280 lines
8.6 KiB
Python
280 lines
8.6 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import asyncio
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from abc import ABC, abstractmethod
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from collections.abc import Sequence
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from typing import TYPE_CHECKING, Any, overload
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from vllm.inputs import EmbedsPrompt, TextPrompt, TokensPrompt
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from vllm.tokenizers import TokenizerLike
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from vllm.utils.async_utils import AsyncMicrobatchTokenizer
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from .embed_utils import safe_load_prompt_embeds
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from .inputs import (
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DictPrompt,
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EncoderDecoderDictPrompt,
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EncoderDecoderTokPrompt,
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TokPrompt,
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)
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from .params import ChatParams, TokenizeParams
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if TYPE_CHECKING:
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from vllm.config import ModelConfig
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from vllm.entrypoints.chat_utils import (
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ChatCompletionMessageParam,
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ConversationMessage,
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)
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class BaseRenderer(ABC):
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@classmethod
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@abstractmethod
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def from_config(
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cls,
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config: "ModelConfig",
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tokenizer_kwargs: dict[str, Any],
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) -> "BaseRenderer":
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raise NotImplementedError
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def __init__(self, config: "ModelConfig") -> None:
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super().__init__()
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self.config = config
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# Lazy initialization since offline LLM doesn't use async
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self._async_tokenizer: AsyncMicrobatchTokenizer | None = None
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@property
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@abstractmethod
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def tokenizer(self) -> TokenizerLike | None:
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raise NotImplementedError
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def get_tokenizer(self) -> TokenizerLike:
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tokenizer = self.tokenizer
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if tokenizer is None:
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raise ValueError("Tokenizer not available when `skip_tokenizer_init=True`")
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return tokenizer
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def get_async_tokenizer(self) -> AsyncMicrobatchTokenizer:
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if self._async_tokenizer is None:
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self._async_tokenizer = AsyncMicrobatchTokenizer(self.get_tokenizer())
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return self._async_tokenizer
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# Step 1: Convert raw inputs to prompts
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def render_prompt(
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self,
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prompt: DictPrompt | bytes,
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) -> DictPrompt:
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if isinstance(prompt, bytes):
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embeds = safe_load_prompt_embeds(self.config, prompt)
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prompt = EmbedsPrompt(prompt_embeds=embeds)
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return prompt
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def render_prompts(
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self,
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prompts: Sequence[DictPrompt | bytes],
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) -> list[DictPrompt]:
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if len(prompts) == 0:
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raise ValueError("You must pass at least one prompt")
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return [self.render_prompt(prompt) for prompt in prompts]
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async def render_prompts_async(
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self,
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prompts: Sequence[DictPrompt | bytes],
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) -> list[DictPrompt]:
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return self.render_prompts(prompts)
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@abstractmethod
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def render_messages(
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self,
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messages: list["ChatCompletionMessageParam"],
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params: ChatParams,
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) -> tuple[list["ConversationMessage"], DictPrompt]:
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raise NotImplementedError
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async def render_messages_async(
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self,
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messages: list["ChatCompletionMessageParam"],
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params: ChatParams,
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) -> tuple[list["ConversationMessage"], DictPrompt]:
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return self.render_messages(messages, params)
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# Step 2: Tokenize prompts if necessary
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def _tokenize_prompt(
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self,
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prompt: TextPrompt,
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params: TokenizeParams,
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) -> TokensPrompt:
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tokenizer = self.get_tokenizer()
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prompt_token_ids = tokenizer.encode(
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prompt["prompt"],
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**params.get_encode_kwargs(),
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)
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return TokensPrompt(prompt_token_ids=prompt_token_ids, **prompt)
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async def _tokenize_prompt_async(
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self,
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prompt: TextPrompt,
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params: TokenizeParams,
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) -> TokensPrompt:
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tokenizer = self.get_async_tokenizer()
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prompt_token_ids = await tokenizer.encode(
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prompt["prompt"],
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**params.get_encode_kwargs(),
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)
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return TokensPrompt(prompt_token_ids=prompt_token_ids, **prompt)
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def _detokenize_prompt(self, prompt: TokensPrompt) -> TokensPrompt:
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tokenizer = self.get_tokenizer()
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prompt["prompt"] = tokenizer.decode(prompt["prompt_token_ids"])
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return prompt
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async def _detokenize_prompt_async(self, prompt: TokensPrompt) -> TokensPrompt:
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tokenizer = self.get_async_tokenizer()
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prompt["prompt"] = await tokenizer.decode(prompt["prompt_token_ids"])
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return prompt
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def _tokenize_enc_dec_prompt(
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self,
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prompt: EncoderDecoderDictPrompt,
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params: TokenizeParams,
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) -> EncoderDecoderTokPrompt:
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enc_prompt, dec_prompt = (
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self.tokenize_prompt(prompt["encoder_prompt"], params),
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(
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None
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if prompt["decoder_prompt"] is None
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else self.tokenize_prompt(prompt["decoder_prompt"], params)
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),
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)
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return EncoderDecoderTokPrompt(
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encoder_prompt=enc_prompt,
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decoder_prompt=dec_prompt,
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)
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async def _tokenize_enc_dec_prompt_async(
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self,
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prompt: EncoderDecoderDictPrompt,
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params: TokenizeParams,
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) -> EncoderDecoderTokPrompt:
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enc_prompt, dec_prompt = await asyncio.gather(
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self.tokenize_prompt_async(prompt["encoder_prompt"], params),
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(
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asyncio.sleep(0)
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if prompt["decoder_prompt"] is None
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else self.tokenize_prompt_async(prompt["decoder_prompt"], params)
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),
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)
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return EncoderDecoderTokPrompt(
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encoder_prompt=enc_prompt,
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decoder_prompt=dec_prompt,
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)
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@overload
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def tokenize_prompt(
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self,
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prompt: TextPrompt | TokensPrompt,
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params: TokenizeParams,
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) -> TokensPrompt: ...
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@overload
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def tokenize_prompt( # type: ignore[misc]
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self,
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prompt: EmbedsPrompt,
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params: TokenizeParams,
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) -> EmbedsPrompt: ...
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@overload
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def tokenize_prompt( # type: ignore[misc]
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self,
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prompt: EncoderDecoderDictPrompt,
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params: TokenizeParams,
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) -> EncoderDecoderTokPrompt: ...
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def tokenize_prompt(
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self,
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prompt: DictPrompt,
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params: TokenizeParams,
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) -> TokPrompt:
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if "encoder_prompt" in prompt:
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return self._tokenize_enc_dec_prompt(prompt, params) # type: ignore[arg-type]
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if "prompt_token_ids" not in prompt and "prompt_embeds" not in prompt:
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prompt = params.apply_pre_tokenization(self.tokenizer, prompt)
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prompt = self._tokenize_prompt(prompt, params)
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if params.needs_detokenization and "prompt" not in prompt:
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if "prompt_token_ids" not in prompt:
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raise RuntimeError("Cannot run detokenization on embeddings")
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prompt = self._detokenize_prompt(prompt) # type: ignore[arg-type]
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return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type]
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def tokenize_prompts(
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self,
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prompts: Sequence[DictPrompt],
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params: TokenizeParams,
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) -> list[TokPrompt]:
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return [self.tokenize_prompt(prompt, params) for prompt in prompts]
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@overload
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async def tokenize_prompt_async(
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self,
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prompt: TextPrompt | TokensPrompt,
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params: TokenizeParams,
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) -> TokensPrompt: ...
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@overload
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async def tokenize_prompt_async( # type: ignore[misc]
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self,
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prompt: EmbedsPrompt,
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params: TokenizeParams,
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) -> EmbedsPrompt: ...
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@overload
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async def tokenize_prompt_async( # type: ignore[misc]
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self,
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prompt: EncoderDecoderDictPrompt,
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params: TokenizeParams,
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) -> EncoderDecoderTokPrompt: ...
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async def tokenize_prompt_async(
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self,
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prompt: DictPrompt,
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params: TokenizeParams,
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) -> TokPrompt:
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if "encoder_prompt" in prompt:
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return await self._tokenize_enc_dec_prompt_async(prompt, params) # type: ignore[arg-type]
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if "prompt_token_ids" not in prompt and "prompt_embeds" not in prompt:
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prompt = params.apply_pre_tokenization(self.tokenizer, prompt)
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prompt = await self._tokenize_prompt_async(prompt, params)
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if params.needs_detokenization and "prompt" not in prompt:
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if "prompt_token_ids" not in prompt:
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raise RuntimeError("Cannot run detokenization on embeddings")
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prompt = await self._detokenize_prompt_async(prompt) # type: ignore[arg-type]
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return params.apply_post_tokenization(self.tokenizer, prompt) # type: ignore[arg-type]
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async def tokenize_prompts_async(
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self,
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prompts: Sequence[DictPrompt],
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params: TokenizeParams,
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) -> list[TokPrompt]:
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return await asyncio.gather(
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*(self.tokenize_prompt_async(prompt, params) for prompt in prompts)
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)
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