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- from abc import ABC, abstractmethod
- from typing import List, Optional
- from transformers import PreTrainedTokenizer
- from aphrodite.lora.request import LoRARequest
- class BaseTokenizerGroup(ABC):
- """A group of tokenizers that can be used for LoRA adapters."""
- @abstractmethod
- def ping(self) -> bool:
- """Check if the tokenizer group is alive."""
- pass
- @abstractmethod
- def get_max_input_len(self,
- lora_request: Optional[LoRARequest] = None
- ) -> Optional[int]:
- """Get the maximum input length for the LoRA request."""
- pass
- @abstractmethod
- def encode(self,
- prompt: str,
- request_id: Optional[str] = None,
- lora_request: Optional[LoRARequest] = None) -> List[int]:
- """Encode a prompt using the tokenizer group."""
- pass
- @abstractmethod
- async def encode_async(
- self,
- prompt: str,
- request_id: Optional[str] = None,
- lora_request: Optional[LoRARequest] = None) -> List[int]:
- """Encode a prompt using the tokenizer group."""
- pass
- @abstractmethod
- def get_lora_tokenizer(
- self,
- lora_request: Optional[LoRARequest] = None
- ) -> "PreTrainedTokenizer":
- """Get a tokenizer for a LoRA request."""
- pass
- @abstractmethod
- async def get_lora_tokenizer_async(
- self,
- lora_request: Optional[LoRARequest] = None
- ) -> "PreTrainedTokenizer":
- """Get a tokenizer for a LoRA request."""
- pass
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