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README.md

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@@ -6,6 +6,31 @@ powered version of loops used in the patched version of [NumPy](https://numpy.or
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Patches were factored out per community feedback ([NEP-36](https://numpy.org/neps/nep-0036-fair-play.html)).
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`mkl_umath` started as a part of Intel (R) Distribution for Python* optimizations to NumPy, and is now being released
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as a stand-alone package. It can be installed into conda environment using
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```
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conda install -c intel mkl_umath
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```
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---
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To install mkl_umath Pypi package please use following command:
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```
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python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_umath
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```
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If command above installs NumPy package from the Pypi, please use following command to install Intel optimized NumPy wheel package from Anaconda Cloud:
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```
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python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_umath numpy==<numpy_version>
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```
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Where `<numpy_version>` should be the latest version from https://anaconda.org/intel/numpy
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---
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## Building
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Intel(R) C compiler and Intel(R) Math Kernel Library are required to build `mkl_umath` from source:

setup.py

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with io.open('mkl_umath/_version.py', 'rt', encoding='utf8') as f:
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version = re.search(r'__version__ = \'(.*?)\'', f.read()).group(1)
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with open("README.md", "r", encoding="utf-8") as file:
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long_description = file.read()
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VERSION = version
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CLASSIFIERS = """\
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Development Status :: 0 - Alpha
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Development Status :: 5 - Production/Stable
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Intended Audience :: Science/Research
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Intended Audience :: Developers
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License :: OSI Approved
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maintainer = "Intel Corp.",
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maintainer_email = "[email protected]",
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description = "MKL-based universal functions for NumPy arrays",
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long_description = """Universal functions for real and complex floating point arrays powered by Intel(R) Math Kernel Library Vector (Intel(R) MKL) and Intel(R) Short Vector Math Library (Intel(R) SVML)""",
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long_description = long_description,
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long_description_content_type="text/markdown",
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url = "http://github.com/IntelPython/mkl_umath",
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author = "Intel Corporation",
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download_url = "http://github.com/IntelPython/mkl_umath",

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