Merge branch 'IntelPython:master' into feature-sparse-linalg-solvers

Author: abagusetty

.github/workflows/build-sphinx.yml

@@ -197,7 +197,7 @@ jobs:
       # Upload artifact for fork PRs
       - name: Upload docs artifact (Fork PRs)
         if: env.GH_EVENT_PR_OPEN == 'true' && steps.check_fork.outputs.is_fork == 'true'
-        uses: actions/upload-artifact@65462800fd760344b1a7b4382951275a0abb4808 # v4.3.3
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
         with:
           name: pr-${{ github.event.number }}-docs
           path: ${{ env.PUBLISH_DIR }}

.github/workflows/openssf-scorecard.yml

@@ -72,6 +72,6 @@ jobs:
 
       # Upload the results to GitHub's code scanning dashboard.
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4.35.5
+        uses: github/codeql-action/upload-sarif@7211b7c8077ea37d8641b6271f6a365a22a5fbfa # v4.36.0
         with:
           sarif_file: results.sarif

.pre-commit-config.yaml

@@ -64,7 +64,7 @@ repos:
         additional_dependencies:
             - tomli
 -   repo: https://github.com/psf/black
-    rev: 26.3.1
+    rev: 26.5.1
     hooks:
     -   id: black
         exclude: "dpnp/_version.py"
@@ -128,7 +128,7 @@ repos:
     hooks:
     -   id: actionlint
 -   repo: https://github.com/BlankSpruce/gersemi-pre-commit
-    rev: 0.27.5
+    rev: 0.27.6
     hooks:
     -   id: gersemi
         exclude: "dpnp/backend/cmake/Modules/"

CHANGELOG.md

@@ -30,6 +30,8 @@ This release is compatible with NumPy 2.4.5.
 * Fixed incorrect `dpnp.tensor.acosh` result for `complex(±0, NaN)` special case to match the Python Array API specification [#2914](https://github.com/IntelPython/dpnp/pull/2914)
 * Fixed fork PR documentation workflow failures by implementing conditional publishing strategy: upstream PRs publish to GitHub Pages with comment, fork PRs upload artifacts [#2910](https://github.com/IntelPython/dpnp/pull/2910)
 * Fixed missing `libtensor` headers in the installed `dpnp` package [#2915](https://github.com/IntelPython/dpnp/pull/2915)
+* Fixed boolean mask indexing to raise `IndexError` when mask dimensions don't match the indexed array dimensions, aligning with NumPy behavior. Previously, incompatible boolean masks silently returned incorrect results instead of raising an error [#2929](https://github.com/IntelPython/dpnp/pull/2929)
+* Fixed a bug in `astype` where casting floating point types to unsigned integral types could cause an intermediate signed integral type to overflow, leading to incorrect results [#2930](https://github.com/IntelPython/dpnp/pull/2930)
 
 ### Security
 

CMakeLists.txt

@@ -247,8 +247,7 @@ if(_use_onemath)
         FetchContent_Declare(
             onemath_library
             GIT_REPOSITORY https://github.com/uxlfoundation/oneMath.git
-            GIT_TAG
-                6ff3a43e555dbb20357017d48f0f6c6263259895 # v0.9
+            GIT_TAG 6ff3a43e555dbb20357017d48f0f6c6263259895 # v0.9
         )
     endif()
 

dpnp/tensor/_slicing.pxi

@@ -107,6 +107,18 @@ cdef bint _is_boolean(object x) except *:
     return False
 
 
+cdef _check_mask_shape(sh : tuple, ma_sh : tuple, Py_ssize_t axis):
+    cdef Py_ssize_t i, sh_i, ma_i
+    for i, ma_i in enumerate(ma_sh):
+        sh_i = sh[axis + i]
+        if ma_i not in (0, sh_i):
+            raise IndexError(
+                "boolean index did not match indexed array along dimension "
+                f"{axis + i}; dimension is {sh_i} but corresponding boolean "
+                f"dimension is {ma_i}"
+            )
+
+
 def _basic_slice_meta(ind, shape : tuple, strides : tuple, offset : int):
     """
     Give basic slicing index `ind` and array layout information produce
@@ -353,6 +365,7 @@ def _basic_slice_meta(ind, shape : tuple, strides : tuple, offset : int):
                 new_advanced_ind.append(ind_i)
                 dt_k = ind_i.dtype.kind
                 if dt_k == "b":
+                    _check_mask_shape(shape, ind_i.shape, k)
                     k_new = k + ind_i.ndim
                 else:
                     k_new = k + 1

dpnp/tensor/libtensor/include/utils/type_utils.hpp

@@ -99,9 +99,14 @@ dstTy convert_impl(const srcTy &v)
     else if constexpr (!std::is_integral_v<srcTy> &&
                        !std::is_same_v<dstTy, bool> &&
                        std::is_integral_v<dstTy> && std::is_unsigned_v<dstTy>) {
-        // first cast to signed variant, the cast to unsigned one
-        using signedT = typename std::make_signed_t<dstTy>;
-        return static_cast<dstTy>(convert_impl<signedT, srcTy>(v));
+        // for negative values, cast through signed integer to get two's
+        // complement wrapping
+        using intermediateT =
+            std::conditional_t<sizeof(dstTy) < sizeof(std::int32_t),
+                               std::int32_t, std::int64_t>;
+        return (v < srcTy{0})
+                   ? static_cast<dstTy>(static_cast<intermediateT>(v))
+                   : static_cast<dstTy>(v);
     }
     else {
         return static_cast<dstTy>(v);

dpnp/tests/tensor/test_usm_ndarray_ctor.py

@@ -1100,6 +1100,15 @@ def test_astype_gh_2121():
     assert dpt.all(res == expected)
 
 
+def test_astype_gh_2882():
+    get_queue_or_skip()
+
+    x = dpt.asarray([160.0, 120.0], dtype="f4")
+    r = dpt.astype(x, dpt.uint8)
+    expected = dpt.asarray([160, 120], dtype="u1")
+    assert dpt.all(r == expected)
+
+
 def test_copy():
     try:
         X = dpt.usm_ndarray((5, 5), "i4")[2:4, 1:4]

dpnp/tests/tensor/test_usm_ndarray_indexing.py

@@ -2052,3 +2052,13 @@ def test_getitem_impl_fn_invalid_inp():
     no_array_inds = (2, 3)
     with pytest.raises(TypeError):
         _take_multi_index(x, no_array_inds, 0, 0)
+
+
+def test_boolean_mask_validation():
+    x = dpt.reshape(dpt.arange(3**5, dtype="i4"), (3,) * 5)
+    ii = dpt.asarray(1)
+    i0 = dpt.asarray(0, dtype="?")
+    i1 = dpt.asarray(0, dtype="?")
+
+    with pytest.raises(IndexError):
+        x[ii, i0[dpt.newaxis], ii, i1[dpt.newaxis], :]