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[Model][2/N] Improve all pooling task | Support multi-vector retrieval (#25370)

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Signed-off-by: wang.yuqi <noooop@126.com>
This commit is contained in:
wang.yuqi
2025-10-15 19:14:41 +08:00
committed by GitHub
parent d4d1a6024f
commit f54f85129e
41 changed files with 786 additions and 399 deletions
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42
vllm/model_executor/models/adapters.py
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@@ -250,7 +250,7 @@ def as_embedding_model(cls: _T) -> _T:
self.pooler = DispatchPooler(
{
"encode": Pooler.for_encode(pooler_config),
"token_embed": Pooler.for_token_embed(pooler_config),
"embed": Pooler.for_embed(pooler_config),
},
)
@@ -279,11 +279,8 @@ def as_seq_cls_model(cls: _T) -> _T:
# Lazy import
from vllm.model_executor.layers.linear import ReplicatedLinear
from vllm.model_executor.layers.pooler import (
ClassifierPooler,
DispatchPooler,
Pooler,
PoolingMethod,
PoolingType,
)
from vllm.model_executor.models.interfaces import SupportsCrossEncoding
from vllm.sequence import IntermediateTensors
@@ -302,42 +299,29 @@ def as_seq_cls_model(cls: _T) -> _T:
model_config.hidden_size,
config.num_labels,
bias=False,
params_dtype=torch.float32,
params_dtype=vllm_config.model_config.head_dtype,
quant_config=quant_config,
return_bias=False,
prefix=maybe_prefix(prefix, "score"),
)
pooler_config = vllm_config.model_config.pooler_config
assert pooler_config is not None
pooling_type_str = pooler_config.pooling_type
assert pooling_type_str is not None
pooling_type = PoolingType[pooling_type_str]
self.pooler = DispatchPooler(
{
"encode": Pooler.for_encode(pooler_config),
"classify": ClassifierPooler(
pooling=PoolingMethod.from_pooling_type(pooling_type),
classifier=self._classifier,
act_fn=ClassifierPooler.act_fn_for_seq_cls(
vllm_config.model_config
),
"token_classify": Pooler.for_token_classify(
pooler_config, classifier=self.score
),
"score": ClassifierPooler(
pooling=PoolingMethod.from_pooling_type(pooling_type),
classifier=self._classifier,
act_fn=ClassifierPooler.act_fn_for_cross_encoder(
vllm_config.model_config
),
"classify": Pooler.for_classify(
pooler_config, classifier=self.score, act_fn="classify"
),
"score": Pooler.for_classify(
pooler_config, classifier=self.score, act_fn="score"
),
}
)
def _classifier(self, x: torch.Tensor):
x, _ = self.score(x.float())
return x
def forward(
self,
input_ids: torch.Tensor,
@@ -393,7 +377,11 @@ def as_reward_model(cls: _T) -> _T:
assert pooler_config is not None
self.pooler = DispatchPooler(
{"encode": Pooler.for_encode(pooler_config)},
{
"token_classify": Pooler.for_token_classify(
pooler_config=pooler_config
)
}
)
ModelForReward.__name__ = _get_pooling_model_name(cls.__name__, "ForReward")