[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/ops/test_activation.py

@@ -53,9 +53,12 @@ def test_QuickGELU_forward(mock_gelu, dummy_tensor, default_vllm_config):
 
 
 @pytest.mark.skipif(is_310p_hw(), reason="non_310P device unittest case.")
+@patch("vllm_ascend.ops.activation.get_weight_prefetch_method",
+       return_value=MagicMock())
 @patch("torch_npu.npu_swiglu", side_effect=lambda x: x + 1)
 def test_SiluAndMul_forward(
     mock_swiglu,
+    mock_get_weight_prefetch_method,
     dummy_tensor,
     default_vllm_config,
 ):