Fix abort in dpnp.all / dpnp.any over an empty axis

CHANGELOG.md

@@ -78,6 +78,7 @@ This release is compatible with NumPy 2.5.
 * Fixed `dpnp.interp` returning `nan` when querying at an exact knot point whose adjacent `fp` value is `inf` [#2986](https://github.com/IntelPython/dpnp/pull/2986)
 * Fixed missing strides validation in `dpnp.tensor.usm_ndarray` constructor when allocating new memory [#2927](https://github.com/IntelPython/dpnp/pull/2927)
 * Fixed `dpnp.bincount` raising a `ValueError` on an empty input array instead of returning an empty `intp` array [#3018](https://github.com/IntelPython/dpnp/pull/3018)
+* Fixed `dpnp.all` and `dpnp.any` aborting when reducing over an empty axis (e.g. an array with a zero-length dimension) [#3021](https://github.com/IntelPython/dpnp/pull/3021)
 
 ### Security
 

dpnp/tensor/_utility_functions.py

@@ -48,7 +48,7 @@
 )
 
 
-def _boolean_reduction(x, axis, keepdims, func):
+def _boolean_reduction(x, axis, keepdims, func, identity):
     if not isinstance(x, dpt.usm_ndarray):
         raise TypeError(f"Expected dpnp.tensor.usm_ndarray, got {type(x)}")
 
@@ -77,37 +77,48 @@ def _boolean_reduction(x, axis, keepdims, func):
     exec_q = x.sycl_queue
     res_usm_type = x.usm_type
 
-    _manager = du.SequentialOrderManager[exec_q]
-    dep_evs = _manager.submitted_events
-    # always allocate the temporary as
-    # int32 and usm-device  to ensure that atomic updates
-    # are supported
-    res_tmp = dpt.empty(
-        res_shape,
-        dtype=dpt.int32,
-        usm_type="device",
-        sycl_queue=exec_q,
-    )
-    hev0, ev0 = func(
-        src=x_tmp,
-        trailing_dims_to_reduce=red_nd,
-        dst=res_tmp,
-        sycl_queue=exec_q,
-        depends=dep_evs,
-    )
-    _manager.add_event_pair(hev0, ev0)
-
-    # copy to boolean result array
-    res = dpt.empty(
-        res_shape,
-        dtype=dpt.bool,
-        usm_type=res_usm_type,
-        sycl_queue=exec_q,
-    )
-    hev1, ev1 = ti._copy_usm_ndarray_into_usm_ndarray(
-        src=res_tmp, dst=res, sycl_queue=exec_q, depends=[ev0]
-    )
-    _manager.add_event_pair(hev1, ev1)
+    if x_tmp.size == 0:
+        # nothing to reduce over: the result is either empty (a non-reduced
+        # dimension is zero) or filled with the reduction identity (a reduced
+        # dimension is zero, e.g. all([]) is True and any([]) is False)
+        res = dpt.full(
+            res_shape,
+            identity,
+            dtype=dpt.bool,
+            usm_type=res_usm_type,
+            sycl_queue=exec_q,
+        )
+    else:
+        _manager = du.SequentialOrderManager[exec_q]
+        dep_evs = _manager.submitted_events
+        # always allocate the temporary as int32 and usm-device to ensure
+        # that atomic updates are supported
+        res_tmp = dpt.empty(
+            res_shape,
+            dtype=dpt.int32,
+            usm_type="device",
+            sycl_queue=exec_q,
+        )
+        hev0, ev0 = func(
+            src=x_tmp,
+            trailing_dims_to_reduce=red_nd,
+            dst=res_tmp,
+            sycl_queue=exec_q,
+            depends=dep_evs,
+        )
+        _manager.add_event_pair(hev0, ev0)
+
+        # copy to boolean result array
+        res = dpt.empty(
+            res_shape,
+            dtype=dpt.bool,
+            usm_type=res_usm_type,
+            sycl_queue=exec_q,
+        )
+        hev1, ev1 = ti._copy_usm_ndarray_into_usm_ndarray(
+            src=res_tmp, dst=res, sycl_queue=exec_q, depends=[ev0]
+        )
+        _manager.add_event_pair(hev1, ev1)
 
     if keepdims:
         res_shape = res_shape + (1,) * red_nd
@@ -142,7 +153,7 @@ def all(x, /, *, axis=None, keepdims=False):
             An array with a data type of `bool`
             containing the results of the logical AND reduction.
     """
-    return _boolean_reduction(x, axis, keepdims, tri._all)
+    return _boolean_reduction(x, axis, keepdims, tri._all, True)
 
 
 def any(x, /, *, axis=None, keepdims=False):
@@ -171,7 +182,7 @@ def any(x, /, *, axis=None, keepdims=False):
             An array with a data type of `bool`
             containing the results of the logical OR reduction.
     """
-    return _boolean_reduction(x, axis, keepdims, tri._any)
+    return _boolean_reduction(x, axis, keepdims, tri._any, False)
 
 
 def _validate_diff_shape(sh1, sh2, axis):