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nano-vllm/nanovllm/config.py
2025-06-27 01:51:57 +08:00

27 lines
845 B
Python

import os
from dataclasses import dataclass
from transformers import AutoConfig
@dataclass
class Config:
model: str
max_num_batched_tokens: int = 16384
max_num_seqs: int = 512
max_model_len: int = 4096
gpu_memory_utilization: float = 0.9
tensor_parallel_size: int = 1
enforce_eager: bool = False
hf_config: AutoConfig | None = None
eos: int = -1
kvcache_block_size: int = 256
num_kvcache_blocks: int = -1
def __post_init__(self):
assert os.path.isdir(self.model)
assert self.kvcache_block_size % 256 == 0
assert 1 <= self.tensor_parallel_size <= 8
self.hf_config = AutoConfig.from_pretrained(self.model)
self.max_model_len = min(self.max_model_len, self.hf_config.max_position_embeddings)
assert self.max_num_batched_tokens >= self.max_model_len