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@@ -47,6 +47,8 @@ This release is compatible with NumPy 2.5.
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* Linked the `dpnp_backend_c` library against only the MKL SYCL domains it uses (`BLAS`, `RNG`, `VM`) [#3012](https://github.com/IntelPython/dpnp/pull/3012)
* Reworked the ASV benchmarks and added end-to-end workload benchmarks derived from dpBench [#2996](https://github.com/IntelPython/dpnp/pull/2996)
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* Reduced allocations in `dpnp.linalg.norm` by reusing the reduction result as the `sqrt` output buffer in the 2-norm and Frobenius-norm branches [#3062](https://github.com/IntelPython/dpnp/pull/3062)
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* Avoided a copy of `dpnp.einsum` result into C-order by building the product in the requested layout directly [#3069](https://github.com/IntelPython/dpnp/pull/3069)
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### Deprecated
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@@ -95,6 +97,9 @@ This release is compatible with NumPy 2.5.
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* Fixed `dpnp.insert` silently ignoring out-of-bounds negative indices in a multi-element `obj`, so a mix of in-bounds and out-of-bounds indices now consistently raises `IndexError`[#3041](https://github.com/IntelPython/dpnp/pull/3041)
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* Fixed a per-call `sycl::queue` leak in `usm_ndarray::get_queue()`/`get_device()`[#3042](https://github.com/IntelPython/dpnp/pull/3042)
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* Fixed `dpnp.linspace` returning `nan` for equal infinite endpoints [#3043](https://github.com/IntelPython/dpnp/pull/3043)
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* Fixed `dpnp.cumsum`, `dpnp.cumprod`, and their `nan`/`cumulative_*` variants (including `dpnp.tensor.cumulative_sum`/`cumulative_prod`) silently returning incorrect results when accumulating along an axis of an array with more than one row [#3063](https://github.com/IntelPython/dpnp/pull/3063)
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* Fixed `dpnp.einsum` returning a result whose memory layout differs from NumPy for the default `order="K"`, and ignoring `out` and `order` for a contraction over a size-0 dimension [#3058](https://github.com/IntelPython/dpnp/pull/3058)
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* Fixed operations on a boolean array whose bytes are not `0x00`/`0x01`[#3055](https://github.com/IntelPython/dpnp/pull/3055)
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