Rebase from master branch

.github/workflows/build-sphinx.yml

@@ -47,7 +47,7 @@ jobs:
 
     steps:
       - name: Cancel Previous Runs
-        uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # 0.12.1
+        uses: styfle/cancel-workflow-action@3155a141048f8f89c06b4cdae32e7853e97536bc # 0.13.0
         with:
           access_token: ${{ github.token }}
 

.github/workflows/check-onemath.yaml

@@ -34,7 +34,7 @@ jobs:
 
     steps:
       - name: Cancel Previous Runs
-        uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # 0.12.1
+        uses: styfle/cancel-workflow-action@3155a141048f8f89c06b4cdae32e7853e97536bc # 0.13.0
         with:
           access_token: ${{ github.token }}
 

.github/workflows/conda-package.yml

@@ -49,7 +49,7 @@ jobs:
 
     steps:
       - name: Cancel Previous Runs
-        uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # 0.12.1
+        uses: styfle/cancel-workflow-action@3155a141048f8f89c06b4cdae32e7853e97536bc # 0.13.0
         with:
           access_token: ${{ github.token }}
 

.github/workflows/cron-run-tests.yaml

@@ -43,7 +43,7 @@ jobs:
 
     steps:
       - name: Cancel Previous Runs
-        uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # 0.12.1
+        uses: styfle/cancel-workflow-action@3155a141048f8f89c06b4cdae32e7853e97536bc # 0.13.0
         with:
           access_token: ${{ github.token }}
 

.github/workflows/generate_coverage.yaml

@@ -33,7 +33,7 @@ jobs:
 
     steps:
       - name: Cancel Previous Runs
-        uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # 0.12.1
+        uses: styfle/cancel-workflow-action@3155a141048f8f89c06b4cdae32e7853e97536bc # 0.13.0
         with:
           access_token: ${{ github.token }}
 

.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@5d4e8d1aca955e8d8589aabd499c5cae939e33c7 # v4.31.9
+        uses: github/codeql-action/upload-sarif@cdefb33c0f6224e58673d9004f47f7cb3e328b89 # v4.31.10
         with:
           sarif_file: results.sarif

.pre-commit-config.yaml

@@ -2,7 +2,7 @@
 # See https://pre-commit.com/hooks.html for more hooks
 repos:
 -   repo: https://github.com/PyCQA/bandit
-    rev: '1.9.2'
+    rev: '1.9.3'
     hooks:
     -   id: bandit
         pass_filenames: false
@@ -64,7 +64,7 @@ repos:
         additional_dependencies:
             - tomli
 -   repo: https://github.com/psf/black
-    rev: 25.12.0
+    rev: 26.1.0
     hooks:
     -   id: black
         exclude: "dpnp/_version.py"
@@ -118,7 +118,7 @@ repos:
             ]
         files: '^dpnp/(dpnp_iface.*|fft|linalg|scipy|dpnp_array)'
 -   repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
-    rev: v2.15.0
+    rev: v2.16.0
     hooks:
     -   id: pretty-format-toml
         args: [--autofix]
@@ -127,7 +127,7 @@ repos:
     hooks:
     -   id: actionlint
 -   repo: https://github.com/BlankSpruce/gersemi
-    rev: 0.25.0
+    rev: 0.25.1
     hooks:
     -   id: gersemi
         exclude: "dpnp/backend/cmake/Modules/"

CHANGELOG.md

@@ -42,23 +42,31 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
 * Unified `dpnp` public API exports by consolidating function exports in `__init__.py` and removing wildcard imports [#2665](https://github.com/IntelPython/dpnp/pull/2665) [#2666](https://github.com/IntelPython/dpnp/pull/2666)
 * Updated tests to reflect the new scalar conversion rules for non-0D `usm_ndarray` [#2694](https://github.com/IntelPython/dpnp/pull/2694)
 * Compile indexing extension with `-fno-sycl-id-queries-fit-in-int` to support huge arrays [#2721](https://github.com/IntelPython/dpnp/pull/2721)
+* Updated `dpnp.fix` to reuse `dpnp.trunc` internally [#2722](https://github.com/IntelPython/dpnp/pull/2722)
+* Changed the build scripts and documentation due to `python setup.py develop` deprecation notice [#2716](https://github.com/IntelPython/dpnp/pull/2716)
+* Clarified behavior on repeated `axes` in `dpnp.tensordot` and `dpnp.linalg.tensordot` functions [#2733](https://github.com/IntelPython/dpnp/pull/2733)
 
 ### Deprecated
 
 * `dpnp.asfarray` is deprecated. Use `dpnp.asarray` with an appropriate dtype instead [#2650](https://github.com/IntelPython/dpnp/pull/2650)
 * Passing the output array ``out`` positionally to `dpnp.minimum` and `dpnp.maximum` is deprecated. Pass the output with the keyword form, e.g. ``dpnp.minimum(a, b, out=c)`` [#2659](https://github.com/IntelPython/dpnp/pull/2659)
 * `dpnp.ndarray.T` property is deprecated for not two-dimensional array to be compatible with the Python array API standard. To achieve a similar behavior when ``a.ndim != 2``, either ``a.transpose()``, or ``a.mT`` (swaps the last two axes only), or ``dpnp.permute_dims(a, range(a.ndim)[::-1])`` can be used [#2681](https://github.com/IntelPython/dpnp/pull/2681)
+* `dpnp.fix` is deprecated. Use `dpnp.trunc` instead, which provides identical functionality [#2730](https://github.com/IntelPython/dpnp/pull/2730)
 
 ### Removed
 
 * Dropped support for Python 3.9 [#2626](https://github.com/IntelPython/dpnp/pull/2626)
 * Removed the obsolete interface from DPNP to Numba JIT [#2647](https://github.com/IntelPython/dpnp/pull/2647)
 * Removed the `newshape` parameter from `dpnp.reshape`, which has been deprecated since dpnp 0.17.0. Pass it positionally or use `shape=` on newer versions [#2670](https://github.com/IntelPython/dpnp/pull/2670)
+* Removed unused `pytest` configuration from `pyproject.toml` [#2729](https://github.com/IntelPython/dpnp/pull/2729)
 
 ### Fixed
 
 * Suppressed a potential deprecation warning triggered during import of the `dpctl.tensor` module [#2709](https://github.com/IntelPython/dpnp/pull/2709)
 * Corrected a phonetic spelling issue due to incorrect using of `a nd` in docstrings [#2719](https://github.com/IntelPython/dpnp/pull/2719)
+* Resolved an issue causing `dpnp.linspace` to return an incorrect output shape when inputs were passed as arrays [#2712](https://github.com/IntelPython/dpnp/pull/2712)
+* Resolved an issue where `dpnp` always returns the base allocation pointer, when the view start is expected [#2651](https://github.com/IntelPython/dpnp/pull/2651)
+* Fixed an issue causing an exception in `dpnp.geomspace` and `dpnp.logspace` when called with explicit `device` keyword but any input array is allocated on another device [#2723](https://github.com/IntelPython/dpnp/pull/2723)
 
 ### Security
 

CMakeLists.txt

@@ -107,7 +107,7 @@ set(DPNP_TARGET_CUDA
 Set to a truthy value (e.g., ON, TRUE) to use default architecture (sm_50), \
 or to a specific architecture like sm_80."
 )
-set(HIP_TARGETS "" CACHE STRING "HIP architecture for target")
+set(DPNP_TARGET_HIP "" CACHE STRING "HIP architecture for target")
 
 set(_dpnp_sycl_targets)
 set(_use_onemath OFF)
@@ -135,18 +135,28 @@ if("x${DPNP_SYCL_TARGETS}" STREQUAL "x")
         set(_use_onemath_cuda ON)
     endif()
 
-    if(HIP_TARGETS)
-        if(HIP_TARGETS MATCHES "^gfx")
+    if(DPNP_TARGET_HIP)
+        if(DPNP_TARGET_HIP MATCHES "^gfx")
             if("x${_dpnp_sycl_targets}" STREQUAL "x")
-                set(_dpnp_sycl_targets "amd_gpu_${HIP_TARGETS},spir64-unknown-unknown")
+                set(_dpnp_sycl_targets
+                    "amd_gpu_${DPNP_TARGET_HIP},spir64-unknown-unknown"
+                )
             else()
-                set(_dpnp_sycl_targets "amd_gpu_${HIP_TARGETS},${_dpnp_sycl_targets}")
+                set(_dpnp_sycl_targets
+                    "amd_gpu_${DPNP_TARGET_HIP},${_dpnp_sycl_targets}"
+                )
             endif()
+
             set(_use_onemath_hip ON)
+            set(HIP_TARGETS
+                ${DPNP_TARGET_HIP}
+                CACHE STRING
+                "HIP GPU targets for oneMath"
+            )
         else()
             message(
                 FATAL_ERROR
-                "Invalid value for HIP_TARGETS: \"${HIP_TARGETS}\". "
+                "Invalid value for DPNP_TARGET_HIP: \"${DPNP_TARGET_HIP}\". "
                 "Expected an architecture name starting with 'gfx', e.g. 'gfx1030'."
             )
         endif()
@@ -159,11 +169,15 @@ else()
     endif()
 
     if("${DPNP_SYCL_TARGETS}" MATCHES "amd_gpu_")
-        set(_use_onemath_hip ON)
-
-        if("x${HIP_TARGETS}" STREQUAL "x")
-            message(FATAL_ERROR "HIP_TARGETS must be specified when using HIP backend")
+        if("x${DPNP_TARGET_HIP}" STREQUAL "x")
+            message(
+                FATAL_ERROR
+                "DPNP_TARGET_HIP must be specified when using HIP backend"
+            )
         endif()
+
+        set(_use_onemath_hip ON)
+        set(HIP_TARGETS ${DPNP_TARGET_HIP} CACHE STRING "HIP GPU targets for oneMath")
     endif()
 
     if("${DPNP_SYCL_TARGETS}" MATCHES "amdgcn-amd-amdhsa")
@@ -295,6 +309,16 @@ else()
     message(FATAL_ERROR "Unsupported system.")
 endif()
 
+# Define flags for CMAKE_BUILD_TYPE=Coverage
+set(CMAKE_C_FLAGS_COVERAGE "${CMAKE_C_FLAGS_DEBUG} -O1 -g1 -DDEBUG")
+set(CMAKE_CXX_FLAGS_COVERAGE "${CMAKE_CXX_FLAGS_DEBUG} -O1 -g1 -DDEBUG")
+set(CMAKE_MODULE_LINKER_FLAGS_COVERAGE "${CMAKE_MODULE_LINKER_FLAGS_DEBUG}")
+mark_as_advanced(
+    CMAKE_C_FLAGS_COVERAGE
+    CMAKE_CXX_FLAGS_COVERAGE
+    CMAKE_MODULE_LINKER_FLAGS_COVERAGE
+)
+
 if(DPNP_GENERATE_COVERAGE)
     string(
         CONCAT PROFILE_FLAGS

conda-recipe/meta.yaml

@@ -1,6 +1,6 @@
 {% set max_compiler_and_mkl_version = environ.get("MAX_BUILD_CMPL_MKL_VERSION", "2026.0a0") %}
 {% set required_compiler_and_mkl_version = "2025.0" %}
-{% set required_dpctl_version = "0.21.0" %}
+{% set required_dpctl_version = "0.22.0*" %}
 
 {% set pyproject = load_file_data('pyproject.toml') %}
 {% set py_build_deps = pyproject.get('build-system', {}).get('requires', []) %}

doc/quick_start_guide.rst

@@ -112,13 +112,15 @@ To build and install the package on Linux OS, run:
 
 .. code-block:: bash
 
-    python setup.py install -- -G Ninja -DCMAKE_C_COMPILER:PATH=icx -DCMAKE_CXX_COMPILER:PATH=icpx
+    python setup.py build_ext --inplace -- -G Ninja -DCMAKE_C_COMPILER:PATH=icx -DCMAKE_CXX_COMPILER:PATH=icpx
+    python -m pip install -e .
 
 To build and install the package on Windows OS, run:
 
 .. code-block:: bash
 
-    python setup.py install -- -G Ninja -DCMAKE_C_COMPILER:PATH=icx -DCMAKE_CXX_COMPILER:PATH=icx
+    python setup.py build_ext --inplace -- -G Ninja -DCMAKE_C_COMPILER:PATH=icx -DCMAKE_CXX_COMPILER:PATH=icx
+    python -m pip install -e .
 
 Alternatively, to develop on Linux OS, you can use the driver script:
 

dpnp/__init__.py

@@ -566,7 +566,6 @@
     kaiser,
 )
 
-
 # =============================================================================
 # Helper functions
 # =============================================================================

dpnp/backend/extensions/ufunc/CMakeLists.txt

@@ -34,7 +34,6 @@ set(_elementwise_sources
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/divmod.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/erf_funcs.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/fabs.cpp
-    ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/fix.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/float_power.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/fmax.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/elementwise_functions/fmin.cpp

dpnp/backend/extensions/ufunc/elementwise_functions/common.cpp

@@ -33,7 +33,6 @@
 #include "divmod.hpp"
 #include "erf_funcs.hpp"
 #include "fabs.hpp"
-#include "fix.hpp"
 #include "float_power.hpp"
 #include "fmax.hpp"
 #include "fmin.hpp"
@@ -67,7 +66,6 @@ void init_elementwise_functions(py::module_ m)
     init_divmod(m);
     init_erf_funcs(m);
     init_fabs(m);
-    init_fix(m);
     init_float_power(m);
     init_fmax(m);
     init_fmin(m);