))) {
temp = Py_TYPE(o2)->tp_as_number->nb_float(o2);
temp = Py_TYPE(o2)->tp_as_number->nb_float((PyObject *)o2);
if (temp == NULL) {
return NPY_NOSCALAR;
}
*out_exponent = PyFloat_AsDouble(o2);
*out_exponent = PyFloat_AsDouble((PyObject *)o2);
Py_DECREF(temp);

if (PyArray_IsScalar(o2, Integer)) {
Expand All @@ -520,7 +520,7 @@ is_scalar_with_conversion(HPyContext *ctx, HPy h_o2, double* out_exponent)
}
}
else if (PyIndex_Check((PyObject*) o2)) {
PyObject* value = PyNumber_Index(o2);
PyObject* value = PyNumber_Index((PyObject *)o2);
Py_ssize_t val;
if (value == NULL) {
if (PyErr_Occurred()) {
Expand Down
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