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diff --git a/numpy/__config__.py.in b/numpy/__config__.py.in
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+# This file is generated by numpy's build process
+# It contains system_info results at the time of building this package.
+__all__ = ["get_info", "show"]
+
+import os
+import sys
+
+extra_dll_dir = os.path.join(os.path.dirname(__file__), '.libs')
+
+if sys.platform == 'win32' and os.path.isdir(extra_dll_dir):
+    os.add_dll_directory(extra_dll_dir)
+
+blas_armpl_info={}
+blas_mkl_info={}
+blis_info={}
+openblas_info={}
+accelerate_info={}
+atlas_3_10_blas_threads_info={}
+atlas_3_10_blas_info={}
+atlas_blas_threads_info={}
+atlas_blas_info={}
+blas_info={}
+blas_src_info={}
+blas_opt_info={}
+lapack_armpl_info={}
+lapack_mkl_info={}
+openblas_lapack_info={}
+openblas_clapack_info={}
+flame_info={}
+atlas_3_10_threads_info={}
+atlas_3_10_info={}
+atlas_threads_info={}
+atlas_info={}
+lapack_info={}
+lapack_src_info={}
+lapack_opt_info={}
+numpy_linalg_lapack_lite={}
+
+def get_info(name):
+    g = globals()
+    return g.get(name, g.get(name + "_info", {}))
+
+def show():
+    """
+    Show libraries in the system on which NumPy was built.
+
+    Print information about various resources (libraries, library
+    directories, include directories, etc.) in the system on which
+    NumPy was built.
+
+    See Also
+    --------
+    get_include : Returns the directory containing NumPy C
+                  header files.
+
+    Notes
+    -----
+    1. Classes specifying the information to be printed are defined
+       in the `numpy.distutils.system_info` module.
+
+       Information may include:
+
+       * ``language``: language used to write the libraries (mostly
+         C or f77)
+       * ``libraries``: names of libraries found in the system
+       * ``library_dirs``: directories containing the libraries
+       * ``include_dirs``: directories containing library header files
+       * ``src_dirs``: directories containing library source files
+       * ``define_macros``: preprocessor macros used by
+         ``distutils.setup``
+       * ``baseline``: minimum CPU features required
+       * ``found``: dispatched features supported in the system
+       * ``not found``: dispatched features that are not supported
+         in the system
+
+    2. NumPy BLAS/LAPACK Installation Notes
+
+       Installing a numpy wheel (``pip install numpy`` or force it
+       via ``pip install numpy --only-binary :numpy: numpy``) includes
+       an OpenBLAS implementation of the BLAS and LAPACK linear algebra
+       APIs. In this case, ``library_dirs`` reports the original build
+       time configuration as compiled with gcc/gfortran; at run time
+       the OpenBLAS library is in
+       ``site-packages/numpy.libs/`` (linux), or
+       ``site-packages/numpy/.dylibs/`` (macOS), or
+       ``site-packages/numpy/.libs/`` (windows).
+
+       Installing numpy from source
+       (``pip install numpy --no-binary numpy``) searches for BLAS and
+       LAPACK dynamic link libraries at build time as influenced by
+       environment variables NPY_BLAS_LIBS, NPY_CBLAS_LIBS, and
+       NPY_LAPACK_LIBS; or NPY_BLAS_ORDER and NPY_LAPACK_ORDER;
+       or the optional file ``~/.numpy-site.cfg``.
+       NumPy remembers those locations and expects to load the same
+       libraries at run-time.
+       In NumPy 1.21+ on macOS, 'accelerate' (Apple's Accelerate BLAS
+       library) is in the default build-time search order after
+       'openblas'.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.show_config()
+    blas_opt_info:
+        language = c
+        define_macros = [('HAVE_CBLAS', None)]
+        libraries = ['openblas', 'openblas']
+        library_dirs = ['/usr/local/lib']
+    """
+    from numpy.core._multiarray_umath import (
+        __cpu_features__, __cpu_baseline__, __cpu_dispatch__
+    )
+    for name,info_dict in globals().items():
+        if name[0] == "_" or type(info_dict) is not type({}): continue
+        print(name + ":")
+        if not info_dict:
+            print("  NOT AVAILABLE")
+        for k,v in info_dict.items():
+            v = str(v)
+            if k == "sources" and len(v) > 200:
+                v = v[:60] + " ...\n... " + v[-60:]
+            print("    %s = %s" % (k,v))
+
+    features_found, features_not_found = [], []
+    for feature in __cpu_dispatch__:
+        if __cpu_features__[feature]:
+            features_found.append(feature)
+        else:
+            features_not_found.append(feature)
+
+    print("Supported SIMD extensions in this NumPy install:")
+    print("    baseline = %s" % (','.join(__cpu_baseline__)))
+    print("    found = %s" % (','.join(features_found)))
+    print("    not found = %s" % (','.join(features_not_found)))