71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
from copy import copy
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from enum import Enum, auto
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from itertools import count
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from nanovllm.sampling_params import SamplingParams
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class SequenceStatus(Enum):
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WAITING = auto()
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RUNNING = auto()
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FINISHED = auto()
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class Sequence:
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counter = count()
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def __init__(self, token_ids: list[int], sampling_params: SamplingParams):
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self.seq_id = next(Sequence.counter)
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self.status = SequenceStatus.WAITING
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self.token_ids = copy(token_ids)
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self.num_prompt_tokens = len(token_ids)
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self._num_cached_tokens = 0
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self.block_table = []
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self.temperature = sampling_params.temperature
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self.max_tokens = sampling_params.max_tokens
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self.ignore_eos = sampling_params.ignore_eos
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def __len__(self):
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return len(self.token_ids)
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def __lt__(self, other):
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return self.seq_id < other.seq_id
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def __getitem__(self, key):
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return self.token_ids[key]
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@property
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def num_completion_tokens(self):
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return len(self.token_ids) - self.num_prompt_tokens
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@property
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def num_cached_tokens(self):
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return self._num_cached_tokens
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@num_cached_tokens.setter
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def num_cached_tokens(self, num_cached_tokens):
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assert num_cached_tokens % 256 == 0
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self._num_cached_tokens = num_cached_tokens
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@property
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def num_cached_blocks(self):
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return self.num_cached_tokens // 256
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@property
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def num_blocks(self):
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return (len(self.token_ids) + 255) // 256
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@property
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def last_token(self):
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return self.token_ids[-1]
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def block(self, i, block_size=256):
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return self.token_ids[i*block_size: (i+1)*block_size]
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def last_block(self, block_size=256):
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n = self.num_blocks
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return self.token_ids[(n-1)*block_size:]
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def append_token(self, token_id: int):
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self.token_ids.append(token_id)
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