from copy import copy from enum import Enum, auto from itertools import count from nanovllm.sampling_params import SamplingParams class SequenceStatus(Enum): WAITING = auto() RUNNING = auto() FINISHED = auto() class Sequence: block_size = 256 counter = count() def __init__(self, token_ids: list[int], sampling_params: SamplingParams): self.seq_id = next(Sequence.counter) self.status = SequenceStatus.WAITING self.token_ids = copy(token_ids) self.num_prompt_tokens = len(token_ids) self._num_cached_tokens = 0 self.block_table = [] self.temperature = sampling_params.temperature self.max_tokens = sampling_params.max_tokens self.ignore_eos = sampling_params.ignore_eos def __len__(self): return len(self.token_ids) def __lt__(self, other): return self.seq_id < other.seq_id def __getitem__(self, key): return self.token_ids[key] @property def is_finished(self): return self.status == SequenceStatus.FINISHED @property def num_completion_tokens(self): return len(self.token_ids) - self.num_prompt_tokens @property def prompt_token_ids(self): return self.token_ids[:self.num_prompt_tokens] @property def completion_token_ids(self): return self.token_ids[self.num_prompt_tokens:] @property def num_cached_tokens(self): return self._num_cached_tokens @num_cached_tokens.setter def num_cached_tokens(self, num_cached_tokens): assert num_cached_tokens % self.block_size == 0 self._num_cached_tokens = num_cached_tokens @property def num_cached_blocks(self): return self.num_cached_tokens // self.block_size @property def num_blocks(self): return (len(self.token_ids) + self.block_size - 1) // self.block_size @property def last_token(self): return self.token_ids[-1] def block(self, i): return self.token_ids[i*self.block_size: (i+1)*self.block_size] def last_block(self): n = self.num_blocks return self.token_ids[(n-1)*self.block_size:] def append_token(self, token_id: int): self.token_ids.append(token_id)