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5 changes: 3 additions & 2 deletions CHANGELOG.md
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Expand Up @@ -15,14 +15,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

### Changed

* Extended `dpnp.fft.fftfreq` and `dpnp.fft.rfftfreq` functions to support `dtype` keyword per Python Array API spec 2024.12 [#2384](https://github.com/IntelPython/dpnp/pull/2384)
* Improved performance of `dpnp.nansum`, `dpnp.nanprod`, `dpnp.nancumsum`, and `dpnp.nancumprod` by reusing `dpnp.nan_to_num` function in implementation of the functions [#2339](https://github.com/IntelPython/dpnp/pull/2339)
* Allowed input array of `uint64` dtype in `dpnp.bincount` [#2361](https://github.com/IntelPython/dpnp/pull/2361)
* The vector norms `ord={None, 1, 2, inf}` and the matrix norms `ord={None, 1, 2, inf, "fro", "nuc"}` now consistently return zero for empty arrays, which are arrays with at least one axis of size zero. This change affects `dpnp.linalg.norm`, `dpnp.linalg.vector_norm`, and `dpnp.linalg.matrix_norm`. Previously, dpnp would either raise errors or return zero depending on the parameters provided [#2371](https://github.com/IntelPython/dpnp/pull/2371)
* Improved performance of `dpnp.nansum`, `dpnp.nanprod`, `dpnp.nancumsum`, and `dpnp.nancumprod` by reusing `dpnp.nan_to_num` function in implementation of the functions [#2339](https://github.com/IntelPython/dpnp/pull/2339)
* Extended `dpnp.fft.fftfreq` and `dpnp.fft.rfftfreq` functions to support `dtype` keyword per Python Array API spec 2024.12 [#2384](https://github.com/IntelPython/dpnp/pull/2384)

### Fixed

* Resolved an issue with an incorrect result returned due to missing dependency from the strided kernel on a copy event in `dpnp.erf` [#2378](https://github.com/IntelPython/dpnp/pull/2378)
* Updated `conda create` commands build and install instructions of `Quick start guide` to avoid a compilation error [#2395](https://github.com/IntelPython/dpnp/pull/2395)


## [0.17.0] - 02/26/2025
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8 changes: 6 additions & 2 deletions doc/quick_start_guide.rst
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Expand Up @@ -88,14 +88,18 @@ On Linux:

.. code-block:: bash

conda create -n build-env dpctl cython dpcpp_linux-64 mkl-devel-dpcpp tbb-devel onedpl-devel cmake scikit-build ninja pytest -c https://software.repos.intel.com/python/conda/ -c conda-forge
conda create -n build-env dpctl cython dpcpp_linux-64 mkl-devel-dpcpp tbb-devel \
onedpl-devel cmake scikit-build ninja pytest -c dppy/label/dev \
-c https://software.repos.intel.com/python/conda/ -c conda-forge
conda activate build-env

On Windows:

.. code-block:: bash

conda create -n build-env dpctl cython dpcpp_win-64 mkl-devel-dpcpp tbb-devel onedpl-devel cmake scikit-build ninja pytest -c https://software.repos.intel.com/python/conda/ -c conda-forge
conda create -n build-env dpctl cython dpcpp_win-64 mkl-devel-dpcpp tbb-devel \
onedpl-devel cmake scikit-build ninja pytest -c dppy/label/dev \
-c https://software.repos.intel.com/python/conda/ -c conda-forge
conda activate build-env

To build and install the package on Linux OS, run:
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