# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project from dataclasses import dataclass, field from typing import Optional import numpy as np import prometheus_client from vllm.config import SpeculativeConfig from vllm.logger import init_logger logger = init_logger(__name__) @dataclass class SpecDecodingStats: """Per-step iteration decoding stats from scheduler. Each scheduler step, statistics on spec decoding performance are aggregated across requests by the scheduler and returned to the frontend in EngineCoreOutputs->SchedulerStats. """ num_spec_tokens: int num_drafts: int = 0 num_draft_tokens: int = 0 num_accepted_tokens: int = 0 num_accepted_tokens_per_pos: list[int] = field(default_factory=list) @classmethod def new(cls, num_spec_tokens: int) -> "SpecDecodingStats": return cls(num_spec_tokens=num_spec_tokens, num_accepted_tokens_per_pos=[0] * num_spec_tokens) def observe_draft(self, num_draft_tokens: int, num_accepted_tokens: int): self.num_drafts += 1 self.num_draft_tokens += num_draft_tokens self.num_accepted_tokens += num_accepted_tokens assert num_accepted_tokens <= self.num_spec_tokens for i in range(num_accepted_tokens): self.num_accepted_tokens_per_pos[i] += 1 class SpecDecodingLogging: """Aggregate and log spec decoding metrics. LoggingStatLogger aggregates per-iteration metrics over a set time interval using observe() and then logs them using log() before resetting to zero. """ def __init__(self): self.reset() def reset(self): self.num_drafts: list[int] = [] self.num_draft_tokens: list[int] = [] self.num_accepted_tokens: list[int] = [] self.accepted_tokens_per_pos_lists: list[list[int]] = [] def observe(self, spec_decoding_stats: SpecDecodingStats): self.num_drafts.append(spec_decoding_stats.num_drafts) self.num_draft_tokens.append(spec_decoding_stats.num_draft_tokens) self.num_accepted_tokens.append( spec_decoding_stats.num_accepted_tokens) self.accepted_tokens_per_pos_lists.append( spec_decoding_stats.num_accepted_tokens_per_pos) def log(self, log_fn=logger.info): if not self.num_drafts: return num_drafts = np.sum(self.num_drafts) num_draft_tokens = np.sum(self.num_draft_tokens) num_accepted_tokens = np.sum(self.num_accepted_tokens) draft_acceptance_rate = (num_accepted_tokens / num_draft_tokens * 100 if num_draft_tokens > 0 else float("nan")) # Conventionally, mean acceptance length includes the bonus token mean_acceptance_length = 1 + (num_accepted_tokens / num_drafts) pos_matrix = np.array(self.accepted_tokens_per_pos_lists) acceptance_rates = np.sum(pos_matrix, axis=0) / num_drafts rates_str = ", ".join(f"{p:.3f}" for p in acceptance_rates) log_fn( "SpecDecoding metrics: " "Draft acceptance rate: %.1f%%, " "Mean acceptance length: %.2f, " "Accepted: %d tokens, " "Drafted: %d tokens, " "Per-position acceptance rate: %s", draft_acceptance_rate, mean_acceptance_length, num_accepted_tokens, num_draft_tokens, rates_str, ) self.reset() class SpecDecodingProm: """Record spec decoding metrics in Prometheus. The acceptance rate can be calculated using a PromQL query: rate(vllm:spec_decode_num_accepted_tokens_total[$interval]) / rate(vllm:spec_decode_num_draft_tokens_total[$interval]) The mean acceptance length (conventionally including bonus tokens) can be calculated using: 1 + ( rate(vllm:spec_decode_num_accepted_tokens_total[$interval]) / rate(vllm:spec_decode_num_drafts[$interval])) A per-position acceptance rate vector can be computed using vllm:spec_decode_num_accepted_tokens_per_pos[$interval] / vllm:spec_decode_num_drafts[$interval] """ _counter_cls = prometheus_client.Counter def __init__( self, speculative_config: Optional[SpeculativeConfig], labelnames: list[str], labelvalues: list[str], ): self.spec_decoding_enabled = speculative_config is not None if not self.spec_decoding_enabled: return self.counter_spec_decode_num_drafts = \ self._counter_cls( name="vllm:spec_decode_num_drafts", documentation="Number of spec decoding drafts.", labelnames=labelnames).labels(*labelvalues) self.counter_spec_decode_num_draft_tokens = \ self._counter_cls( name="vllm:spec_decode_num_draft_tokens", documentation="Number of draft tokens.", labelnames=labelnames,).labels(*labelvalues) self.counter_spec_decode_num_accepted_tokens = \ self._counter_cls( name="vllm:spec_decode_num_accepted_tokens", documentation="Number of accepted tokens.", labelnames=labelnames).labels(*labelvalues) assert speculative_config is not None num_spec_tokens = (speculative_config.num_speculative_tokens if self.spec_decoding_enabled else 0) pos_labelnames = labelnames + ["position"] base_counter = self._counter_cls( name="vllm:spec_decode_num_accepted_tokens_per_pos", documentation="Accepted tokens per draft position.", labelnames=pos_labelnames, ) self.counter_spec_decode_num_accepted_tokens_per_pos: list[ prometheus_client.Counter] = [] for pos in range(num_spec_tokens): pos_labelvalues = labelvalues + [str(pos)] self.counter_spec_decode_num_accepted_tokens_per_pos.append( base_counter.labels(*pos_labelvalues)) def observe(self, spec_decoding_stats: SpecDecodingStats): if not self.spec_decoding_enabled: return self.counter_spec_decode_num_drafts.inc(spec_decoding_stats.num_drafts) self.counter_spec_decode_num_draft_tokens.inc( spec_decoding_stats.num_draft_tokens) self.counter_spec_decode_num_accepted_tokens.inc( spec_decoding_stats.num_accepted_tokens) for pos, counter in enumerate( self.counter_spec_decode_num_accepted_tokens_per_pos): counter.inc(spec_decoding_stats.num_accepted_tokens_per_pos[pos])