vllm.v1.sample.logits_processor.interface ¶

@dataclass(frozen=True)
class BatchUpdate:
    """Persistent batch state change info for logitsprocs"""

    batch_size: int  # Current num reqs in batch

    # Metadata for requests added to, removed from, and moved
    # within the persistent batch.
    #
    # Key assumption: the `output_tok_ids` list (which is an element of each
    # tuple in `added`) is a reference to the request's running output tokens
    # list; via this reference, the logits processors always see the latest
    # list of generated output tokens.
    #
    # NOTE:
    # * Added or moved requests may replace existing requests with the same
    #   index.
    # * Operations should be processed in the following order:
    #   - removed, added, moved
    removed: Sequence[RemovedRequest]
    added: Sequence[AddedRequest]
    moved: Sequence[MovedRequest]

class LogitsProcessor(ABC):
    @classmethod
    def validate_params(cls, sampling_params: SamplingParams):
        """Validate sampling params for this logits processor.

        Raise ValueError for invalid ones.
        """
        return None

    @abstractmethod
    def __init__(
        self, vllm_config: "VllmConfig", device: torch.device, is_pin_memory: bool
    ) -> None:
        raise NotImplementedError

    @abstractmethod
    def apply(self, logits: torch.Tensor) -> torch.Tensor:
        """Apply LogitsProcessor to batch logits tensor.

        The updated tensor must be returned but may be
        modified in-place.
        """
        raise NotImplementedError

    @abstractmethod
    def is_argmax_invariant(self) -> bool:
        """True if logits processor has no impact on the
        argmax computation in greedy sampling.
        NOTE: may or may not have the same value for all
        instances of a given LogitsProcessor subclass,
        depending on subclass implementation.
        """
        raise NotImplementedError

    @abstractmethod
    def update_state(
        self,
        batch_update: "BatchUpdate | None",
    ) -> None:
        """Called when there are new output tokens, prior
        to each forward pass.

        Args:
            batch_update: Non-None iff there have been changes
                to the batch makeup.
        """
        raise NotImplementedError