8000 ENH: Allow an arbitrary number of operands in nditer by seberg · Pull Request #28080 · numpy/numpy · GitHub
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ENH: Allow an arbitrary number of operands in nditer #28080

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Merged
merged 5 commits into from
Jan 6, 2025
Merged

ENH: Allow an arbitrary number of operands in nditer #28080

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b592672
ENH: Allow an arbitrary number of operands in nditer
seberg Dec 19, 2024
a41abb3
BUG,TST: Test nested_iters and remove missed MAXARGS use
seberg Dec 31, 2024
a380ff2
MAINT: Add (unnecessary) error check on npyiter_cache_values
seberg Dec 31, 2024
81f5618
Address Marten's review comments
seberg Jan 2, 2025
5097048
More smaller fixes from review (and previous commmit)
seberg Jan 2, 2025
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1 change: 1 addition & 0 deletions doc/release/upcoming_changes/28080.c_api.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
* ``NpyIter`` now has no limit on the number of operands it supports.
2 changes: 2 additions & 0 deletions doc/release/upcoming_changes/28080.improvement.rst
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@@ -0,0 +1,2 @@
* ``np.nditer`` now has no limit on the number of supported operands
(C-integer).
34 changes: 18 additions & 16 deletions numpy/_core/src/multiarray/nditer_constr.c
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Expand Up @@ -50,7 +50,7 @@ npyiter_prepare_operands(int nop,
PyArray_Descr **op_dtype,
npy_uint32 flags,
npy_uint32 *op_flags, npyiter_opitflags *op_itflags,
npy_int8 *out_maskop);
int *out_maskop);
static int
npyiter_check_casting(int nop, PyArrayObject **op,
PyArray_Descr **op_dtype,
Expand Down Expand Up @@ -100,7 +100,7 @@ npyiter_get_priority_subtype(int nop, PyArrayObject **op,
static int
npyiter_allocate_transfer_functions(NpyIter *iter);

static void
static int
npyiter_find_buffering_setup(NpyIter *iter, npy_intp buffersize);

/*NUMPY_API
Expand Down Expand Up @@ -158,13 +158,6 @@ NpyIter_AdvancedNew(int nop, PyArrayObject **op_in, npy_uint32 flags,

NPY_IT_TIME_POINT(c_start);

if (nop > NPY_MAXARGS) {
PyErr_Format(PyExc_ValueError,
"Cannot construct an iterator with more than %d operands "
"(%d were requested)", NPY_MAXARGS, nop);
return NULL;
}

/*
* Before 1.8, if `oa_ndim == 0`, this meant `op_axes != NULL` was an error.
* With 1.8, `oa_ndim == -1` takes this role, while op_axes in that case
Expand Down Expand Up @@ -433,7 +426,10 @@ NpyIter_AdvancedNew(int nop, PyArrayObject **op_in, npy_uint32 flags,

/* If buffering is set prepare it */
if (itflags & NPY_ITFLAG_BUFFER) {
npyiter_find_buffering_setup(iter, buffersize);
if (npyiter_find_buffering_setup(iter, buffersize) < 0) {
NpyIter_Deallocate(iter);
return NULL;
}

/*
* Initialize for use in FirstVisit, which may be called before
Expand Down Expand Up @@ -1168,10 +1164,10 @@ npyiter_prepare_operands(int nop, PyArrayObject **op_in,
PyArray_Descr **op_dtype,
npy_uint32 flags,
npy_uint32 *op_flags, npyiter_opitflags *op_itflags,
npy_int8 *out_maskop)
int *out_maskop)
{
int iop, i;
npy_int8 maskop = -1;
int maskop = -1;
int any_writemasked_ops = 0;

/*
Expand Down Expand Up @@ -2001,22 +1997,27 @@ operand_different_than_broadcast: {
* In theory, the reduction could also span multiple axes if other operands
* are buffered. We do not try to discover this.
*/
static void
static int
npyiter_find_buffering_setup(NpyIter *iter, npy_intp buffersize)
{
int nop = iter->nop;
int ndim = iter->ndim;
npy_uint32 itflags = iter->itflags;
NpyIter_BufferData *bufferdata = NIT_BUFFERDATA(iter);

/* Per operand space; could also reuse an iterator field initialized later */
NPY_ALLOC_WORKSPACE(dim_scratch_space, int, 10, 2 * nop);
if (dim_scratch_space == NULL) {
return -1;
}
/*
* We check two things here, first how many operand dimensions can be
* iterated using a single stride (all dimensions are consistent),
* and second, whether we found a reduce dimension for the operand.
* That is an outer dimension a reduce would have to take place on.
*/
int op_single_stride_dims[NPY_MAXARGS];
int op_reduce_outer_dim[NPY_MAXARGS];
int *op_single_stride_dims = dim_scratch_space;
int *op_reduce_outer_dim = dim_scratch_space + nop;

npy_intp sizeof_axisdata = NIT_AXISDATA_SIZEOF(itflags, ndim, nop);
NpyIter_AxisData *axisdata = NIT_AXISDATA(iter);
Expand Down Expand Up @@ -2312,7 +2313,8 @@ npyiter_find_buffering_setup(NpyIter *iter, npy_intp buffersize)
/* Core starts at 0 initially, if needed it is set in goto index. */
NIT_BUFFERDATA(iter)->coreoffset = 0;

return;
npy_free_workspace(dim_scratch_space);
return 0;
}


Expand Down
4 changes: 2 additions & 2 deletions numpy/_core/src/multiarray/nditer_impl.h
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Expand Up @@ -152,8 +152,8 @@
struct NpyIter_InternalOnly {
/* Initial fixed position data */
npy_uint32 itflags;
npy_uint8 ndim, nop;
npy_int8 maskop;
n 8E1E py_uint8 ndim;
int nop, maskop;
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So I think effectively, this means we need 64bit more space here (on typical systems). A bit unfortunate, but even if we limit to int16, we lose 32bits here anyway.

npy_intp itersize, iterstart, iterend;
/* iterindex is only used if RANGED or BUFFERED is set */
npy_intp iterindex;
Expand Down
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