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[main2main] upgrade vllm main 0202 (#6560)

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### 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>
This commit is contained in:
meihanc
2026-02-05 19:31:17 +08:00
committed by GitHub
parent 2c1608265b
commit 922e5c163b
28 changed files with 246 additions and 30 deletions
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17
vllm_ascend/ops/mla.py
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@@ -23,7 +23,6 @@ from typing import Optional
import torch
from torch import nn
from vllm.attention.layer import MLAAttention
from vllm.config import CacheConfig, get_current_vllm_config
from vllm.distributed import get_tensor_model_parallel_world_size
from vllm.forward_context import ForwardContext, get_forward_context
@@ -34,6 +33,12 @@ from vllm.utils.torch_utils import direct_register_custom_op
from vllm.v1.attention.backend import AttentionMetadata # type: ignore
from vllm_ascend.ascend_config import get_ascend_config
from vllm_ascend.utils import vllm_version_is
if vllm_version_is("v0.15.0"):
from vllm.attention.layer import MLAAttention # type: ignore
else:
from vllm.model_executor.layers.attention import MLAAttention
class IndexerWrapper(nn.Module):
@@ -125,6 +130,16 @@ class AscendMultiHeadLatentAttention(MultiHeadLatentAttentionWrapper):
o_proj=mla_modules.o_proj,
)
original_process_weights = self.mla_attn.process_weights_after_loading
def wrapped_process_weights(act_dtype: torch.dtype):
from vllm_ascend.attention.sfa_v1 import AscendSFAImpl
if not isinstance(self.mla_attn.impl, AscendSFAImpl):
original_process_weights(act_dtype)
self.mla_attn.impl.process_weights_after_loading(act_dtype)
self.mla_attn.process_weights_after_loading = wrapped_process_weights
compilation_config = get_current_vllm_config().compilation_config
if prefix in compilation_config.static_forward_context:
raise ValueError(f"Duplicate layer name: {prefix}")