Fix dpnp.repeat with uint64 repeats above the int64 maximum

CHANGELOG.md

@@ -121,6 +121,7 @@ This release is compatible with NumPy 2.5.
 * Fixed `dpnp.median` and `dpnp.nanmedian` raising a `ValueError` for a tuple `axis` when a kept dimension has size 0 [#3081](https://github.com/IntelPython/dpnp/pull/3081)
 * Fixed a `RuntimeError` raised by `dpnp.tensor` kernels launched over more than `INT_MAX` work-items when built with DPC++ compiler 2026.2 or newer, by also passing `-fno-sycl-id-queries-fit-in-int` to the linker [#3089](https://github.com/IntelPython/dpnp/pull/3089)
 * Fixed `dpnp.__all__` missing `ndarray` and `__array_namespace_info__` and listing `mean`, `median` and `min` twice [#3100](https://github.com/IntelPython/dpnp/pull/3100)
+* Fixed `dpnp.repeat` and `dpnp.tensor.repeat` silently returning wrong results for `uint64` repeats above the `int64` maximum [#3115](https://github.com/IntelPython/dpnp/pull/3115)
 
 ### Security
 

dpnp/tensor/_manipulation_functions.py

@@ -638,8 +638,12 @@ def repeat(x, repeats, /, *, axis=None):
         if not dpt.can_cast(repeats.dtype, dpt.int64, casting="same_kind"):
             raise TypeError(
                 f"'repeats' data type {repeats.dtype} cannot be cast to "
-                "'int64' according to the casting rule ''safe.''"
+                "'int64' according to the casting rule ''same_kind.''"
             )
+        err_msg = "`repeats` elements must be positive"
+        if repeats.dtype == dpt.uint64:
+            repeats = dpt.astype(repeats, dpt.int64)
+            err_msg = "`repeats` elements must not exceed the int64 maximum"
         if repeats.size == 1:
             scalar = True
             # bring the single element to the host
@@ -650,15 +654,15 @@ def repeat(x, repeats, /, *, axis=None):
                 # since non-0D arrays can not be converted to scalars
                 repeats = int(repeats[0])
             if repeats < 0:
-                raise ValueError("`repeats` elements must be positive")
+                raise ValueError(err_msg)
         else:
             if repeats.size != axis_size:
                 raise ValueError(
                     "'repeats' array must be broadcastable to the size of "
                     "the repeated axis"
                 )
             if not dpt.all(repeats >= 0):
-                raise ValueError("'repeats' elements must be positive")
+                raise ValueError(err_msg)
 
     elif isinstance(repeats, (tuple, list, range)):
         usm_type = x.usm_type

dpnp/tests/tensor/test_usm_ndarray_manipulation.py

@@ -1509,6 +1509,14 @@ def test_repeat_arg_validation():
     with pytest.raises(ValueError):
         dpt.repeat(x, reps)
 
+    # u8 repeats above i8 max
+    reps = dpt.asarray(2**64 - 1, dtype="u8")
+    with pytest.raises(ValueError, match="int64 maximum"):
+        dpt.repeat(x, reps)
+    reps = dpt.asarray([1, 1, 2**64 - 1, 1, 1], dtype="u8")
+    with pytest.raises(ValueError, match="int64 maximum"):
+        dpt.repeat(x, reps)
+
     # repeats must broadcastable to axis size
     reps = dpt.arange(10, dtype="i8")
     with pytest.raises(ValueError):