[bugfix] fix torchair runtime error caused by configuration mismtaches and file missing (#2532)

### What this PR does / why we need it?
This PR ports #2312 #2506 #2531 to main branch.

Original implementation of torchair caching forces users to make
everything prepared, fix all the configuration and enable
`use_cached_npu_graph`, and it might cause some problems confusing to
understand and tackle for users. It is better to compile the graph twice
instead of reusing the old kvcaches and cached torchair graph. And the
extra duration time is acceptable. Additionally, this pr fixes a
recompilation problem of torchair graph mode caused by
`running_in_graph` variable in `AscendMLATorchairImpl`.

### Does this PR introduce _any_ user-facing change?
If users want to enabling torchair.cache_compile with high compilation
speed, it is recommended to enable both `use_cached_kv_cache_bytes` and
`use_cached_graph` in `torchair_graph_config`. Without
`use_cached_kv_cache_bytes`, we'll compile torchair computation graph
twice to avoid runtime error caused by configuration mismtaches (the
second compilation will be much faster). Additionally, we've made a
change to how the TORCHAIR_CACHE_HOME enviroment variable is utilized to
enhance safety and prevent accidental file deletion by adding a suffix
directory.

### How was this patch tested?
CI and e2e vllm serving pass.


- vLLM version: v0.10.1.1
- vLLM main:
70549c1245

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>

vllm_ascend/torchair/torchair_worker.py

@@ -17,9 +17,9 @@ import torch
 from vllm.logger import logger
 
 import vllm_ascend.envs as envs_ascend
+from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.torchair.torchair_model_runner import NPUTorchairModelRunner
 from vllm_ascend.torchair.utils import (check_kv_cache_bytes_cache_exist,
-                                        check_torchair_cache_exist,
                                         delete_torchair_cache_file,
                                         read_kv_cache_bytes_from_file)
 from vllm_ascend.worker.worker_v1 import NPUWorker
@@ -33,7 +33,9 @@ class NPUTorchairWorker(NPUWorker):
 
         available_kv_cache_memory = super().determine_available_memory()
 
-        if check_torchair_cache_exist() and check_kv_cache_bytes_cache_exist():
+        if get_ascend_config(
+        ).torchair_graph_config.use_cached_kv_cache_bytes and check_kv_cache_bytes_cache_exist(
+        ):
             old_kv_cache_bytes = read_kv_cache_bytes_from_file(
                 torch.distributed.get_rank())
             if 0 < old_kv_cache_bytes <= available_kv_cache_memory: