### What this PR does / why we need it?
This 'test_rejection_sampler' unit test is something wrong.
> def test_sample_recovered_tokens_pytorch_autoregressive(self):
> output_token_ids = torch.empty(2, dtype=torch.int32)
> cu_num_draft_tokens = torch.tensor([1, 1])
> draft_token_ids = torch.tensor([0, 1])
len(draft_token_ids ) = 2, cu_num_draft_tokens should be
torch.tensor([1, 2]) or torch.tensor([2, 2])
I fix it and set cu_num_draft_tokens = torch.tensor([1, 2]). The methods
before and after optimization can pass.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
NA
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
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Signed-off-by: lio <1983142975@qq.com>
cd58a643c5