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Currently dpctl creates usm_ndarray with default dtype="|f8" which cause an issue on gpu device without double type support.
usm_ndarray
dtype="|f8"
The below example code cause an exception for Iris XE:
> import dpctl.tensor as dpt > dpt.usm_ndarray((10,)) ValueError Traceback (most recent call last) Cell In[3], line 1 ----> 1 dpt.usm_ndarray((10,)) File dpctl/tensor/_usmarray.pyx:264, in dpctl.tensor._usmarray.usm_ndarray.__cinit__() ValueError: Device Intel(R) Graphics [0x9a49] does not support |f8 natively.
The text was updated successfully, but these errors were encountered:
Completion of fix for gh-1058
ff3c680
This changes builds up on gh-1265 and takes into account queue from the pre-allocated buffer, if provided.
This has been fixed:
In [1]: import dpctl, dpctl.tensor as dpt In [2]: dpt.usm_ndarray((10,)) Out[2]: usm_ndarray([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32) In [3]: import dpctl.memory as dpm In [4]: dpt.usm_ndarray((10,), buffer=dpm.MemoryUSMShared(80)) Out[4]: usm_ndarray([nan, nan, 0., 0., 0., 0., 0., 0., nan, nan], dtype=float32)
Sorry, something went wrong.
Please retest and close.
I can confirm the issue is resolved:
import dpctl, dpctl.tensor as dpt dpt.usm_ndarray((10,)) # Out: usm_ndarray([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32) dpctl.__version__ # Out: '0.17.0dev0+232.gd8b9cceed7'
oleksandr-pavlyk
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Currently dpctl creates
usm_ndarray
with defaultdtype="|f8"
which cause an issue on gpu device without double type support.The below example code cause an exception for Iris XE:
The text was updated successfully, but these errors were encountered: