Api cleanup #648
Api cleanup #648
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I went ahead and cleaned up the function signatures related to both LoRA and 3D models. |
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Also, I created a new submodule |
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| def get_3d_sam_model( | ||
| def get_sam_3d_model( |
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I changed these names to match the order of sam_3d we use everywhere else, cc @lufre1
| # unclear how batches are handled | ||
| def forward(self, batched_input, multimask_output, image_size) -> torch.Tensor: | ||
| return self._forward_train(batched_input, multimask_output, image_size) | ||
| def forward( |
| use_lora: bool = False, | ||
| rank: Optional[int] = None, | ||
| lora_rank: Optional[int] = None, | ||
| lora_kwargs: Optional[Dict] = None, |
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I removed the use_lora, since it is redundant with rank = None and renamed rank -> lora_rank to have a more explicit name.
I added lora_kwargs, so that we can also customize the PEFT SAM layers from here.
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Thanks @constantinpape for the refactoring. This is GTG from my side.
Let's merge this once you think this is ready.
(PS. I was thinking if TrainableSAM is adapted with PEFT_Sam now as the test case seems to me that it is build in two stages: get_sam_model + PEFT_Sam, where it could be done in one-stage with lora_rank, but that's really minor and I can also take care of it later once we look at the LoRA experiments)
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Thanks for checking everyone, I will go ahead and merge! |
Clean up interfaces related to 3d models and PEFT
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