Make 'partitioning' differentiable/vectorized#70
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SCiarella
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SCiarella
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SarahAlidoost
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Jan 13, 2026
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SarahAlidoost
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@SCiarella thanks for the implementation 👍 . It looks good. Just minor suggestions for docstring.
Regarding your comments on _check_partitioning, I found out the warning is triggered only in the class TestDiffPartitioningGradients and not TestPartitioning. The reason might be the random test values for different parameters. To me this is fine.
Also, another thing to check later is that if the parameters of the Partitioning can be optimized in general (to be discussed in the update meeting?!). If so, we can add a notebook to show the optimization, similar to other modules.
Co-authored-by: SarahAlidoost <55081872+SarahAlidoost@users.noreply.github.com>
Co-authored-by: SarahAlidoost <55081872+SarahAlidoost@users.noreply.github.com>
Co-authored-by: SarahAlidoost <55081872+SarahAlidoost@users.noreply.github.com>
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Target issue #41.
In implementing the partitioning module, I have realized that the x-values of
Afgentables are actually not fully differentiable (seetest_x_breakpoint_at_clampintest_utils.py). I belive that in a real scenario, the user will be interested in optimizing the y-values but not the x-values, so I am just ignoring them intest_partitioning.More than once during the tests the
_check_partitioningwarning gets triggered, suggesting that the sum of the partitions is not 1. To me this behavior looks suspicious, however the tests produce the expected results.