fix(processing): Filter kwargs in ProcessorMixin call to prevent Type…#41606
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CodersAcademy006 wants to merge 2 commits intohuggingface:mainfrom
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fix(processing): Filter kwargs in ProcessorMixin call to prevent Type…#41606CodersAcademy006 wants to merge 2 commits intohuggingface:mainfrom
CodersAcademy006 wants to merge 2 commits intohuggingface:mainfrom
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cc @zucchini-nlp! I'm not sure about this because some of the submodules may just have |
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| input_data, input_kwargs = attribute_to_kwargs[attribute_name] | ||
| if input_data is not None and attribute is not None: | ||
| attribute_output = attribute(input_data, **kwargs[input_kwargs]) |
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in this line kwargs are filtered already and we are obtaining kwargs[input_kwargs]. That should work for all models if if there's a TypeError anywhere, I'd suggest to see what has gone wrong with specific model
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The model where this issue is occurring is CSM-1B, so it might be related to how that particular architecture handles its input kwargs.
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View the CircleCI Test Summary for this PR: https://huggingface.co/spaces/transformers-community/circle-ci-viz?pr=41606&sha=987d5c |
This was referenced Apr 29, 2026
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This PR fixes an issue where multimodal processors could raise a
TypeErrorwhen called with arguments specific to one modality. TheProcessorMixin.__call__method was passing all keyword arguments to each sub-processor (tokenizer, feature extractor, etc.), causing a crash if a processor received an argument it didn't recognize (e.g.,EncodecFeatureExtractorreceivingpad_to_multiple_offrom the tokenizer).This fix resolves the problem by filtering the keyword arguments before they are passed to each sub-processor. It uses Python's
inspectmodule to get the valid parameters for each processor's__call__method and only passes the arguments that match. This preventsTypeErrors and makes the processor logic more robust.Fixes #41598