[vllm] support vllm_mm_processor_cache_gb

[hjh0119]

support vllm_mm_processor_cache_gb to set mm processor cache size

[gemini-code-assist]

Summary of Changes

Hello @hjh0119, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the vLLM integration by introducing a new configuration option, vllm_mm_processor_cache_gb. This parameter provides users with explicit control over the cache size allocated for multi-modal processors within vLLM, offering greater flexibility and optimization capabilities for multi-modal inference tasks.

Highlights

• New Configuration Parameter: Introduced a new configuration parameter, vllm_mm_processor_cache_gb, allowing users to specify the multi-modal processor cache size for vLLM in gigabytes.
• VLLM Engine Integration: The mm_processor_cache_gb parameter is now accepted and correctly propagated through the GrpoVllmEngine and VllmEngine classes to the underlying vLLM engine initialization.
• Argument Parsing Update: The VllmArguments class has been updated to include vllm_mm_processor_cache_gb, enabling this new setting to be configured via command-line arguments or configuration files.

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[gemini-code-assist]

Code Review

This pull request adds support for the vllm_mm_processor_cache_gb parameter to configure the multi-modal processor cache size in vLLM. The changes correctly propagate this new parameter through GRPOVllmEngine, VllmEngine, and VllmArguments. The implementation is straightforward and looks good. I have one minor suggestion to improve code formatting for better readability and maintainability.

[gemini-code-assist]

For better readability and adherence to Python style guides (PEP 8), it's recommended to format this list of keys with one item per line. This makes the list easier to read and modify in the future.

Suggested change

	for key in [
	'enable_expert_parallel', 'enable_sleep_mode', 'disable_cascade_attn', 'load_format',
	'mm_processor_cache_gb'
	]:
	for key in [
	'enable_expert_parallel',
	'enable_sleep_mode',
	'disable_cascade_attn',
	'load_format',
	'mm_processor_cache_gb',
	]: