init

vllm/spec_decode/interfaces.py

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+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+
+import torch
+
+from vllm.sequence import ExecuteModelRequest
+
+
+@dataclass
+class SpeculativeProposals:
+    """Datastructure used to represent proposal tokens from some proposer. It
+    also tracks how many speculative tokens each sequence has.
+    """
+
+    # Speculative proposal tokens.
+    proposal_token_ids: torch.Tensor
+
+    # Probabilities of the proposal tokens according to the proposer.
+    proposal_probs: torch.Tensor
+
+    # The valid length of each proposal; can be zero.
+    proposal_lens: torch.Tensor
+
+    def __repr__(self):
+        return (f"SpeculativeProposals("
+                f"proposal_token_ids={self.proposal_token_ids}, "
+                f"proposal_probs={self.proposal_probs.shape}, "
+                f"proposal_lens={self.proposal_lens})")
+
+
+@dataclass
+class SpeculativeScores:
+    """Datastructure used to represent the scores of speculative tokens
+    according to the scoring model.
+    """
+
+    # Probabilities of the speculative tokens according to the scoring model.
+    probs: torch.Tensor
+
+    # Log-probabilities of the speculative tokens according to the scoring
+    # model. These values can be used to generate Logprob objects that are
+    # returned to the user.
+    logprobs: torch.Tensor
+
+    # Token ids sampled from the scoring model. Used for speculative bonus
+    # tokens and also non-speculative normal decoding.
+    token_ids: torch.Tensor
+
+    def __repr__(self):
+        return (f"SpeculativeScores("
+                f"probs={self.probs.shape}, "
+                f"token_ids={self.token_ids.shape})")
+
+
+class SpeculativeProposer(ABC):
+
+    @abstractmethod
+    def get_proposals(
+        self,
+        execute_model_req: ExecuteModelRequest,
+    ) -> SpeculativeProposals:
+        raise NotImplementedError
+
+
+class SpeculativeScorer(ABC):
+
+    @abstractmethod
+    def score_proposals(
+        self,
+        execute_model_req: ExecuteModelRequest,
+        proposals: SpeculativeProposals,
+    ) -> SpeculativeScores:
+        raise NotImplementedError