Use Gradient Checkpointing Layer in Jamba & Blip Related Models #38310
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ArthurZucker
approved these changes
May 23, 2025
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| if getattr(self.config, "gradient_checkpointing", False) and self.training and use_cache: | ||
| logger.warning( | ||
| "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..." |
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Nice, I think the gradient checkpoint layer does should get use_cache as input and fallback to not do GC ! 🤗
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Awesome, thanks for merging this @ArthurZucker! I agree, I'll open a follow-up PR to take use_cache in the gcp layer and move the warning into it 😄
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Updates a few models to use the new
GradientCheckpointingLayer. The models changed in this PR are leveraged by IBM model architectures (granite vision / bamba) or share code, either directly or through modular. Happy to submit a follow-up with other models too if that would be helpful!Updated models:
@ArthurZucker