Files
bi_150-vllm/vllm/model_executor/layers/pooler/special.py

174 lines
5.3 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Mapping, Set
from itertools import groupby
import torch
from vllm.config import PoolerConfig
from vllm.model_executor.layers.pooler import PoolingParamsUpdate
from vllm.tasks import PoolingTask
from vllm.v1.pool.metadata import PoolingMetadata
from .abstract import Pooler, PoolerOutput
from .common import ClassifierFn
from .seqwise import (
SequencePoolingFn,
SequencePoolingMethod,
pooler_for_classify,
pooler_for_embed,
)
from .tokwise import AllPool, pooler_for_token_classify, pooler_for_token_embed
class DispatchPooler(Pooler):
"""Dispatches calls to a sub-pooler based on the pooling task."""
@classmethod
def for_embedding(cls, pooler_config: PoolerConfig):
return cls(
{
"token_embed": pooler_for_token_embed(pooler_config),
"embed": pooler_for_embed(pooler_config),
},
)
@classmethod
def for_seq_cls(
cls,
pooler_config: PoolerConfig,
*,
pooling: SequencePoolingMethod | SequencePoolingFn | None = None,
classifier: ClassifierFn | None = None,
):
return cls(
{
"token_classify": pooler_for_token_classify(
pooler_config,
pooling=AllPool(),
classifier=classifier,
),
"classify": pooler_for_classify(
pooler_config,
pooling=pooling,
classifier=classifier,
act_fn="classify",
),
"score": pooler_for_classify(
pooler_config,
pooling=pooling,
classifier=classifier,
act_fn="score",
),
}
)
def __init__(self, poolers_by_task: Mapping[PoolingTask, Pooler]) -> None:
super().__init__()
for task, pooler in poolers_by_task.items():
if task not in pooler.get_supported_tasks():
raise ValueError(
f"{pooler=} does not support {task=}. "
f"Supported tasks: {pooler.get_supported_tasks()}"
)
self.poolers_by_task = poolers_by_task
def get_supported_tasks(self) -> Set[PoolingTask]:
return set(self.poolers_by_task)
def get_pooling_updates(self, task: PoolingTask) -> PoolingParamsUpdate:
return self.poolers_by_task[task].get_pooling_updates(task)
def forward(
self,
hidden_states: torch.Tensor,
pooling_metadata: PoolingMetadata,
) -> PoolerOutput:
poolers_by_task = self.poolers_by_task
outputs = list[torch.Tensor | None]()
offset = 0
for task, group in groupby(pooling_metadata.tasks):
if not (pooler := poolers_by_task.get(task)):
raise ValueError(
f"Unsupported task: {task!r} "
f"Supported tasks: {self.get_supported_tasks()}"
)
num_items = len(list(group))
group_output: PoolerOutput = pooler(
hidden_states,
pooling_metadata[offset : offset + num_items],
)
outputs.extend(group_output)
offset += num_items
return outputs
def extra_repr(self) -> str:
s = f"supported_task={self.get_supported_tasks()}"
return s
class IdentityPooler(Pooler):
def get_supported_tasks(self) -> Set[PoolingTask]:
return {"plugin", "score"}
def forward(
self,
hidden_states: torch.Tensor,
pooling_metadata: PoolingMetadata,
) -> PoolerOutput:
return hidden_states
class BOSEOSFilter(Pooler):
"""Filters the BOS and EOS token results from outputs."""
def __init__(
self,
pooler: Pooler,
bos_token_id: int = -1, # -1 disables the filtering
eos_token_id: int = -1,
) -> None:
super().__init__()
self.pooler = pooler
self.bos_token_id = bos_token_id
self.eos_token_id = eos_token_id
def get_supported_tasks(self) -> Set[PoolingTask]:
return self.pooler.get_supported_tasks()
def get_pooling_updates(self, task: PoolingTask) -> PoolingParamsUpdate:
return PoolingParamsUpdate(requires_token_ids=True)
def forward(
self,
hidden_states: torch.Tensor | list[torch.Tensor],
pooling_metadata: PoolingMetadata,
) -> PoolerOutput:
pooled_outputs = self.pooler(hidden_states, pooling_metadata)
assert isinstance(pooled_outputs, list)
for i, prompt_len in enumerate(pooling_metadata.prompt_lens):
pooled_data = pooled_outputs[i]
assert (
isinstance(pooled_data, torch.Tensor)
and pooled_data.shape[0] == prompt_len
)
token_ids = pooling_metadata.prompt_token_ids[i, :prompt_len]
if token_ids[0] == self.bos_token_id:
pooled_data = pooled_data[1:]
if token_ids[-1] == self.eos_token_id:
pooled_data = pooled_data[:-1]
pooled_outputs[i] = pooled_data.squeeze(-1)
return pooled_outputs
__all__ = ["BOSEOSFilter", "DispatchPooler", "IdentityPooler"]