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task: add patch methods for mkl_random #90
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ndgrigorian
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IntelPython:master
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jharlow-intel:task/patch-numpy
Mar 10, 2026
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f007ddd
task: add patch methods for mkl_random
jharlow-intel 15404d2
Merge branch 'master' into task/patch-numpy
jharlow-intel 38fe23d
fix: patching to match mkl_fft, lint, and review
jharlow-intel 0a94878
fix: testing
jharlow-intel 8a8b942
chore: update CHANGELOG
jharlow-intel 4055e3c
task: review fixes
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,184 @@ | ||
| # Copyright (c) 2019, Intel Corporation | ||
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|
||
| # | ||
| # Redistribution and use in source and binary forms, with or without | ||
| # modification, are permitted provided that the following conditions are met: | ||
| # | ||
| # * Redistributions of source code must retain the above copyright notice, | ||
| # this list of conditions and the following disclaimer. | ||
| # * Redistributions in binary form must reproduce the above copyright | ||
| # notice, this list of conditions and the following disclaimer in the | ||
| # documentation and/or other materials provided with the distribution. | ||
| # * Neither the name of Intel Corporation nor the names of its contributors | ||
| # may be used to endorse or promote products derived from this software | ||
| # without specific prior written permission. | ||
| # | ||
| # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
| # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE | ||
| # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
| # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
| # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, | ||
| # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
| # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
|
|
||
| """Define functions for patching NumPy with MKL-based NumPy interface.""" | ||
|
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| from contextlib import ContextDecorator | ||
| from threading import Lock, local | ||
|
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| import numpy as np | ||
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| import mkl_random.interfaces.numpy_random as _nrand | ||
|
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|
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| class _GlobalPatch: | ||
| def __init__(self): | ||
| self._lock = Lock() | ||
| self._patch_count = 0 | ||
| self._restore_dict = {} | ||
| # make _patched_functions a tuple (immutable) | ||
| self._patched_functions = tuple(_nrand.__all__) | ||
| self._tls = local() | ||
|
|
||
| def _register_func(self, name, func): | ||
| if name not in self._patched_functions: | ||
| raise ValueError(f"{name} not an mkl_random function.") | ||
| if name not in self._restore_dict: | ||
| self._restore_dict[name] = getattr(np.random, name) | ||
| setattr(np.random, name, func) | ||
|
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| def _restore_func(self, name, verbose=False): | ||
| if name not in self._patched_functions: | ||
| raise ValueError(f"{name} not an mkl_random function.") | ||
| try: | ||
| val = self._restore_dict[name] | ||
| except KeyError: | ||
| if verbose: | ||
| print(f"failed to restore {name}") | ||
| return | ||
| else: | ||
| if verbose: | ||
| print(f"found and restoring {name}...") | ||
| setattr(np.random, name, val) | ||
|
|
||
| def do_patch(self, verbose=False): | ||
| with self._lock: | ||
| local_count = getattr(self._tls, "local_count", 0) | ||
| if self._patch_count == 0: | ||
| if verbose: | ||
| print( | ||
| "Now patching NumPy random submodule with mkl_random " | ||
| "NumPy interface." | ||
| ) | ||
| print( | ||
| "Please direct bug reports to " | ||
| "https://github.com/IntelPython/mkl_random" | ||
| ) | ||
| for f in self._patched_functions: | ||
| self._register_func(f, getattr(_nrand, f)) | ||
| self._patch_count += 1 | ||
| self._tls.local_count = local_count + 1 | ||
|
|
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| def do_restore(self, verbose=False): | ||
| with self._lock: | ||
| local_count = getattr(self._tls, "local_count", 0) | ||
| if local_count <= 0: | ||
| if verbose: | ||
| print( | ||
| "Warning: restore_numpy_random called more times than " | ||
| "patch_numpy_random in this thread." | ||
| ) | ||
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|
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| return | ||
| self._tls.local_count -= 1 | ||
| self._patch_count -= 1 | ||
| if self._patch_count == 0: | ||
| if verbose: | ||
| print("Now restoring original NumPy random submodule.") | ||
| for name in tuple(self._restore_dict): | ||
| self._restore_func(name, verbose=verbose) | ||
| self._restore_dict.clear() | ||
|
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| def is_patched(self): | ||
| with self._lock: | ||
| return self._patch_count > 0 | ||
|
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| _patch = _GlobalPatch() | ||
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| def patch_numpy_random(verbose=False): | ||
| """ | ||
| Patch NumPy's random submodule with mkl_random's numpy_interface. | ||
|
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||
| Parameters | ||
| ---------- | ||
| verbose : bool, optional | ||
| print message when starting the patching process. | ||
|
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| Notes | ||
| ----- | ||
| This function uses reference-counted semantics. Each call increments a | ||
| global patch counter. Restoration requires a matching number of calls | ||
| between `patch_numpy_random` and `restore_numpy_random`. | ||
|
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| In multi-threaded programs, prefer the `mkl_random` context manager. | ||
|
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| """ | ||
| _patch.do_patch(verbose=verbose) | ||
|
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|
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| def restore_numpy_random(verbose=False): | ||
| """ | ||
| Restore NumPy's random submodule to its original implementations. | ||
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|
||
|
|
||
| Parameters | ||
| ---------- | ||
| verbose : bool, optional | ||
| print message when starting restoration process. | ||
|
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||
| Notes | ||
| ----- | ||
| This function uses reference-counted semantics. Each call decrements a | ||
| global patch counter. Restoration requires a matching number of calls | ||
| between `patch_numpy_random` and `restore_numpy_random`. | ||
|
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| In multi-threaded programs, prefer the `mkl_random` context manager. | ||
|
|
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| """ | ||
| _patch.do_restore(verbose=verbose) | ||
|
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| def is_patched(): | ||
| """Return True if NumPy's random sm is currently patched by mkl_random.""" | ||
| return _patch.is_patched() | ||
|
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||
|
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| class mkl_random(ContextDecorator): | ||
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|
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| """ | ||
| Context manager and decorator to temporarily patch NumPy random submodule | ||
| with MKL-based implementations. | ||
|
|
||
| Examples | ||
| -------- | ||
| >>> import mkl_random | ||
| >>> mkl_random.is_patched() | ||
| # False | ||
|
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| >>> with mkl_random.mkl_random(): # Enable mkl_random in NumPy | ||
| >>> print(mkl_random.is_patched()) | ||
| # True | ||
|
|
||
| >>> mkl_random.is_patched() | ||
| # False | ||
|
|
||
| """ | ||
|
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| def __enter__(self): | ||
| patch_numpy_random() | ||
| return self | ||
|
|
||
| def __exit__(self, *exc): | ||
| restore_numpy_random() | ||
| return False | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,105 @@ | ||
| # Copyright (c) 2017, Intel Corporation | ||
| # | ||
| # Redistribution and use in source and binary forms, with or without | ||
| # modification, are permitted provided that the following conditions are met: | ||
| # | ||
| # * Redistributions of source code must retain the above copyright notice, | ||
| # this list of conditions and the following disclaimer. | ||
| # * Redistributions in binary form must reproduce the above copyright | ||
| # notice, this list of conditions and the following disclaimer in the | ||
| # documentation and/or other materials provided with the distribution. | ||
| # * Neither the name of Intel Corporation nor the names of its contributors | ||
| # may be used to endorse or promote products derived from this software | ||
| # without specific prior written permission. | ||
| # | ||
| # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
| # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE | ||
| # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
| # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
| # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, | ||
| # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
| # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
|
|
||
| import numpy as np | ||
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|
||
|
|
||
| import mkl_random | ||
| import mkl_random.interfaces.numpy_random as _nrand | ||
|
|
||
|
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| def test_is_patched(): | ||
| """Test that is_patched() returns correct status.""" | ||
| assert not mkl_random.is_patched() | ||
| try: | ||
| mkl_random.patch_numpy_random() | ||
| assert mkl_random.is_patched() | ||
| mkl_random.restore_numpy_random() | ||
| assert not mkl_random.is_patched() | ||
| finally: | ||
| while mkl_random.is_patched(): | ||
| mkl_random.restore_numpy_random() | ||
|
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|
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| def test_patch(): | ||
| old_module = np.random.normal.__module__ | ||
| assert not mkl_random.is_patched() | ||
|
|
||
| try: | ||
| mkl_random.patch_numpy_random() # Enable mkl_random in NumPy | ||
| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
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| mkl_random.restore_numpy_random() # Disable mkl_random in NumPy | ||
| assert not mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == old_module | ||
| finally: | ||
| while mkl_random.is_patched(): | ||
| mkl_random.restore_numpy_random() | ||
|
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|
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| def test_patch_redundant_patching(): | ||
| old_module = np.random.normal.__module__ | ||
| assert not mkl_random.is_patched() | ||
|
|
||
| try: | ||
| mkl_random.patch_numpy_random() | ||
| mkl_random.patch_numpy_random() | ||
|
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| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
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| mkl_random.restore_numpy_random() | ||
| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
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| mkl_random.restore_numpy_random() | ||
| assert not mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == old_module | ||
| finally: | ||
| while mkl_random.is_patched(): | ||
| mkl_random.restore_numpy_random() | ||
|
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||
|
|
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| def test_patch_reentrant(): | ||
| old_module = np.random.normal.__module__ | ||
| assert not mkl_random.is_patched() | ||
|
|
||
| try: | ||
| with mkl_random.mkl_random(): | ||
| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
|
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| with mkl_random.mkl_random(): | ||
| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
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| assert mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == _nrand.normal.__module__ | ||
|
|
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| assert not mkl_random.is_patched() | ||
| assert np.random.normal.__module__ == old_module | ||
| finally: | ||
| while mkl_random.is_patched(): | ||
| mkl_random.restore_numpy_random() | ||
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