Optimize rope_deltas propagation logic in Qwen2.5-VL #41176
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…econd_per_grid_ts
- Forward rope_deltas from Qwen2_5_VLForConditionalGeneration to Qwen2_5_VLModel - Update Qwen2_5_VLModel to accept rope_deltas and store internally - Refactor prepare_inputs_for_generation to unify rope_deltas handling - Ensure that passing rope_deltas in forward() now correctly affects position_ids calculation This fixes an issue where passing rope_deltas directly to the model's forward() had no effect, which could lead to inconsistencies between pre-fill generation and manual forward calls.
Xqle
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cc @zucchini-nlp for VLMs, @ArthurZucker for rope |
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[For maintainers] Suggested jobs to run (before merge) run-slow: qwen2_5_vl |
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What does this PR do?
This PR fixes the propagation of
rope_deltasin the Qwen2.5-VL model during generation.Currently, the
forward()method ofQwen2_5_VLForConditionalGenerationacceptsrope_deltasas an argument, but the value is never passed to the underlyingQwen2_5_VLModel. As a result, users providingrope_deltasdirectly toforward()would see no effect.Modifications
Qwen2_5_VLForConditionalGeneration.forward()now passesrope_deltastoQwen2_5_VLModel.forward().Qwen2_5_VLModel.forward()now acceptsrope_deltasand updates its internal state accordingly.prepare_inputs_for_generation()to store calculated rope_deltasin model_inputs, aligning its handling with position_ids.
Impact
rope_deltasduring generation and have them correctly applied.Before submitting
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