Merge branch 'master' into syrk

Author: Vahid Tavanashad

.github/workflows/openssf-scorecard.yml

@@ -68,6 +68,6 @@ jobs:
 
       # Upload the results to GitHub's code scanning dashboard.
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@39edc492dbe16b1465b0cafca41432d857bdb31a # v3.29.1
+        uses: github/codeql-action/upload-sarif@181d5eefc20863364f96762470ba6f862bdef56b # v3.29.2
         with:
           sarif_file: results.sarif

CHANGELOG.md

@@ -22,6 +22,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 * Updated existing GitHub workflows to add testing with Python 3.13 [#2510](https://github.com/IntelPython/dpnp/pull/2510)
 * Aligned the license expression with `PEP-639` [#2511](https://github.com/IntelPython/dpnp/pull/2511)
 * Bumped oneMKL version up to `v0.8` [#2514](https://github.com/IntelPython/dpnp/pull/2514)
+* Removed the use of class template argument deduction for alias template to conform to the C++17 standard [#2517](https://github.com/IntelPython/dpnp/pull/2517)
 
 ### Deprecated
 

dpnp/backend/extensions/statistics/histogram.cpp

@@ -139,12 +139,14 @@ struct HistogramF
             auto dispatch_edges = [&](uint32_t local_mem, const auto &weights,
                                       auto &hist) {
                 if (device.is_gpu() && (local_mem >= bins_count + 1)) {
-                    auto edges = CachedEdges(bins_edges, bins_count + 1, cgh);
+                    auto edges =
+                        CachedEdges<BinsT>(bins_edges, bins_count + 1, cgh);
                     submit_histogram(in, size, dims, WorkPI, hist, edges,
                                      weights, nd_range, cgh);
                 }
                 else {
-                    auto edges = UncachedEdges(bins_edges, bins_count + 1, cgh);
+                    auto edges =
+                        UncachedEdges<BinsT>(bins_edges, bins_count + 1, cgh);
                     submit_histogram(in, size, dims, WorkPI, hist, edges,
                                      weights, nd_range, cgh);
                 }
@@ -165,7 +167,8 @@ struct HistogramF
                 }
                 else {
                     auto hist = HistGlobalMemory<HistType>(out);
-                    auto edges = UncachedEdges(bins_edges, bins_count + 1, cgh);
+                    auto edges =
+                        UncachedEdges<BinsT>(bins_edges, bins_count + 1, cgh);
                     submit_histogram(in, size, dims, WorkPI, hist, edges,
                                      weights, nd_range, cgh);
                 }

dpnp/tests/helper.py

@@ -456,6 +456,14 @@ def is_lts_driver(device=None):
     return dev.has_aspect_gpu and "1.3" in dev.driver_version
 
 
+def is_ptl(device=None):
+    """
+    Return True if a test is running on Panther Lake with Iris Xe3 GPU device,
+    False otherwise.
+    """
+    return _get_dev_mask(device) == 0xB000
+
+
 def is_win_platform():
     """
     Return True if a test is running on Windows OS, False otherwise.

dpnp/tests/test_product.py

@@ -12,6 +12,9 @@
     assert_dtype_allclose,
     generate_random_numpy_array,
     get_all_dtypes,
+    is_gpu_device,
+    is_ptl,
+    is_win_platform,
     numpy_version,
 )
 from .third_party.cupy import testing
@@ -1151,6 +1154,7 @@ def test_large_values(self, dtype):
         expected = numpy.matmul(a, b)
         assert_dtype_allclose(result, expected)
 
+    @pytest.mark.skipif(is_ptl(), reason="MKLD-18712")
     @pytest.mark.parametrize("dt_out", [numpy.int32, numpy.float32])
     @pytest.mark.parametrize(
         "shape1, shape2",
@@ -1495,6 +1499,9 @@ def test_invalid_axes(self, xp):
 
 @testing.with_requires("numpy>=2.2")
 class TestMatvec:
+    @pytest.mark.skipif(
+        is_win_platform() and not is_gpu_device(), reason="SAT-8073"
+    )
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))
     @pytest.mark.parametrize(
         "shape1, shape2",
@@ -2206,6 +2213,9 @@ def test_error(self, xp):
 
 @testing.with_requires("numpy>=2.2")
 class TestVecmat:
+    @pytest.mark.skipif(
+        is_win_platform() and not is_gpu_device(), reason="SAT-8073"
+    )
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))
     @pytest.mark.parametrize(
         "shape1, shape2",

dpnp/tests/test_umath.py

@@ -23,6 +23,7 @@
     has_support_aspect64,
     is_cuda_device,
     is_gpu_device,
+    is_win_platform,
 )
 
 # full list of umaths
@@ -121,6 +122,9 @@ def test_umaths(test_cases):
             pytest.skip("dpnp.modf is not supported with dpnp.float16")
         elif is_cuda_device():
             pytest.skip("dpnp.modf is not supported on CUDA device")
+    elif umath in ["vecmat", "matvec"]:
+        if is_win_platform() and not is_gpu_device():
+            pytest.skip("SAT-8073")
 
     expected = getattr(numpy, umath)(*args)
     result = getattr(dpnp, umath)(*iargs)