[main2main] upgrade vllm main 0202 (#6560)

### What this PR does / why we need it?
1. Fix `TypeError: FusedMoEParallelConfig.__init__() missing 1 required
positional argument: 'is_sequence_parallel'` due to
https://github.com/vllm-project/vllm/pull/32567
2. Fix ` TypeError: '>' not supported between instances of 'MagicMock'
and 'int'` due to https://github.com/vllm-project/vllm/pull/33035
3. Fix `TypeError: Can't instantiate abstract class AscendMLAImpl with
abstract methods forward_mha, forward_mqa` and AttributeError: 'bool'
object has no attribute 'process_weights_after_loading' due to
https://github.com/vllm-project/vllm/pull/33284
4. Fix `'AscendSharedFusedMoE' object has no attribute
'_routed_input_transform'`due to
https://github.com/vllm-project/vllm/pull/32790
5. Fix `NPUModelRunner._dummy_run() got an unexpected keyword argument
'num_active_loras'` due to
https://github.com/vllm-project/vllm/pull/32005
6. Fix the problem caused by` 'tuple' object has no attribute 'job_id'`
due to https://github.com/vllm-project/vllm/pull/27492
7. Fix the problem that all_moe_layers is not equal to vllm.moe_forward,
vllm.moe_forward_shared due to
https://github.com/vllm-project/vllm/pull/33184
8. Add patch to fix the problem "got multiple values for keyword
argument 'add_special_tokens'" due to
https://github.com/vllm-project/vllm/pull/32863
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0

---------

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: hfadzxy <starmoon_zhang@163.com>

vllm_ascend/worker/model_runner_v1.py

@@ -30,7 +30,6 @@ import numpy as np
 import torch
 import torch.distributed as dist
 import torch.nn as nn
-from vllm.attention.layer import Attention, MLAAttention
 from vllm.compilation.cuda_graph import CUDAGraphStat
 from vllm.config import CompilationMode, CUDAGraphMode, VllmConfig, get_layers_from_vllm_config
 from vllm.distributed import get_tensor_model_parallel_world_size, tensor_model_parallel_all_gather
@@ -137,6 +136,12 @@ if TYPE_CHECKING:
 else:
     xgr = LazyLoader("xgr", globals(), "xgrammar")
 
+from vllm_ascend.utils import vllm_version_is
+
+if vllm_version_is("v0.15.0"):
+    from vllm.attention.layer import Attention, MLAAttention  # type: ignore
+else:
+    from vllm.model_executor.layers.attention import Attention, MLAAttention
 
 # if true, allow tensor initialization and casting with internal format (e.g., NZ)
 torch.npu.config.allow_internal_format = True
@@ -2026,6 +2031,7 @@ class NPUModelRunner(GPUModelRunner):
         remove_lora: bool = True,
         activate_lora: bool = False,
         is_graph_capturing: bool = False,
+        num_active_loras: int = 0,
     ) -> tuple[torch.Tensor, torch.Tensor]:
         # only support eager mode and piecewise graph now
         assert cudagraph_runtime_mode is None or cudagraph_runtime_mode.valid_runtime_modes()