[VLM][Model] Add test for InternViT vision encoder

[Isotr0py]

FILL IN THE PR DESCRIPTION HERE

FIX #xxxx (link existing issues this PR will resolve)

• As mentioned in [Bugfix] Fix input processor for InternVL2 model #7164, we can only test the vision encoder to cover InternVL2-26B larger models etc, they only differ from vision encoder.
• Since the AWQ 26B model ran out of VRAM with tp=1 in [Model] Add AWQ quantization support for InternVL2 model #7187, I decided to use this way to cover large InternVL2 models test.

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[github-actions]

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[Isotr0py]

/ready

[DarkLight1337]

@youkaichao is this a valid way of setting up distributed environment?

[youkaichao]

sorry didn't notice I was tagged for this PR.

is it possible to test this through openai api server?

vllm/tests/utils.py

Line 52 in 16422ea

class RemoteOpenAIServer:

it has clean set up and clean up.

[Isotr0py]

I think it's difficult to test this model through openai api server, because this model is the vision tower of InternVL instead of a complete model, which may have no compatibility with openai api server (or I can't find a valid way to make it run on the server).

The motivation of this PR is to test this vision tower while we can't test the whole model with tp_size=1 due to VRAM limit.

BTW, this distributed environment setup is referring to the lora confest:

vllm/tests/lora/conftest.py

Lines 81 to 93 in dd164d7

	@pytest.fixture
	def dist_init():
	temp_file = tempfile.mkstemp()[1]
	init_distributed_environment(
	world_size=1,
	rank=0,
	distributed_init_method=f"file://{temp_file}",
	local_rank=0,
	backend="nccl",
	)
	initialize_model_parallel(1, 1)
	yield
	cleanup()

Maybe we can use this fixture as well?

[youkaichao]

you can try to use these fixtures, as long as they work.

[DarkLight1337]

Sorry for the delay, let's merge this once the tests pass.