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FIX Pop unnecessary elements from metric_kwargs in datasets_pair.pyx.tp #26987

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merged 2 commits into from
Aug 2, 2023
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FIX Pop unnecessary elements from metric_kwargs in datasets_pair.pyx.tp #26987

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6051b58
Moved bugfix
Micky774 Aug 1, 2023
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Micky774 Aug 2, 2023
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15 changes: 11 additions & 4 deletions sklearn/metrics/_pairwise_distances_reduction/_datasets_pair.pyx.tp
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Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
import copy

{{py:

implementation_specific_values = [
Expand Down Expand Up @@ -84,12 +86,17 @@ cdef class DatasetsPair{{name_suffix}}:
datasets_pair: DatasetsPair{{name_suffix}}
The suited DatasetsPair{{name_suffix}} implementation.
"""
# Y_norm_squared might be propagated down to DatasetsPairs
# via metrics_kwargs when the Euclidean specialisations
# can't be used. To prevent Y_norm_squared to be passed
# X_norm_squared and Y_norm_squared might be propagated
# down to DatasetsPairs via metrics_kwargs when the Euclidean
# specialisations can't be used.
# To prevent X_norm_squared and Y_norm_squared to be passed
# down to DistanceMetrics (whose constructors would raise
# a RuntimeError), we pop it here.
# a RuntimeError), we pop them here.
if metric_kwargs is not None:
# Copying metric_kwargs not to pop "X_norm_squared"
# and "Y_norm_squared" where they are used
metric_kwargs = copy.copy(metric_kwargs)
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quick question: does metric_kwargs can have nested objects such that calling deepcopy instead of copy could be better?

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Here, we do not want to copy the objects themselves, (which is what deepcopy does), and only want to copy their reference in another dictionary (which is what copy does).

What do you think? Is this right?

Probably we could include a comment to explain the function that is used.

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OK right, metric_kwargs will only be used "read-only", that makes sense.

metric_kwargs.pop("X_norm_squared", None)
metric_kwargs.pop("Y_norm_squared", None)
cdef:
{{DistanceMetric}} distance_metric = DistanceMetric.get_metric(
Expand Down