[BugFix] [310p] Fix attention accuracy issue (#6803)

### What this PR does / why we need it?
This pull request resolves an attention accuracy issue by enhancing the
AttentionMaskBuilder310 to correctly handle the maximum model length.
The change ensures that the attention mask generation process is
properly parameterized by the model's configuration, rather than relying
on a fixed internal value. This leads to more accurate attention mask
creation, which is crucial for the correct functioning of the attention
mechanism.
Update fused_moe to main branch.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Qwen3 dense mode & moe model e2e test
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1

---------

Signed-off-by: pu-zhe <zpuaa@outlook.com>

tests/ut/_310p/attention/test_attention_mask_310.py

@@ -23,7 +23,8 @@ from vllm_ascend._310p.attention.attention_mask import AttentionMaskBuilder310
 
 class TestAttentionMaskBuilder310(TestBase):
     def setUp(self):
-        self.attention_mask_builder = AttentionMaskBuilder310(torch.device("cpu"))
+        self.max_seqlen = 4096
+        self.attention_mask_builder = AttentionMaskBuilder310(torch.device("cpu"), self.max_seqlen)
 
     def test_get_attention_mask_310_for_pooling_model(self):
         model_config = MagicMock()
@@ -36,7 +37,7 @@ class TestAttentionMaskBuilder310(TestBase):
         mock_format_cast.side_effect = lambda x, y: x
         model_config = MagicMock()
         attn_mask = self.attention_mask_builder.get_attention_mask(model_config)
-        self.assertEqual(attn_mask.shape, (1, 128, 2048, 16))
+        self.assertEqual(attn_mask.shape, (1, self.max_seqlen // 16, self.max_seqlen, 16))
         self.assertEqual(attn_mask[0][-1][0][-1], torch.tensor(float("-inf"), dtype=torch.float16))
 
     @patch("torch_npu.npu_format_cast")
@@ -47,7 +48,7 @@ class TestAttentionMaskBuilder310(TestBase):
 
         sliding_window = 128
         swa_mask = self.attention_mask_builder.get_swa_mask(torch.float16, sliding_window)
-        self.assertEqual(swa_mask.shape, (1, 128, 2048, 16))
+        self.assertEqual(swa_mask.shape, (1, self.max_seqlen // 16, self.max_seqlen, 16))
         self.assertEqual(swa_mask[0][-1][0][-1], torch.tensor(float("-inf"), dtype=torch.float16))
         self.assertEqual(swa_mask[0][0][-1][0], torch.tensor(float("-inf"), dtype=torch.float16))
 
@@ -58,4 +59,4 @@ class TestAttentionMaskBuilder310(TestBase):
         attn_metadata.query_start_loc = torch.tensor([0, 1, 5])
         attn_metadata.seq_lens = torch.tensor([7, 4])
         attn_mask = self.attention_mask_builder.get_splitfuse_mask(attn_metadata, torch.device("cpu"))
-        self.assertEqual(attn_mask.shape, (1, 128, 16, 16))
+        self.assertEqual(attn_mask.shape, (1, self.max_seqlen // 16, 16, 16))