[Model] Move vision_feature_select_strategy into resolve_visual_encoder_outputs

[DarkLight1337]

Purpose

Clean up some duplicate code across models that use common vision encoders. This also avoids applying layernorm on the features that are not selected.

Also, clean up the signature of resolve_visual_encoder_outputs.

Test Plan

Unblock all multimodal tests

Test Result

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[gemini-code-assist]

Code Review

This pull request is a nice refactoring that centralizes the vision_feature_select_strategy logic into the resolve_visual_encoder_outputs utility function. This successfully removes duplicated code across several vision models, improving maintainability. The changes are consistent and well-applied across all relevant files.

However, I've found a critical issue in the resolve_visual_encoder_outputs function in vllm/model_executor/models/vision.py. The logic for applying post_layer_norm will cause a runtime error, and the condition to check if the last layer is being used is also incorrect. I've provided a detailed comment with a suggested fix for this.

[gemini-code-assist]

There appear to be two issues in this block of code:

1. The condition to check if the last layer is being used seems incorrect. uses_last_layer is checked against len(hs_pool) - 1, which is len(select_layers) - 1. This doesn't seem to correctly identify if the last layer of the encoder is being used. It should probably check against max_possible_layers, for example: select_layers[-1] in (max_possible_layers - 1, -1).

2. post_layer_norm is being called with encoder_outputs, which is a list of tensors when select_layers is provided. This will cause a runtime error. It should be called with the last hidden state tensor, which is encoder_outputs[-1].

Here is a suggested fix for both issues:

Suggested change

	uses_last_layer = select_layers[-1] in (len(hs_pool) - 1, -1)
	if post_layer_norm is not None and uses_last_layer:
	hs_pool[-1] = post_layer_norm(encoder_outputs)
	uses_last_layer = select_layers[-1] in (max_possible_layers - 1, -1)
	if post_layer_norm is not None and uses_last_layer:
	hs_pool[-1] = post_layer_norm(encoder_outputs[-1])

[DarkLight1337]

These suggestions look reasonable, so I have applied them. cc @alex-jw-brooks

[Isotr0py]

LGTM