[VLM] Minor space optimization for ClipVisionModel

[ywang96]

Previously we initialize the full ClipVisionModel and forward passes up to the required feature layer. This PR avoids loading the unused layers and initializes the model up to the required feature layer to save space on the GPU. This change makes the forward signature cleaner too.

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[github-actions]

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[ywang96]

Tests have passed locally - @DarkLight1337 Please take a look when you get a chance, thanks

[DarkLight1337]

To avoid mutating the config object, let's move the logic of setting number of layers back inside CLIPVisionModel.__init__.

[ywang96]

To avoid mutating the config object, let's move the logic of setting number of layers back inside CLIPVisionModel.__init__.

I'm actually a bit skeptical about that for two reasons:

1. The setting for the vision feature layer is often directly under model config (e.g., LlavaConfig) instead of CLIPVisionConfig - moving it inside CLIPVisionModel means we need to pass info in addition to CLIPVisionConfig when initializing.
2. Another reason for this PR is to also make the CLIPVisionModel completely separate from the main VLM's logics, so it's easier for us to swap between vLLM implementation and transformers for future debugging.

[DarkLight1337]

We can add an extra override_num_hidden_layers argument to CLIPVisionModel.__init__ that is used in place of vision_config.num_hidden_layers if passed. This lets us keep the code for determining whether/how to override this inside the main VLM file.

[ywang96]

@DarkLight1337 I modified the code to move the logic into CLIPVisionModel.__init__

[DarkLight1337]

It seems that the config object is still being mutated inside CLIPVisionModel. Can we forward the override_num_hidden_layers argument all the way to CLIPEncoder so we don't have to touch the existing config?

[ywang96]

Ah I see what you meant - yea let me do that.

[DarkLight1337]

Thanks for taking my comments into account!