chore: import upstream snapshot with attribution

vllm/model_executor/layers/pooler/common.py

@@ -0,0 +1,32 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+from collections.abc import Callable
+from dataclasses import dataclass
+from typing import TypeVar
+
+import torch
+
+from vllm.pooling_params import PoolingParams
+
+_T = TypeVar("_T", bound=torch.Tensor | list[torch.Tensor])
+
+ProjectorFn = Callable[[torch.Tensor], torch.Tensor]
+ClassifierFn = Callable[[torch.Tensor], torch.Tensor]
+ActivationFn = Callable[[_T], _T]
+
+
+@dataclass(frozen=True)
+class PoolingParamsUpdate:
+    requires_token_ids: bool = False
+    """Set this flag to enable prompt token IDs for your pooler."""
+
+    def __or__(self, other: "PoolingParamsUpdate") -> "PoolingParamsUpdate":
+        return PoolingParamsUpdate(
+            requires_token_ids=self.requires_token_ids or other.requires_token_ids,
+        )
+
+    def apply(self, params: PoolingParams) -> None:
+        params.requires_token_ids = self.requires_token_ids
+
+
+__all__ = ["ActivationFn", "ClassifierFn", "ProjectorFn", "PoolingParamsUpdate"]