[CI/Build] Fix multimodal tests

[DarkLight1337]

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

Fix failing tests caused by #22441

The reason is that the tests use different model configs (some with cache size set to 0 and others with the normal cache size) which require different caches to be created for each setup.

Test Plan

Test Result

(Optional) Documentation Update

[gemini-code-assist]

Code Review

This pull request aims to fix an issue in multimodal tests where different cache configurations were causing problems. The introduction of a globally cached _get_processor_cache function is a good approach. However, the implementation within MultiModalRegistry._get_processor_cache still incorrectly caches the processor cache at the instance level. This can lead to a stale cache being used when the model configuration changes. I've provided a critical comment with a suggested fix to ensure the correct cache is always retrieved.

[gemini-code-assist]

The current implementation of _get_processor_cache has a flaw. The check if self._processor_cache is None: causes the cache to be created only once and then reused for all subsequent calls, regardless of whether the model_config (and thus the required cache capacity) has changed. This can lead to using a cache with an incorrect size or using a cache when it should be disabled (e.g., when capacity_gb is 0), which can cause difficult-to-debug errors.

The new global _get_processor_cache function is correctly memoized with lru_cache, so it's safe and efficient to call it on every invocation of this method. This ensures the correct cache is used based on the current model_config.

Suggested change

	def _get_processor_cache(self, model_config: "ModelConfig"):
	capacity_gb = model_config.mm_processor_cache_gb
	if capacity_gb is None:
	return None # Overrides `disable_cache` argument
	if self._processor_cache is None:
	self._processor_cache = ProcessingCache(capacity_gb)
	model_id = model_config.model
	capacity_gb = model_config.mm_processor_cache_gb
	self._processor_cache = _get_processor_cache(model_id, capacity_gb)
	capacity_gb = model_config.mm_processor_cache_gb
	self._processor_cache = _get_processor_cache(capacity_gb)
	return self._processor_cache

[github-actions]

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