[Models][Qwen3VL] Fix MM encoder cuda graph input capture

[lgeiger]

Purpose

Using a MM encoder CUDA graph currently fails with for Qwen3VL with:

File "/home/ubuntu/vllm/vllm/model_executor/models/qwen3_vl.py", line 371, in forward
        x = x.view(L, -1, self.temporal_patch_size, self.patch_size, self.patch_size)

RuntimeError: cannot reshape tensor of 0 elements into shape [0, -1, 2, 16, 16] because the unspecified dimension size -1 can be any value and is ambiguous

Qwen2VL and Qwen2.5VL already use ceil to ensure that the capture capacity is never smaller than the token budget:

vllm/vllm/model_executor/models/qwen2_vl.py

Lines 1586 to 1587 in 6548560

	# Use ceil so captured capacity is never smaller than token_budget.
	per_mm_item_output = (token_budget + max_batch_size - 1) // max_batch_size

vllm/vllm/model_executor/models/qwen2_5_vl.py

Lines 1727 to 1731 in 6548560

	# Use ceil here (not floor) so total captured capacity is never smaller
	# than token_budget when token_budget is not divisible by max_batch_size
	# (e.g., 324 budget with max_batch_size=8). Floor under-allocates
	# input_buffer and can fail replay copy for valid single-item batches.
	per_mm_item_output = (token_budget + max_batch_size - 1) // max_batch_size

This PR is a followup on #35963 and applies the same fix to Qwen3VL. /cc @Isotr0py @b-mu

Test Plan

vllm serve Qwen/Qwen3.6-35B-A3B-FP8 --compilation-config '{"cudagraph_mm_encoder": true}'

Test Result

Server starts up properly

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

[gemini-code-assist]

Code Review

This pull request updates the prepare_encoder_cudagraph_capture_inputs method in vllm/model_executor/models/qwen3_vl.py to use ceiling division when calculating per_mm_item_output, ensuring the captured capacity is never smaller than the token_budget. I have no feedback to provide as there were no review comments to evaluate.

[b-mu]

This bug was fixed in #38040.

[Isotr0py]

Duplicate of #38040