[BugFix] Fix logits repetition penalty cuda check

[PicoCreator]

Essential Elements of an Effective PR Description Checklist

One line bug fix for sampling on CPU, on systems with GPU's as per reported here:
#22591

It really is a simple fix

def apply_repetition_penalties(logits: torch.Tensor, prompt_mask: torch.Tensor,
                               output_mask: torch.Tensor,
                               repetition_penalties: torch.Tensor) -> None:
    """Apply repetition penalties to logits in-place.
    Args:
        logits: The logits tensor of shape [num_seqs, vocab_size].
        prompt_mask: A boolean tensor indicating which tokens appear in the prompt.
        output_mask: A boolean tensor indicating which tokens appear in the output.
        repetition_penalties: The repetition penalties of shape (num_seqs, ).
    """
    # if current_platform.is_cuda() and logits.is_contiguous(): # <-- this was the original code
    if logits.is_cuda and logits.is_contiguous(): # <-- this is the fix
        apply_repetition_penalties_cuda(logits, prompt_mask, output_mask,
                                        repetition_penalties)
    else:
        apply_repetition_penalties_torch(logits, prompt_mask, output_mask,
                                         repetition_penalties)

Fixes #22591

Purpose

Test Plan

Test Result

(Optional) Documentation Update

[github-actions]

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[gemini-code-assist]

Code Review

This pull request addresses a bug in the apply_repetition_penalties function that caused a runtime error when running on a CPU device on a system with GPUs. The original implementation incorrectly used current_platform.is_cuda() to dispatch to a CUDA-specific kernel, which failed when the logits tensor was on the CPU. The fix replaces this platform check with logits.is_cuda(), ensuring that the dispatch logic correctly depends on the tensor's device. This is the correct approach and resolves the reported issue. The change is well-targeted and I see no further issues.

[njhill]

LGTM thanks

[DarkLight1337]

Thanks, next time please sign-off your commits according to https://docs.vllm.ai/en/latest/contributing/index.html#dco-and-signed-off-by