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Merge branch 'maintenance/0.16.x' into backport-gh-2071
2 parents afa239e + dd2ff5d commit a902099

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CHANGELOG.md

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@@ -115,8 +115,8 @@ In addition, this release completes implementation of `dpnp.fft` module and adds
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* Resolved an issue with input array of `usm_ndarray` passed into `dpnp.ix_` [#2047](https://github.com/IntelPython/dpnp/pull/2047)
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* Added a workaround to prevent crash in tests on Windows in internal CI/CD (when running on either Lunar Lake or Arrow Lake) [#2062](https://github.com/IntelPython/dpnp/pull/2062)
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* Fixed a crash in `dpnp.choose` caused by missing control of releasing temporary allocated device memory [#2063](https://github.com/IntelPython/dpnp/pull/2063)
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* Resolve compilation warning and error while building in debug mode [#2066](https://github.com/IntelPython/dpnp/pull/2066)
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* Resolved compilation warning and error while building in debug mode [#2066](https://github.com/IntelPython/dpnp/pull/2066)
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* Fixed an issue with asynchronous execution in `dpnp.fft` module [#2067](https://github.com/IntelPython/dpnp/pull/2067)
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## [0.15.0] - 05/25/2024
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dpnp/fft/dpnp_utils_fft.py

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@@ -264,6 +264,8 @@ def _copy_array(x, complex_input):
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dtype = x.dtype
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if numpy.min(x.strides) < 0:
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# negative stride is not allowed in OneMKL FFT
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# TODO: support for negative strides will be added in the future
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# versions of OneMKL, see discussion in MKLD-17597
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copy_flag = True
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elif complex_input and not dpnp.issubdtype(dtype, dpnp.complexfloating):
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# c2c/c2r FFT, if input is not complex, convert to complex
@@ -443,8 +445,6 @@ def _truncate_or_pad(a, shape, axes):
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else:
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# zero-padding
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exec_q = a.sycl_queue
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_manager = dpu.SequentialOrderManager[exec_q]
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dep_evs = _manager.submitted_events
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index[axis] = slice(0, a_shape[axis]) # orig shape
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a_shape[axis] = s # modified shape
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order = "F" if a.flags.fnc else "C"
@@ -455,6 +455,8 @@ def _truncate_or_pad(a, shape, axes):
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usm_type=a.usm_type,
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sycl_queue=exec_q,
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)
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_manager = dpu.SequentialOrderManager[exec_q]
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dep_evs = _manager.submitted_events
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ht_copy_ev, copy_ev = ti._copy_usm_ndarray_into_usm_ndarray(
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src=dpnp.get_usm_ndarray(a),
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dst=z.get_array()[tuple(index)],

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