[Refact]Refact MLA/SFA weight prefetch to consist with moe weight prefetch (#6629)

### What this PR does / why we need it?
1. [Refact] Refact MLA/SFA weight prefetch to consist with moe weight
prefetch
2. Remove duplicated o_proj weight prefetch in forward for MLA/SFA

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

### How was this patch tested?

1) Performance result:
Perf test data:
*) MLA:

| | 1st test | 2nd test | Output Token Throughput(Avg) | Performance
improvement percentage |
| --- | --- | --- | --- | --- |
| o_proj duplicate prefetch | 11.9669 token/s | 12.0287 token/s |
11.9978 |
| o_proj no duplicate prefetch | 12.5594 token/s | 12.6216 token/s |
12.5905 | 4.94%| |

single layer performace improve: 5%~8%

*) SFA:

| | 1st test | 2nd test | Output Token Throughput(Avg) | Performance
improvement percentage |
| --- | --- | --- | --- | --- |
| o_proj duplicate prefetch | 13.0523 token/s | 13.1084 token/s |
13.08035 | |
| o_proj no duplicate prefetch | 13.9844 token/s | 14.1678 token/s |
14.0761 | 7.6% |

- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>

tests/ut/attention/test_mla_v1.py

@@ -967,10 +967,10 @@ class TestAscendMLAImpl(TestBase):
         mock_npu_fused_infer_attention_score.assert_called_once()
 
     @patch("torch.ops.vllm.maybe_all_gather_and_maybe_unpad")
-    @patch("vllm_ascend.attention.mla_v1.maybe_npu_prefetch")
-    def test_mla_preprocess(self, magic_npu_fetch,
+    @patch("vllm_ascend.attention.mla_v1.get_weight_prefetch_method",
+           return_value=MagicMock())
+    def test_mla_preprocess(self, mock_get_weight_prefetch_method,
                             mock_maybe_all_gather_and_maybe_unpad):
-        magic_npu_fetch.return_value = MagicMock()
         mock_maybe_all_gather_and_maybe_unpad.side_effect = lambda x, label: x
         batch_size = 4
         seq_len = 8