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[Feat] support basic pcp&dcp for qwen3next (#6091)

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### What this PR does / why we need it?
This PR implements Context Parallelism (CP) support for the Qwen3-Next
model, including PCP (Parallel Context Parallelism) and DCP
(Dynamic/Data Context Parallelism).

- vLLM version: v0.15.0
- vLLM main:
f176443446

---------

Signed-off-by: SunnyLee219 <3294305115@qq.com>
Signed-off-by: Jingchun Gao <gaojingchun1@huawei.com>
Signed-off-by: 白永斌 <baiyongbin3@h-partners.com>
Signed-off-by: Bai Yongbin <845473182@qq.com>
Co-authored-by: SunnyLee219 <3294305115@qq.com>
Co-authored-by: Jingchun Gao <gaojingchun1@huawei.com>
Co-authored-by: 白永斌 <baiyongbin3@h-partners.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
This commit is contained in:
Bai Yongbin
2026-02-28 21:44:08 +08:00
committed by GitHub
parent 64fba51275
commit 9d09488b4a
16 changed files with 906 additions and 81 deletions
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16
vllm_ascend/attention/attention_v1.py
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@@ -892,10 +892,12 @@ class AscendAttentionBackendImpl(AttentionImpl):
def reshape_and_cache(
self,
query: torch.Tensor,
key: torch.Tensor,
value: torch.Tensor,
kv_cache: tuple[torch.Tensor],
attn_metadata: AscendMetadata,
output: torch.Tensor,
):
if len(kv_cache) > 1:
if self.is_kv_producer:
@@ -915,7 +917,7 @@ class AscendAttentionBackendImpl(AttentionImpl):
)
if self.is_kv_producer:
attn_metadata.reshape_cache_event.record()
return key, value
return query, key, value, output
def forward_impl(
self,
@@ -970,12 +972,20 @@ class AscendAttentionBackendImpl(AttentionImpl):
num_tokens = query.shape[0]
if attn_metadata is None:
return output.fill_(0)
output_padded = None
if key is not None and value is not None:
key, value = self.reshape_and_cache(key, value, kv_cache, attn_metadata)
output_padded = output
query, key, value, output_padded = self.reshape_and_cache(
query, key, value, kv_cache, attn_metadata, output
)
# pooling model branch
if attn_metadata.model_runner_type == "pooling":
attn_output = self._forward_encoder_attention(query, key, value, attn_metadata, output)
output[:num_tokens] = attn_output[:num_tokens]
return output
output = self.forward_impl(query, key, value, kv_cache, attn_metadata, output)
if output_padded is not None:
attn_output = self.forward_impl(query, key, value, kv_cache, attn_metadata, output_padded)
else:
attn_output = self.forward_impl(query, key, value, kv_cache, attn_metadata, output)
output[:num_tokens] = attn_output[:num_tokens]
return output