[refact] unified soc_version code (#4359)

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

Currently, there are two paths to judge the chip type in code,
`get_ascend_soc_version` use `get_soc_version` api in torch_npu, and
`is_310p` `use _build_info.__soc_version__`, which generate when
install. We need to unify the two paths.

We need to unify these codes based on the following points:

1. We need to ensure consistency in chip type judgment between compiling
and running states;
2. In compiling state, we need chip type to complete op's compilation,
but in running state, we only need device
type(910B/910_93/310P/910_95/etc) to make code branch judgement;
3. In compiling state, torch_npu may not have been installed yet, so we
can't use torch_npu's api.

Based on the above points, we have made the following changes:

1. When user set env `SOC_VERSION`, use it; when not set, query
soc_version by `npu-smi`;
2. generate device_type based on soc_version when compiling, and write
`__device_type__` instead of `__soc_version__` in `_build_info.py`;
3. In running state, use `__device_type__` to judge code branch.

### Does this PR introduce _any_ user-facing change?

When not set env `SOC_VERSION`, it will not be `ASCEND910B1` by default,
we will query soc_version by `npu-smi`. And env `SOC_VERSION` must be in
the list `soc_to_device` in `setup.py`.

- vLLM version: v0.11.0
- vLLM main:
2918c1b49c

Signed-off-by: zzzzwwjj <1183291235@qq.com>

vllm_ascend/torchair/torchair_attention.py

@@ -34,8 +34,8 @@ from vllm_ascend.attention.attention_v1 import (AscendAttentionBackend,
                                                 AscendMetadata)
 from vllm_ascend.attention.utils import AscendCommonAttentionMetadata
 from vllm_ascend.torchair.utils import TorchairCommonAttentionMetadata
-from vllm_ascend.utils import (ACL_FORMAT_FRACTAL_NZ, aligned_16, is_310p,
-                               nd_to_nz_2d)
+from vllm_ascend.utils import (ACL_FORMAT_FRACTAL_NZ, AscendDeviceType,
+                               aligned_16, get_ascend_device_type, nd_to_nz_2d)
 
 
 class AscendAttentionTorchairBackend(AscendAttentionBackend):
@@ -185,7 +185,8 @@ class AscendAttentionTorchairMetadataBuilder(AscendAttentionMetadataBuilder):
         attn_mask = common_attn_metadata.attn_mask
 
         attn_state = common_attn_metadata.attn_state
-        if is_310p() and attn_state == AscendAttentionState.PrefillNoCache:
+        if get_ascend_device_type(
+        ) == AscendDeviceType._310P and attn_state == AscendAttentionState.PrefillNoCache:
             mask_nz = nd_to_nz_2d(attn_mask)
             attn_mask = torch_npu.npu_format_cast(mask_nz.contiguous(), 29)
 
@@ -381,7 +382,7 @@ class AscendAttentionTorchairBackendImpl(AttentionImpl):
             key = key.view(-1, self.num_kv_heads, self.head_size)
             value = value.view(-1, self.num_kv_heads, self.head_size)
 
-            if is_310p():
+            if get_ascend_device_type() == AscendDeviceType._310P:
                 # align q k v output tensors
                 query = aligned_16(query)
                 key = aligned_16(key)