Fix issues for numpy 2.1.0

.github/workflows/conda-package.yml

@@ -490,8 +490,8 @@ jobs:
         run: |
           CHANNELS="${{ env.CHANNELS }}"
           . $CONDA/etc/profile.d/conda.sh
-          conda create -n ${{ env.EXAMPLES_ENV_NAME }} -y pytest python=${{ matrix.python }} $CHANNELS
-          conda install -n ${{ env.EXAMPLES_ENV_NAME }} -y cmake">=3.22" $CHANNELS || exit 1
+          conda create -n ${{ env.EXAMPLES_ENV_NAME }} -y pytest python=${{ matrix.python }} setuptools"<72.2.0" $CHANNELS
+          conda install -n ${{ env.EXAMPLES_ENV_NAME }} -y cmake $CHANNELS || exit 1
           conda install -n ${{ env.EXAMPLES_ENV_NAME }} -y ninja $CHANNELS || exit 1
           conda install -n ${{ env.EXAMPLES_ENV_NAME }} -y pybind11 cython scikit-build $CHANNELS || exit 1
           conda install -n ${{ env.EXAMPLES_ENV_NAME }} -y mkl-dpcpp mkl-devel-dpcpp dpcpp_cpp_rt $CHANNELS || exit 1

.github/workflows/generate-coverage.yaml

@@ -15,7 +15,7 @@ jobs:
 
     env:
       ONEAPI_ROOT: /opt/intel/oneapi
-      GTEST_ROOT: /home/runner/work/googletest-1.13.0/install
+      GTEST_ROOT: /home/runner/work/googletest-1.15.2/install
       # Use oneAPI compiler 2023 to work around an issue
       USE_2023: 0
 
@@ -52,16 +52,16 @@ jobs:
       - name: Setup Python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.11'
+          python-version: '3.12'
           architecture: x64
 
       - name: Cache Gtest
         id: cache-gtest
         uses: actions/cache@v4
         with:
           path: |
-            /home/runner/work/googletest-1.13.0/install
-          key: ${{ runner.os }}-build-${{ env.cache-name }}-${{ hashFiles('/home/runner/work/googletest-1.13.0/install/include/gtest/*') }}
+            /home/runner/work/googletest-1.15.2/install
+          key: ${{ runner.os }}-build-${{ env.cache-name }}-${{ hashFiles('/home/runner/work/googletest-1.15.2/install/include/gtest/*') }}
           restore-keys: |
             ${{ runner.os }}-build-${{ env.cache-name }}-
             ${{ runner.os }}-build-
@@ -72,12 +72,12 @@ jobs:
         shell: bash -l {0}
         run: |
           cd /home/runner/work
-          wget https://github.com/google/googletest/archive/refs/tags/v1.13.0.tar.gz
-          tar xf v1.13.0.tar.gz
-          cd googletest-1.13.0
+          wget https://github.com/google/googletest/archive/refs/tags/v1.15.2.tar.gz
+          tar xf v1.15.2.tar.gz
+          cd googletest-1.15.2
           mkdir build
           cd build
-          cmake .. -DCMAKE_INSTALL_PREFIX=/home/runner/work/googletest-1.13.0/install
+          cmake .. -DCMAKE_INSTALL_PREFIX=/home/runner/work/googletest-1.15.2/install
           make && make install
 
       - name: Checkout repo
@@ -92,7 +92,7 @@ jobs:
       - name: Install dpctl dependencies
         shell: bash -l {0}
         run: |
-          pip install numpy"<1.26.0" cython setuptools pytest pytest-cov scikit-build cmake coverage[toml] versioneer[toml]==0.29
+          pip install numpy cython setuptools pytest pytest-cov scikit-build cmake coverage[toml] versioneer[toml]==0.29
 
       - name: Build dpctl with coverage
         shell: bash -l {0}

.github/workflows/os-llvm-sycl-build.yml

@@ -100,7 +100,7 @@ jobs:
       - name: Setup Python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.11'
+          python-version: '3.12'
           architecture: x64
 
       - name: Install dpctl dependencies

dpctl/tensor/_ctors.py

@@ -765,8 +765,11 @@ def _get_arange_length(start, stop, step):
 
 
 def _to_scalar(obj, sc_ty):
-    "A way to convert object to NumPy scalar type"
-    zd_arr = np.asarray(obj).astype(sc_ty, casting="unsafe")
+    """A way to convert object to NumPy scalar type.
+    Raises OverflowError if obj can not be represented
+    using the requested scalar type.
+    """
+    zd_arr = np.asarray(obj, dtype=sc_ty)
     return zd_arr[tuple()]
 
 

dpctl/tensor/_dlpack.pyx

@@ -1083,9 +1083,10 @@ def from_dlpack(x, /, *, device=None, copy=None):
     except TypeError:
         # exporter does not support max_version keyword
         got_type_error = True
-    except (BufferError, NotImplementedError):
-        # Either dl_device, or copy can be satisfied
+    except (BufferError, NotImplementedError, ValueError) as e:
+        # Either dl_device, or copy cannot be satisfied
         got_buffer_error = True
+        saved_exception = e
     except Exception as e:
         got_other_error = True
         saved_exception = e
@@ -1144,6 +1145,8 @@ def from_dlpack(x, /, *, device=None, copy=None):
                 raise BufferError(
                     "Importing data via DLPack requires copying, but copy=False was provided"
                 )
+            if dl_device is None:
+                raise saved_exception
             # must copy via host
             if dl_device[0] != device_OneAPI:
                 raise BufferError(f"Can not import to requested device {dl_device}")

dpctl/tests/test_sycl_kernel_submit.py

@@ -66,6 +66,9 @@ def test_create_program_from_source(ctype_str, dtype, ctypes_ctor):
 
     n_elems = 1024 * 512
     lws = 128
+    if dtype.kind in "ui":
+        n_elems = min(n_elems, dpt.iinfo(dtype).max)
+        n_elems = (n_elems // lws) * lws
     a = dpt.arange(n_elems, dtype=dtype, sycl_queue=q)
     b = dpt.arange(n_elems, stop=0, step=-1, dtype=dtype, sycl_queue=q)
     c = dpt.zeros(n_elems, dtype=dtype, sycl_queue=q)

dpctl/tests/test_usm_ndarray_ctor.py

@@ -1791,17 +1791,22 @@ def test_full_strides():
     assert np.array_equal(dpt.asnumpy(X), Xnp)
 
 
-def test_full_gh_1230():
-    q = get_queue_or_skip()
-    dtype = "i4"
+@pytest.mark.parametrize("dt", ["i1", "u1", "i2", "u2", "i4", "u4", "i8", "u8"])
+def test_full_gh_1230(dt):
+    get_queue_or_skip()
+    dtype = dpt.dtype(dt)
     dt_maxint = dpt.iinfo(dtype).max
-    X = dpt.full(1, dt_maxint + 1, dtype=dtype, sycl_queue=q)
-    X_np = dpt.asnumpy(X)
-    assert X.dtype == dpt.dtype(dtype)
-    assert np.array_equal(X_np, np.full_like(X_np, dt_maxint + 1))
 
-    with pytest.raises(OverflowError):
-        dpt.full(1, dpt.iinfo(dpt.uint64).max + 1, sycl_queue=q)
+    if (dtype.itemsize < 8) and (np.lib.NumpyVersion(np.__version__) < "2.0.0"):
+        try:
+            X = dpt.full(1, fill_value=(dt_maxint + 1), dtype=dt)
+        except OverflowError:
+            pytest.skip("Expected OverflowError raised")
+        Y = dpt.full_like(X, fill_value=dpt.iinfo(dt).min)
+        assert dpt.all(X == Y)
+    else:
+        with pytest.raises(OverflowError):
+            dpt.full(1, dt_maxint + 1, dtype=dt)
 
 
 @pytest.mark.parametrize(

dpctl/tests/test_usm_ndarray_linalg.py

@@ -89,12 +89,20 @@ def test_matmul_simple(dtype):
     skip_if_dtype_not_supported(dtype, q)
 
     n, m = 235, 17
-    m1 = dpt.ones((m, n), dtype=dtype)
-    m2 = dpt.ones((n, m), dtype=dtype)
+    m1 = dpt.zeros((m, n), dtype=dtype)
+    m2 = dpt.zeros((n, m), dtype=dtype)
+
+    dt = m1.dtype
+    if dt.kind in "ui":
+        n1 = min(n, dpt.iinfo(dt).max)
+    else:
+        n1 = n
+    m1[:, :n1] = dpt.ones((m, n1), dtype=dt)
+    m2[:n1, :] = dpt.ones((n1, m), dtype=dt)
 
     for k in [1, 2, 3, 4, 7, 8, 9, 15, 16, 17]:
         r = dpt.matmul(m1[:k, :], m2[:, :k])
-        assert dpt.all(r == dpt.full((k, k), n, dtype=dtype))
+        assert dpt.all(r == dpt.full((k, k), fill_value=n1, dtype=dt))
 
 
 @pytest.mark.parametrize("dtype", _numeric_types)