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[REVIEW] Optimize pg.get_x_data APIs #3086
[REVIEW] Optimize pg.get_x_data APIs #3086
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assert ( | ||
df["_VERTEX_"] == df["_VERTEX_"]._constructor(range(start, stop + 1)) | ||
).all() |
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These changes are similar to https://github.com/rapidsai/cugraph/pull/3036/files#r1048542911 .
Unsure how CI passed without them
expected = cur._constructor(sorted(x for x, *args in data[key][1])) | ||
assert (cur.values == expected.values).all() |
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These changes are similar to https://github.com/rapidsai/cugraph/pull/3036/files#r1048542911 .
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I made similar changes in my PR. We have to be more careful running MG tests until they are included in CI.
actual = df[pG.edge_id_col_name] | ||
expected = actual._constructor(range(start, stop + 1)) | ||
assert (actual == expected).all() |
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These changes are similar to https://github.com/rapidsai/cugraph/pull/3036/files#r1048542911 .
Codecov ReportBase: 58.50% // Head: 57.17% // Decreases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## branch-23.02 #3086 +/- ##
================================================
- Coverage 58.50% 57.17% -1.34%
================================================
Files 133 148 +15
Lines 7895 9295 +1400
================================================
+ Hits 4619 5314 +695
- Misses 3276 3981 +705
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report at Codecov. |
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LGTM, but I did have one suggestion.
@VibhuJawa could you clarify - is cudf.Series the preferred datatype to pass in here? So cupy arrays are discouraged? |
Nope, You can use anything you want after this PR . Before this PR cupy arrays on SG bonked on SG and MG . I think even cudf.series was a problem for MG previously but i might be wrong |
rerun tests Reason:
|
@rlratzel / @alexbarghi-nv , Can we merge this in now ? I think all changes have been addressed and CI passes. |
I've approved, but don't have merge privileges. |
@gpucibot merge |
This PR closes #3026 .
The speed up on cupy arrays is
83x
.