asarray supports sequence of arrays from multiple devices #1151
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```
In [1]: import dpctl, dpctl.tensor as dpt
In [2]: m = dpt.zeros((2, 4), dtype="i2", device="cpu")
In [3]: w = dpt.full(4, -1, device="opencl:gpu")
In [4]: res = dpt.asarray([m, [w, [0,] * 4 ]], dtype="f4", device="cpu")
In [5]: res
Out[5]:
usm_ndarray([[[ 0., 0., 0., 0.],
[ 0., 0., 0., 0.]],
[[-1., -1., -1., -1.],
[ 0., 0., 0., 0.]]], dtype=float32)
In [6]: res.device
Out[6]: Device(opencl:cpu:0)
```
This usage requires user to specify sycl_queue or device keyword to
indicate where the result is created, or ExecitionPlacementError is
raised.
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_65 ran successfully. |
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_66 ran successfully. |
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View rendered docs @ https://intelpython.github.io/dpctl/pulls/1151/index.html |
antonwolfy
reviewed
Apr 4, 2023
``` import dpnp, numpy, dpctl, dpctl.tensor as dpt w = dpt.full(4, -1, device="opencl:gpu") res = dpt.asarray([w, range(4)], dtype="f4") # now correctly infers where to allocate output array ``` ``` import dpctl, dpctl.tensor as dpt m = dpt.zeros((2, 4), dtype="i2", device="cpu") w = dpt.full(4, -1, device="opencl:gpu") res = dpt.asarray([m, [w, range(4)], dtype="f4", device="cpu") ```
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_72 ran successfully. |
antonwolfy
approved these changes
Apr 5, 2023
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Deleted rendered PR docs from intelpython.github.com/dpctl, latest should be updated shortly. 🤞 |
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_74 ran successfully. |
oleksandr-pavlyk
deleted the
as-type-supports-sequence-of-arrays-from-multiple-devices
branch
oleksandr-pavlyk
changed the title
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Added support for
asarrayto create arrays from sequences of usm_ndarray objects allocated on different devices, and other Python sequences or numpy arrays.