Add add_weighted_adapter to IA3 adapters #1701

alexrs · 2024-05-01T14:12:23Z

(Partially) Resolves: #1688
See #980 for context.

What

$(IA)^3$ adapters can't be combined. This option, however, is available for other PEFT adapters such as LoRA.

Solution

Implement add_weighted_adapter method for $(IA)^3$ models supporting only weighted average of adapters for now.

BenjaminBossan · 2024-05-02T09:32:13Z

@alexrs Thanks a lot for reviving the feature and updating it so quickly. LMK when you think it's ready for review.

@Abdullah-kwl If you could give this a try, that would be great.

src/peft/tuners/ia3/model.py

alexrs · 2024-05-02T13:27:48Z

src/peft/tuners/ia3/model.py

        if peft_config.target_modules is None:
            if model_config["model_type"] not in TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING:
                raise ValueError("Please specify `target_modules` in `peft_config`")
-            peft_config.target_modules = TRANSFORMERS_MODELS_TO_IA3_TARGET_MODULES_MAPPING[model_config["model_type"]]
+            peft_config.target_modules = set(


As discussed in #980 (comment), this seemed to be a bug.

alexrs · 2024-05-02T13:29:21Z

src/peft/tuners/lora/model.py

-        for adapter in adapters:
-            if adapter not in list(self.peft_config.keys()):
-                raise ValueError(f"Adapter {adapter} does not exist")


This is done in _check_add_weighted_adapter

peft/src/peft/tuners/lora/model.py

Lines 462 to 464 in 77b7238

for adapter in adapters:

if adapter not in list(self.peft_config.keys()):

raise ValueError(f"Adapter {adapter} does not exist")

, which is called right after

alexrs · 2024-05-02T13:33:18Z

src/peft/tuners/ia3/model.py

+                else:
+                    continue
+
+                target_ia3_l.data = target_ia3_l.data * 0.0


I guess here we could use:

Suggested change

target_ia3_l.data = target_ia3_l.data * 0.0

target_ia3_l.data = target_ia3_l.data.zero_()

but I tried to follow the code style used in LoRA:

peft/src/peft/tuners/lora/model.py

Line 612 in 77b7238

target_lora_A.data = target_lora_A.data * 0.0

https://pytorch.org/docs/stable/generated/torch.Tensor.zero_.html#torch-tensor-zero

Probably .zero_() is more efficient (or has the potential to be so), so I'd be fine with this change.

alexrs · 2024-05-02T13:34:01Z

@BenjaminBossan Ready for review! 👀

BenjaminBossan

Thanks a lot for your work. This already looks quite good. I have a few smaller comments, and then 3 more general points:

I haven't reviewed the tests yet. I see that you refactored _test_weighted_combination_of_adapters to work with both LoRA and IA³. However, all the changes make the review quite hard and there is also the risk to accidentally break the LoRA tests (e.g. skipping to test something that is currently tested). Instead, it would be better IMO if _test_weighted_combination_of_adapters would call a submethod _test_weighted_combination_of_adapters_lora, _test_weighted_combination_of_adapters_ia3, etc., with _test_weighted_combination_of_adapters being the current function body. Then you can copy and modify it for IA³. Yes, this will result in more code duplication, but for tests that doesn't matter as much and it will be more maintainable, especially since the different methods will always be quite different and thus tests will differ.
IIUC, right now, if I merge, say, 10 adapters, all with weight=1, the resulting merged adapter will possibly have very large values, right? So I should probably assign weight=1/10 so that the norm does not shift. Maybe this should be documented.
How about adding a section to https://github.com/huggingface/peft/blob/main/docs/source/developer_guides/model_merging.md?

src/peft/tuners/ia3/model.py

BenjaminBossan · 2024-05-03T13:06:04Z

src/peft/tuners/ia3/model.py

+        if str in target_module_types:
+            new_target_modules = "|".join(f"({self.peft_config[adapter].target_modules})" for adapter in adapters)
+        else:
+            new_target_modules = set.union(*(self.peft_config[adapter].target_modules for adapter in adapters))


Oh yeah, simpler than the reduce op we have in LoRA 👍

BenjaminBossan · 2024-05-03T13:07:50Z

src/peft/tuners/ia3/model.py

+                else:
+                    continue
+
+                target_ia3_l.data = target_ia3_l.data * 0.0


Probably .zero_() is more efficient (or has the potential to be so), so I'd be fine with this change.

alexrs · 2024-05-07T09:16:22Z

Hey @BenjaminBossan. I made some changes:

Re-factored the tests to include _test_weighted_combination_of_adapters_lora and _test_weighted_combination_of_adapters_ia3. These methods are called from _test_weighted_combination_of_adapters.
Added a short section to the docs. Let me know if I should expand it.

With respect to whether we should normalize the adapter weights or not, I'm not sure what is the best approach. On the one hand, I agree that having a combination of adapters with the sum of weights > 1 might not return the best results. On the other hand, I also think it is interesting for users to specify how they want their adapter weights to be normalized. In your example, weight=1/10 is a totally valid approach, but also is taking a softmax of the weights or passing some weights as 0 if we want to do some sort of Top K combination. I'm not sure this method should be in charge of handling all of that.

Maybe we should just specify in the docs that we recommend sum(weights) == 1? We can also print a warning if that condition is not fulfilled.

HuggingFaceDocBuilderDev · 2024-05-07T10:38:31Z

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

BenjaminBossan

Thanks for the updates, I think we're almost good, I only had a few minor points.

Maybe we should just specify in the docs that we recommend sum(weights) == 1?

Yes, my suggestion is to document that users should take care that the weights should sum up to 1 or at least be close to 1.

docs/source/developer_guides/model_merging.md

BenjaminBossan · 2024-05-07T10:46:34Z

tests/testing_common.py

+            **config_kwargs,
+        )
+
+        # Define a dictionary to map config types to their respective test functions


I think it's more straightforward to read (though less elegant) if we do:

if isinstance(config, LoraConfig): self._test_weighted_combination_of_adapters_lora(...) elif ...

WDYT?

I initially did that, but if we want to call model = get_peft_model(model, config, adapter_list[0]) only for LoraConfig and IA3Config, we'd need to:

# check if config is LoraConfig or IA3Config. Skip if not. if not isinstance(config, (LoraConfig, IA3Config)): pytest.skip(f"Test not applicable for {config}") # Initialize model ... # Call test method according to config type if isinstance(config, LoraConfig): self._test_weighted_combination_of_adapters_lora(...) elif isinstance(config, IA3Config): self._test_weighted_combination_of_adapters_ia3(...) else: pytest.skip(f"Test not applicable for {config}")

and it seems a bit redundant.

All in all, I don't have a strong opinion here. Let me know if you think this is more readable and I'll change it!

I see what you mean but honestly, for a test I don't care so much about such issues, it's more important to me that I can quickly read from top to bottom and understand what's going on.

tests/testing_common.py

Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

BenjaminBossan

Thanks a lot Alejandro, LGTM, good to have this feature finally.

@pacman100 do you also want to review?

pacman100

Thank you, @alexrs, for adding support for combining adapters when usiung IA3! ✨

alexrs added 2 commits May 1, 2024 16:11

Add add_weighted_adapter to IA3 adapters

36d7f28

Refactor to simplify code

0a209e8

alexrs force-pushed the ars-ia3-merge-adapter branch from 3dd8e12 to 0a209e8 Compare May 1, 2024 14:26

alexrs mentioned this pull request May 2, 2024

Add Support for IA3 Adapters in add_weighted_adapter Method, Currently facing issue that 'IA3Model' object has no attribute 'add_weighted_adapter' #1688

Closed

alexrs commented May 2, 2024

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src/peft/tuners/ia3/model.py Show resolved Hide resolved

alexrs commented May 2, 2024

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alexrs marked this pull request as ready for review May 2, 2024 13:33

BenjaminBossan requested changes May 3, 2024

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alexrs added 2 commits May 7, 2024 10:52

refactor test

1c3e4b7

Add IA3 merging docs

5d7f313

BenjaminBossan requested changes May 7, 2024

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alexrs and others added 3 commits May 7, 2024 14:14

Update docs/source/developer_guides/model_merging.md

1b442d4

Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

Update docs/source/developer_guides/model_merging.md

faa30e7

Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

address PR feedback

e4bc355

alexrs force-pushed the ars-ia3-merge-adapter branch from 71c941f to e4bc355 Compare May 7, 2024 13:38

alexrs requested a review from BenjaminBossan May 7, 2024 13:47

BenjaminBossan approved these changes May 7, 2024

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pacman100 approved these changes May 17, 2024

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pacman100 merged commit fb7f279 into huggingface:main May 17, 2024
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Add add_weighted_adapter to IA3 adapters #1701

Add add_weighted_adapter to IA3 adapters #1701

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	for adapter in adapters:
	if adapter not in list(self.peft_config.keys()):
	raise ValueError(f"Adapter {adapter} does not exist")

	target_ia3_l.data = target_ia3_l.data * 0.0
	target_ia3_l.data = target_ia3_l.data.zero_()

Add add_weighted_adapter to IA3 adapters #1701

Add add_weighted_adapter to IA3 adapters #1701

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alexrs commented May 1, 2024 • edited Loading

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alexrs commented May 1, 2024 •

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