fix(core/federated): guard aggregation module lookup against None#566
fix(core/federated): guard aggregation module lookup against None#566g-k-s-03 wants to merge 2 commits into
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This pull request introduces a safety check in the FederatedLearning class initialization to ensure that the required aggregation module is present, raising a ValueError if it is missing. The reviewer suggested extending this validation to also check if the aggregator instance itself is None (i.e., _aggregation[1] is None) to prevent a potential AttributeError later in the execution flow.
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self.module_instances.get() returns None when the aggregation block is missing from the algorithm YAML. Unpacking None immediately crashes with TypeError: cannot unpack non-iterable NoneType object Add a None guard that raises a descriptive ValueError pointing the user to the missing YAML entry before the unpack is attempted. Issue: 565 Signed-off-by: g-k-s-03 <govindsingh97704@gmail.com>
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Signed-off-by: g-k-s-03 <govindsingh97704@gmail.com>
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/assign @hsj576, @Poorunga, @MooreZheng can you review this when you get time |
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Description
FederatedLearning.__init__()unpacks the result ofself.module_instances.get()directly without a None guard. When theuser's algorithm YAML omits the
aggregationblock,.get()returnsNoneand Python crashes with:TypeError: cannot unpack non-iterable NoneType object
This gives no hint about which module is missing or how to fix the YAML.
Fix
Added a None guard that raises a descriptive
ValueErrorpointing theuser to the missing YAML entry before the unpack is attempted.
File Changed
core/testcasecontroller/algorithm/paradigm/federated_learning/federated_learning.pyline 78Testing
The fix is a pure guard — no behavior change on the happy path where
aggregation module is present.
Fixes #565