update to vllm 12-19 (#5223)

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

### Does this PR introduce _any_ user-facing change?
Fix vllm break:
1. [Enable cuda graph for deepepHT, 5.3% throughput improvement, 4.4%
TTFT improvement] (https://github.com/vllm-project/vllm/pull/29558)
Fix Solution: Add the now-necessary `all2all_backend` parameter. The
impact of this parameter on the original `set_splitting_ops_for_v1`
implementation is only that graph mode is disabled in `vllm` if
`deepep_high_throughput` is enabled; it has no effect on the
`vllm-ascend` logic.

2.[Migrate legacy ViT MultiHeadAttention to new MMEncoderAttention
interface ] (https://github.com/vllm-project/vllm/pull/30684)
Fix Solution: The reason why the GPU does not need to convert qkv to 3D
is that the GPU's flash_attention operator is compatible with 3D and 4D
(b s h d and s b ( h d)), but the NPU's flash_attention_unpad operator
only supports 3D (s b ( h d)). Therefore, we need to introduce the
reshape_qkv_to_3d operation.

4.Skip Tencent-Hunyuan/HunyuanOCR test case, as it has following issue
in upgrade vllm code:
https://github.com/vllm-project/vllm-ascend/issues/5297

### How was this patch tested?


Co-authored-by: zxwang <1476209578@qq.com>

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
Signed-off-by: zxwang <1476209578@qq.com>
Co-authored-by: zxwang <1476209578@qq.com>

vllm_ascend/platform.py

@@ -232,7 +232,11 @@ class NPUPlatform(Platform):
                 "using only ACL Graph mode")
             assert compilation_config.mode == CompilationMode.VLLM_COMPILE, \
                 "When enabling VLLM_COMPILE aclgraph, please make sure compilation_config.mode == CompilationMode.VLLM_COMPILE and compilation_config.cudagraph_mode == CUDAGraphMode.VLLM_COMPILE"
-            compilation_config.set_splitting_ops_for_v1()
+            compilation_config.set_splitting_ops_for_v1(
+                all2all_backend=vllm_config.parallel_config.all2all_backend,
+                data_parallel_size=vllm_config.parallel_config.
+                data_parallel_size,
+            )
             compilation_config.use_inductor = False
             compilation_config.splitting_ops.extend(["vllm::mla_forward"])
             update_aclgraph_sizes(vllm_config)