[Bugfix][MM] Move grid_thw tensor to cpu before directly converting to numpy

[shen-shanshan]

Purpose

When grid_thw in ViT forward is a tensor, it should be moved to cpu before directly converting to numpy, otherwise there could be error like:

TypeError: can't convert npu:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

Test Plan

Test Result

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[gemini-code-assist]

Code Review

This pull request correctly fixes a TypeError that occurs when converting a tensor to a NumPy array on a non-CPU device. The change introduces a .to("cpu") call to move the grid_thw tensor to the CPU before the conversion, which is the proper way to handle this. The fix is targeted and effective. I have no further comments.

[lgeiger]

I'm a bit confused where this error is coming from. Shouldn't #28168 prevent grid_thw from being moved to the GPU in the first place?
@shen-shanshan do you mind sharing a reproduction in where you are seeing this issue pop up?

[shen-shanshan]

I'm a bit confused where this error is coming from. Shouldn't #28168 prevent grid_thw from being moved to the GPU in the first place? @shen-shanshan do you mind sharing a reproduction in where you are seeing this issue pop up?

After discussing with @DarkLight1337 , this error is because the model_runner in vllm-ascend didn't implement multimodal_cpu_fields, which has defined what tensor should be moved to cpu for different multi-modal models. I will solve this problem just in vllm-ascend, thanks for reviewing.