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Update build and install instructions in Quick start guide (#2395)
As reported in #2388 the instruction was not complete and caused compilation error. The PR proposes to add `dppy/label/dev` channel in `conda create` command to mitigate the issue. Also the list of conda packages was extended to install `intel-gpu-ocl-icd-system` conda package, because FFT function will fail otherwise.
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CHANGELOG.md

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### Changed
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* 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)
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* 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)
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* Allowed input array of `uint64` dtype in `dpnp.bincount` [#2361](https://github.com/IntelPython/dpnp/pull/2361)
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* 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)
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* 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)
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* 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)
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### Fixed
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* 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)
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* 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)
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## [0.17.0] - 02/26/2025

doc/quick_start_guide.rst

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.. code-block:: bash
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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
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conda create -n build-env dpctl cython dpcpp_linux-64 mkl-devel-dpcpp tbb-devel \
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onedpl-devel cmake scikit-build ninja pytest intel-gpu-ocl-icd-system \
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-c dppy/label/dev -c https://software.repos.intel.com/python/conda/ -c conda-forge
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conda activate build-env
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On Windows:
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.. code-block:: bash
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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
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conda create -n build-env dpctl cython dpcpp_win-64 mkl-devel-dpcpp tbb-devel \
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onedpl-devel cmake scikit-build ninja pytest intel-gpu-ocl-icd-system \
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-c dppy/label/dev -c https://software.repos.intel.com/python/conda/ -c conda-forge
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conda activate build-env
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To build and install the package on Linux OS, run:

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