[Bugfix] Fix race condition in d2h transfer (#3372)

### What this PR does / why we need it?

Using non-blocking operations for device-to-host transfers can lead to
data corruption in later steps. The CPU tensor is accessed right after
the transfer is triggered, but the transfer might not be complete yet.
As a result, the data could be wrong. This problem was seen in the A3
environment during `profile_run`.

### How was this patch tested?
CI pass.

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: Jade Zheng <zheng.shoujian@outlook.com>

vllm_ascend/torchair/quantization/torchair_w8a8_dynamic.py

@@ -459,7 +459,7 @@ def torchair_fused_experts_with_all2all(
         token_counts_combined = token_counts_combined.view(
             2, ep_group.world_size, -1).sum(dim=2)
         token_counts_combined_cpu = token_counts_combined.to(
-            torch.device("cpu"), non_blocking=True).numpy()
+            torch.device("cpu"), non_blocking=False).numpy()
         all_tokens = gather_sizes.sum()
 
         gathered_tokens = quantized_tokens.new_empty(all_tokens.item(),