[Bugfix] Fix CPU backend crash in KV cache block zeroing

[DorBernsohn]

• Override _zero_block_ids in CPUModelRunner with a pure PyTorch implementation to avoid calling the Triton GPU kernel (_zero_kv_blocks_kernel), which crashes on CPU nodes without an active GPU driver.

  • The Triton block-zeroing kernel was introduced in [BUGFIX][Mamba][Qwen3.5] Zero freed SSM cache blocks on GPU #35219 (March 10), but CPUModelRunner lacked a CPU-safe fallback. This caused a TypeError: 'function' object is not subscriptable on the first inference request for all models using the CPU backend.

Closes #37546

Test plan

• Verified syntax and pre-commit hooks pass
• Implemented a minimal override using PyTorch (tensor.zero_()) to replace the Triton kernel path only for CPU
• Existing CPU CI tests cover the integration path

[gemini-code-assist]

Code Review

The changes effectively address the reported bug by providing a CPU-specific implementation for zeroing KV cache blocks. This prevents the TypeError that occurred when GPU-specific kernels were invoked on CPU-only environments. The solution is straightforward and uses standard PyTorch operations, ensuring compatibility and correctness for the CPU backend.

[bigPYJ1151]

For CPU attention backend the zeroing is not required. Different from FlashAttention, in CPU attention logits of invalid postions will be assigned to -INF, so invalid KV cache will not affect computation. Therefor _zero_block_ids can be passed.

vllm/csrc/cpu/cpu_attn_impl.hpp

Lines 1129 to 1134 in 35141a7

	for (int32_t i = 0; i < left_invalid_token_num; ++i) {
	curr_logits_buffer[i] = neg_inf;
	}
	for (int32_t i = 0; i < right_invalid_token_num; ++i) {
	curr_logits_buffer_tail[i] = neg_inf;
	}

[DorBernsohn]

@bigPYJ1151 youre right - updated _zero_block_ids to be a no-op since the cpu attention backend already handles invalid positions by assigning -inf to their logits.

[bigPYJ1151]

Thanks! LGTM