Allow Python scalars as the search values in dpt.searchsorted
#2225
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View rendered docs @ https://intelpython.github.io/dpctl/pulls/2225/index.html |
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_104 ran successfully. |
ndgrigorian
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_104 ran successfully. |
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_105 ran successfully. |
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_106 ran successfully. |
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_106 ran successfully. |
ndgrigorian
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vlad-perevezentsev
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| if not isinstance(x2, usm_ndarray): | ||
| x2 = dpt.asarray(x2, dtype=dt2, usm_type=res_usm_type, sycl_queue=q) | ||
| if x2.dtype != dt: |
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| if x2.dtype != dt: | |
| elif x2.dtype != dt: |
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this is not meant to be an elif. x2 is taken to dt2 first if not usm_ndarray then is cast to dt which is the resolved dtype. This way, it passes through dt2 under all circumstances.
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Then it's unclear for me, why do we need to run 2 kernels in that case?
- to convert a scalar to a temporary usm_ndarray and to copy back to the result
- to cast the array to
dt
What is a drawback to pass dt directly to asarray call?
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Also, in the sequence:
- cast
x1todt - cast
x2to usm_ndarray if any - cast
x2todt
We have to make step 2 as the 1st or as the last in the sequence, but not in the middle, because currently step 2 depends on events from step 1, but shouldn't.
And from other side, step 2 produces depending events which we must pass to step 3, but we didn't (asarray must be completed before we can start casting x2 to dt).
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Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_110 ran successfully. |
| "shape as the first argument array" | ||
| ) | ||
| res = empty(x1.shape, dtype=x1_dt, usm_type=x1.usm_type, sycl_queue=q) | ||
| res = empty(x1.shape, dtype=x1_dt, usm_type=x1_usm_type, sycl_queue=q) |
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Isn't that exactly the same as below?
| res = empty(x1.shape, dtype=x1_dt, usm_type=x1_usm_type, sycl_queue=q) | |
| res = empty_like(x1) |
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| if not isinstance(x2, usm_ndarray): | ||
| x2 = dpt.asarray(x2, dtype=dt2, usm_type=res_usm_type, sycl_queue=q) | ||
| if x2.dtype != dt: |
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Then it's unclear for me, why do we need to run 2 kernels in that case?
- to convert a scalar to a temporary usm_ndarray and to copy back to the result
- to cast the array to
dt
What is a drawback to pass dt directly to asarray call?
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| if not isinstance(x2, usm_ndarray): | ||
| x2 = dpt.asarray(x2, dtype=dt2, usm_type=res_usm_type, sycl_queue=q) | ||
| if x2.dtype != dt: |
There was a problem hiding this comment.
Also, in the sequence:
- cast
x1todt - cast
x2to usm_ndarray if any - cast
x2todt
We have to make step 2 as the 1st or as the last in the sequence, but not in the middle, because currently step 2 depends on events from step 1, but shouldn't.
And from other side, step 2 produces depending events which we must pass to step 3, but we didn't (asarray must be completed before we can start casting x2 to dt).
3 participants
This PR proposes permitting the search values of
dpt.searchsortedto be Python scalars, a change coming to the 2026 array API specResolves #2224