[Refactor] Remove the process patches of Qwen2.5-VL and Qwen2.5-Omni (#5035)

### What this PR does / why we need it?

Related to #4084. Before we add the patches temporarily for making
`set_forward_context` patched by `set_ascend_forward_context` in the
function `_process_image_input` and `_process_video_input` of
`Qwen2.5-VL` and `Qwen2.5-Omni` models. After removing these patches, I
met the `AttributeError` for `ForwardContext` missing
`prefetch_mlp_enabled`. So we need to add the defensive check for
`prefetch_mlp_enabled`.

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

No.

### How was this patch tested?

```
vllm serve Qwen/Qwen2.5-VL-7B-Instruct \
    --max-model-len 30000 \
    --max-num-batched-tokens 50000 \
    --max-num-seqs 30 \
    --no-enable-prefix-caching \
    --trust-remote-code \
    --dtype bfloat16
```

```
{"id":"chatcmpl-b66d8acb76905c49","object":"chat.completion","created":1765796863,"model":"/root/.cache/modelscope/hub/models/Qwen/Qwen2.5-VL-7B-Instruct","choices":[{"index":0,"message":{"role":"assistant","content":"The text in the illustration reads \"TONGYI Qwen.\"","refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning":null,"reasoning_content":null},"logprobs":null,"finish_reason":"stop","stop_reason":null,"token_ids":null}],"service_tier":null,"system_fingerprint":null,"usage":{"prompt_tokens":73,"total_tokens":88,"completion_tokens":15,"prompt_tokens_details":null},"prompt_logprobs":null,"prompt_token_ids":null,"kv_transfer_params":null}
```


- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: gcanlin <canlinguosdu@gmail.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/ops/register_custom_ops.py

@@ -116,7 +116,7 @@ def _maybe_prefetch_mlp_gate_up_proj_impl(x_dependency: torch.Tensor,
     except AssertionError:
         return
 
-    if not forward_context.prefetch_mlp_enabled:
+    if not getattr(forward_context, 'prefetch_mlp_enabled', False):
         return
     model_instance = forward_context.model_instance
     prefetch_stream = forward_context.prefetch_stream
@@ -173,7 +173,7 @@ def _maybe_prefetch_mlp_down_proj_impl(x_dependency: torch.Tensor) -> None:
     except AssertionError:
         return
 
-    if not forward_context.prefetch_mlp_enabled:
+    if not getattr(forward_context, 'prefetch_mlp_enabled', False):
         return
     forward_context.prefetch_mlp_down_proj = True
     model_instance = forward_context.model_instance
@@ -202,7 +202,7 @@ def _maybe_wait_prefetch_done_impl(x: torch.Tensor) -> None:
     except AssertionError:
         return
 
-    if not forward_context.prefetch_mlp_enabled:
+    if not getattr(forward_context, 'prefetch_mlp_enabled', False):
         return
     if forward_context.prefetch_mlp_gate_up_proj or \
         forward_context.prefetch_mlp_down_proj:

vllm_ascend/patch/worker/patch_qwen2_5_omni.py

@@ -18,8 +18,7 @@
 import torch
 import torch.nn as nn
 from vllm.model_executor.models.qwen2_5_omni_thinker import (
-    Qwen2_5_VLImageInputs, Qwen2_5_VLVideoInputs,
-    Qwen2_5OmniThinkerForConditionalGeneration)
+    Qwen2_5_VLImageInputs, Qwen2_5_VLVideoInputs)
 
 from vllm_ascend.ascend_forward_context import set_ascend_forward_context
 
@@ -65,8 +64,3 @@ class AscendQwen2_5OmniThinkerForConditionalGeneration(nn.Module):
         sizes = grid_thw.prod(-1) // merge_size // merge_size
 
         return video_embeds.split(sizes.tolist())
-
-
-# NOTE: These will be removed after ascend_forward_context is refactored.
-Qwen2_5OmniThinkerForConditionalGeneration._process_image_input = AscendQwen2_5OmniThinkerForConditionalGeneration._process_image_input
-Qwen2_5OmniThinkerForConditionalGeneration._process_video_input = AscendQwen2_5OmniThinkerForConditionalGeneration._process_video_input

vllm_ascend/patch/worker/patch_qwen2_5_vl.py

@@ -20,9 +20,9 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import torch_npu
-from vllm.model_executor.models.qwen2_5_vl import (
-    Qwen2_5_VisionAttention, Qwen2_5_VLForConditionalGeneration,
-    Qwen2_5_VLImageInputs, Qwen2_5_VLVideoInputs)
+from vllm.model_executor.models.qwen2_5_vl import (Qwen2_5_VisionAttention,
+                                                   Qwen2_5_VLImageInputs,
+                                                   Qwen2_5_VLVideoInputs)
 from vllm.model_executor.models.qwen2_vl import Qwen2VisionAttention
 from vllm.model_executor.models.vision import run_dp_sharded_mrope_vision_model
 
@@ -169,7 +169,3 @@ class AscendQwen2_5_VLForConditionalGeneration(nn.Module):
 # NOTE: This will be removed after MMEncoderAttention has been extract as a CustomOp in vllm.
 Qwen2VisionAttention.forward = AscendQwen2_5_VisionAttention.forward
 Qwen2_5_VisionAttention.forward = AscendQwen2_5_VisionAttention.forward
-
-# NOTE: These will be removed after ascend_forward_context is refactored.
-Qwen2_5_VLForConditionalGeneration._process_image_input = AscendQwen2_5_VLForConditionalGeneration._process_image_input
-Qwen2_5_VLForConditionalGeneration._process_video_input = AscendQwen2_5_VLForConditionalGeneration._process_video_input