[0.11.0][MTP][Aclgraph] Fix the support aclgraph with MTP (#3912)

### What this PR does / why we need it?
Fix 2 breaks of aclgraph with MTP:
1. deepseekmtp in vllm 0.11.0 does not support aclgraph and lack the
`support_torch_compile` decorator
2. There is a d2h synchornization in the original forward of mtp
predictor. The fix pr in vllm
https://github.com/vllm-project/vllm/pull/27643

As we'll fix it in vllm main, this fix pr is only needed in branch
v0.11.0-dev

The profling shows that MTP replays in aclgraph now:
<img width="1612" height="1866" alt="a7d7f04155df4ed454b7eb20a92b2e2a"
src="https://github.com/user-attachments/assets/eaa4b9ff-aeb0-416d-964f-5a06e497f155"
/>

### How was this patch tested?
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---------

Signed-off-by: MengqingCao <cmq0113@163.com>

vllm_ascend/patch/worker/patch_deepseek_mtp.py

@@ -1,16 +1,54 @@
+from typing import Optional
+
 import torch
 import torch.nn as nn
+import vllm
 from transformers import PretrainedConfig
+from vllm.compilation.decorators import support_torch_compile
 from vllm.config import VllmConfig
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.quantization import QuantizationConfig
 from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead
-from vllm.model_executor.models.deepseek_mtp import \
+from vllm.model_executor.models.deepseek_mtp import (
-    DeepSeekMultiTokenPredictorLayer
+    DeepSeekMTP, DeepSeekMultiTokenPredictorLayer)
 from vllm.model_executor.models.deepseek_v2 import DeepseekV2DecoderLayer
 from vllm.model_executor.models.utils import maybe_prefix
 
 
+def forward(
+    self,
+    input_ids: torch.Tensor,
+    positions: torch.Tensor,
+    previous_hidden_states: torch.Tensor,
+    inputs_embeds: Optional[torch.Tensor] = None,
+    spec_step_index: int = 0,
+) -> torch.Tensor:
+    assert inputs_embeds is not None
+    # masking inputs at position 0, as not needed by MTP
+    # Patch this for aclgraph support, as the original operation introduced d2h sync,
+    # which breaks aclgraph
+    inputs_embeds = torch.where(positions.unsqueeze(-1) == 0, 0, inputs_embeds)
+    inputs_embeds = self.enorm(inputs_embeds)
+    previous_hidden_states = self.hnorm(previous_hidden_states)
+
+    hidden_states = self.eh_proj(
+        torch.cat([inputs_embeds, previous_hidden_states], dim=-1))
+
+    hidden_states, residual = self.mtp_block(positions=positions,
+                                             hidden_states=hidden_states,
+                                             residual=None)
+    hidden_states = residual + hidden_states
+    return hidden_states
+
+
+# Patch this only for aclgraph support, as this is not support in vLLM 0.11.0
+@support_torch_compile
+class AscendDeepSeekMTP(DeepSeekMTP):
+
+    def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
+        super().__init__(vllm_config=vllm_config, prefix=prefix)
+
+
 class SharedHead(nn.Module):
 
     def __init__(
@@ -53,3 +91,4 @@ def predictor_init(self, vllm_config: VllmConfig, prefix: str) -> None:
 
 
 DeepSeekMultiTokenPredictorLayer.__init__ = predictor_init
+vllm.model_executor.models.deepseek_mtp.DeepSeekMultiTokenPredictorLayer.forward = forward

vllm_ascend/spec_decode/mtp_proposer.py

@@ -11,7 +11,6 @@ from vllm.forward_context import BatchDescriptor, get_forward_context
 from vllm.model_executor.model_loader import get_model_loader
 from vllm.model_executor.model_loader.utils import (
     process_weights_after_loading, set_default_torch_dtype)
-from vllm.model_executor.models.deepseek_mtp import DeepSeekMTP
 from vllm.v1.core.sched.output import SchedulerOutput
 from vllm.v1.sample.metadata import SamplingMetadata
 from vllm.v1.spec_decode.metadata import SpecDecodeMetadata
@@ -19,6 +18,8 @@ from vllm.v1.spec_decode.metadata import SpecDecodeMetadata
 from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.ascend_forward_context import set_ascend_forward_context
 from vllm_ascend.attention.utils import AscendCommonAttentionMetadata
+from vllm_ascend.patch.worker.patch_deepseek_mtp import \
+    AscendDeepSeekMTP as DeepSeekMTP
 from vllm_ascend.spec_decode.interface import Proposer, SpecDcodeType
 from vllm_ascend.torchair.models.torchair_deepseek_mtp import \
     TorchairDeepSeekMTP