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* Array parameters for these distributions must broadcast to the requested `size` without adding dimensions; previously accepted mismatches now raise `ValueError`[gh-171](https://github.com/IntelPython/mkl_random/pull/171)
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*`uniform` with array-valued bounds may return `high` due to floating-point rounding [gh-171](https://github.com/IntelPython/mkl_random/pull/171)
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* Pinned Cython in the Coverity Scan workflow so generated code stays stable between scans, and added `coverity/README.md` documenting the known Cython-boilerplate false positives and the scan review checklist [gh-164](https://github.com/IntelPython/mkl_random/pull/164)
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* Sped up `randint` for power-of-two ranges at or above `INT_MAX`[gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* The random streams for power-of-two `randint` ranges at or above `INT_MAX` have changed: with a fixed seed these now produce different (but equally valid) samples. All other streams are unaffected. [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* Sped up `randint` for `bool`, `uint8`, `int8`, `uint16` and `int16`; generated values are unchanged [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* Raised the minimum build-time `Cython` requirement to `3.1.0`, the first release providing the `freethreading_compatible` directive [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
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* Extended the `memcpy`-based fast path of `shuffle` to multi-dimensional `ndarray` inputs whose first-axis items are contiguous, which is also much faster than the previous buffered path [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
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### Fixed
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* Fixed `uniform` to return a Python `float` for scalar bounds with `size=None` instead of a 0-d array [gh-167](https://github.com/IntelPython/mkl_random/pull/167)
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* Fixed `randint` returning `high` for `int64`, `uint64` and the default `int` dtype when the range is at or above `INT_MAX`[gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* Fixed the integer fills silently under-filling requests larger than two `MKL_INT_MAX` chunks [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* Fixed `multinomial` under-filling large outputs by decrementing its chunk counter by elements instead of draws [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
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* Fixed a memory leak in `set_state`, which leaked the previous MKL stream on every call [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
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* Fixed a memory leak in `logseries`, which leaked a temporary buffer on every call [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
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