【A5】【Qwen VL】Qwen VL adapt for A5 (#7046)

### What this PR does / why we need it?
Replace the '_npu_flash_attention_unpad' operator with the
'npu_fusion_attention' operator to ensure that the Qwen VL model can run
in the A5 environment and remove the 'mrope' operator call restriction
for A5.
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.16.0
- vLLM main:
4034c3d32e

Signed-off-by: 汪越 <wangyue361@h-partners.com>

vllm_ascend/ops/mm_encoder_attention.py

@@ -118,19 +118,18 @@ class AscendMMEncoderAttention(MMEncoderAttention):
             k = F.pad(k, (0, pad_len), mode="constant", value=0)
             v = F.pad(v, (0, pad_len), mode="constant", value=0)
 
-        context_layer = torch.empty_like(q)
+        seq_lens_cpu = list(seq_lens_cpu.cumsum(0))
 
-        # operator requires pta version >= 2.5.1
-        torch_npu._npu_flash_attention_unpad(
+        context_layer = torch_npu.npu_fusion_attention(
             query=q,
             key=k,
             value=v,
-            seq_len=seq_lens_cpu,
-            scale_value=self.scale_value,
-            num_heads=self.num_heads,
-            num_kv_heads=self.num_kv_heads,
-            out=context_layer,
-        )
+            actual_seq_qlen=seq_lens_cpu,
+            actual_seq_kvlen=seq_lens_cpu,
+            head_num=self.num_heads,
+            scale=self.scale_value,
+            input_layout="TND",
+        )[0]
 
         if self.enable_pad:
             context_layer = context_layer[..., :origin_shape]

vllm_ascend/ops/rotary_embedding.py

@@ -32,7 +32,7 @@ from vllm.triton_utils import HAS_TRITON
 
 from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 from vllm_ascend.platform import NPUPlatform
-from vllm_ascend.utils import AscendDeviceType, get_ascend_device_type, has_rope, is_vl_model
+from vllm_ascend.utils import has_rope, is_vl_model
 
 if HAS_TRITON:
     from vllm.model_executor.layers.rotary_embedding.mrope import triton_mrope
@@ -519,7 +519,7 @@ class AscendMRotaryEmbedding(MRotaryEmbedding):
             # todo: need cann update in 8.5.0
             return self.forward_triton(positions, query, key)
 
-        if self.mrope_section != [16, 24, 24] or get_ascend_device_type() == AscendDeviceType.A5:
+        if self.mrope_section != [16, 24, 24]:
             return super().forward_oot(positions, query, key)
 
         import torch_npu