[Bugfix] Fix missing return value in load_weights method of adapters.py

[noc-turne]

Previously, the load_weights method in adapters.py did not return the weights, which caused loaded_params to be None in some cases — for example, when using the Qwen2ForEmbedding model (see vllm/models/utils.py#L171-L177).

This PR fixes the issue by properly returning the result of load_weights, and ensures that the prefix matches the expected format for external usage.

[github-actions]

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[DarkLight1337]

This is intentional - if we return the loaded weights, there may be some mismatch compared to the expected weights (leading to an error) because we removed some unused modules in the adapter class .

[noc-turne]

But now when deploying a multimodal model—in my case, InternVLChatModel—the adaptor's load_weights function not returning a value causes the language model's parameters to fail to load(Qwen2ForEmbedding), which in turn leads to deployment failure.

[DarkLight1337]

Hmm, to work in all cases I think we may need to keep the unnecessary modules then. Can you remove the code where lm_head etc. is being removed? Then it should be ok then return the weights.

[noc-turne]

No, it doesnt' work. If removing the code about lm_head, it will be reported the error as

File "/vllm/vllm/model_executor/models/adapters.py", line 105, in load_weights
ERROR 03-27 07:43:20 [engine.py:448]     self.model.load_weights(weights)
ERROR 03-27 07:43:20 [engine.py:448]   File "vllm/vllm/model_executor/models/qwen2.py", line 400, in load_weights
ERROR 03-27 07:43:20 [engine.py:448]     param = params_dict[name]
ERROR 03-27 07:43:20 [engine.py:448] KeyError: 'lm_head.weight'

And the original code(not returning the weights) will throw an error:

File "vllm/vllm/model_executor/model_loader/loader.py", line 448, in load_model
    raise ValueError(
ValueError: Following weights were not initialized from checkpoint: {
    'language_model.model.layers.16.mlp.down_proj.weight',
    'language_model.model.layers.22.input_layernorm.weight',
    'language_model.model.layers.27.mlp.down_proj.weight',
    'language_model.model.layers.8.input_layernorm.weight',
    'language_model.model.layers.18.mlp.gate_up_proj.weight',
    ...
}

However, when returning its weight and adapting its prefix, Qwen2ForEmbedding can be deployed normally.

[DarkLight1337]

Let me unblock some tests and see if the existing embedding models can still be loaded under your PR.

[DarkLight1337]

It looks like other tests are failing in this CI run. Can you try to run tests/models/embedding/language locally and report the results?

[noc-turne]

It’s too hard for me to download so many models locally to run this test. If others haven’t encountered a similar issue, then just forget it for now and close the PR.

[DarkLight1337]

I'll run this in the background then and report back the results

[noc-turne]

Thanks!

[DarkLight1337]

Ok it seems the embedding models can indeed be loaded, perhaps you somehow patched the problem from before as well. In that case, thanks!