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[FEA] Support missing operators in cudf.Series (__divmod__
, __rdivmod__
, __round__
).
#10177
Comments
List of other operators I've found are implemented in pandas but not cudf:
|
#10360 handles the reverse binary operators. The three that you listed in your last comment are not yet done. divmod and rdivmod are out of scope for #10360 but are in general trivial to implement in the relevant classes once that PR is merged since they are just
I think they should probably just bypass the new binop machinery, but maybe there will be a benefit to including them.
|
__rxor__
, __divmod__
, __rdivmod
, __round__
).
__rxor__
, __divmod__
, __rdivmod
, __round__
).__rxor__
, __divmod__
, __rdivmod__
, __round__
).
This PR builds on the framework introduced in #9925 to implement scans. I plan to apply this mixin to ColumnBase as well, but that will require more work to clean up binary operations for column types and it is large enough to merit a separate PR. Contributes to #10177. Authors: - Vyas Ramasubramani (https://github.com/vyasr) Approvers: - Michael Wang (https://github.com/isVoid) - Ashwin Srinath (https://github.com/shwina) URL: #10360
This issue has been labeled |
This issue has been labeled |
__rxor__
, __divmod__
, __rdivmod__
, __round__
).__divmod__
, __rdivmod__
, __round__
).
Is your feature request related to a problem? Please describe.
cudf.Series
does not have reverse binary operators for bitwise operators like__rxor__
. This was caught after changing the output ofSeries.hash_values
from acupy.array
to acudf.Series
in #9390, which broke NVTabular: NVIDIA-Merlin/NVTabular#1376 (review). Thecupy.array
class supports both directions, likearray ^ scalar
andscalar ^ array
. Similarly, pandas supports both directions. Currentlycudf.Series
only supportsseries ^ scalar
.Describe the solution you'd like
Add reverse binary operators for all cases that are missing, which include at least bitwise operators like
__rxor__
but possibly others as well. Missing operators have been addressed several times in the past (#208, #213, #1292, #8598, ...). Resolving this issue should involve checking the full list in the Python object model documentation to make sure we catch everything that pandas supports.Additional context
A workaround is to use the binary operator in the reverse order (for commutative operators).
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