Files
vLLM/vllm/inputs/parse.py
T
cc2a77d7f1 [Core] [Bugfix] Add Input Embeddings (#15428)
Signed-off-by: Andrew Sansom <andrew@protopia.ai>
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
Co-authored-by: 临景 <linjing.yx@alibaba-inc.com>
Co-authored-by: Bryce1010 <bryceyx@gmail.com>
Co-authored-by: Nan2018 <nan@protopia.ai>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk>
2025-05-02 01:06:39 -07:00

162 lines
4.7 KiB
Python

# SPDX-License-Identifier: Apache-2.0
from collections.abc import Sequence
from typing import Literal, Optional, TypedDict, Union, cast, overload
from typing_extensions import TypeIs
from vllm.utils import is_list_of
from .data import (EmbedsInputs, EmbedsPrompt, ExplicitEncoderDecoderPrompt,
ProcessorInputs, PromptType, SingletonInputs,
SingletonPrompt, TextPrompt, TokensPrompt)
class ParsedText(TypedDict):
content: str
is_tokens: Literal[False]
class ParsedTokens(TypedDict):
content: list[int]
is_tokens: Literal[True]
@overload
def parse_and_batch_prompt(
prompt: Union[str, list[str]]) -> Sequence[ParsedText]:
...
@overload
def parse_and_batch_prompt(
prompt: Union[list[int], list[list[int]]]) -> Sequence[ParsedTokens]:
...
def parse_and_batch_prompt(
prompt: Union[str, list[str], list[int], list[list[int]]],
) -> Union[Sequence[ParsedText], Sequence[ParsedTokens]]:
if isinstance(prompt, str):
# case 1: a string
return [ParsedText(content=prompt, is_tokens=False)]
if isinstance(prompt, list):
if len(prompt) == 0:
raise ValueError("please provide at least one prompt")
if is_list_of(prompt, str):
# case 2: array of strings
prompt = cast(list[str], prompt)
return [
ParsedText(content=elem, is_tokens=False) for elem in prompt
]
if is_list_of(prompt, int):
# case 3: array of tokens
prompt = cast(list[int], prompt)
return [ParsedTokens(content=prompt, is_tokens=True)]
if is_list_of(prompt, list):
prompt = cast(list[list[int]], prompt)
if len(prompt[0]) == 0:
raise ValueError("please provide at least one prompt")
if is_list_of(prompt[0], int):
# case 4: array of token arrays
return [
ParsedTokens(content=elem, is_tokens=True)
for elem in prompt
]
raise TypeError("prompt must be a string, array of strings, "
"array of tokens, or array of token arrays")
class ParsedStrPrompt(TypedDict):
type: Literal["str"]
content: str
class ParsedTextPrompt(TypedDict):
type: Literal["text"]
content: TextPrompt
class ParsedTokensPrompt(TypedDict):
type: Literal["tokens"]
content: TokensPrompt
class ParsedEmbedsPrompt(TypedDict):
type: Literal['embeds']
content: EmbedsPrompt
@overload
def parse_singleton_prompt(prompt: str) -> ParsedStrPrompt:
...
@overload
def parse_singleton_prompt(prompt: TextPrompt) -> ParsedTextPrompt:
...
@overload
def parse_singleton_prompt(prompt: TokensPrompt) -> ParsedTokensPrompt:
...
@overload
def parse_singleton_prompt(prompt: EmbedsPrompt) -> ParsedEmbedsPrompt:
...
def parse_singleton_prompt(
prompt: SingletonPrompt,
) -> Union[ParsedStrPrompt, ParsedTextPrompt, ParsedTokensPrompt,
ParsedEmbedsPrompt]:
if isinstance(prompt, str):
return ParsedStrPrompt(type="str", content=prompt)
elif isinstance(prompt, dict):
# Type ignores are because mypy does not correctly infer the TypedDicts
# Pyright does succeed.
if "prompt_embeds" in prompt:
return ParsedEmbedsPrompt(
type="embeds", content=prompt) # type: ignore[typeddict-item]
elif "prompt_token_ids" in prompt:
return ParsedTokensPrompt(
type="tokens", content=prompt) # type: ignore[typeddict-item]
elif "prompt" in prompt:
return ParsedTextPrompt(type="text", content=prompt)
raise TypeError(
"inputs must be a string, TextPrompt, TokensPrompt, or EmbedsPrompt")
def is_token_prompt(prompt: PromptType) -> TypeIs[TokensPrompt]:
return isinstance(prompt, dict) and "prompt_token_ids" in prompt
def is_embeds_prompt(prompt: PromptType) -> TypeIs[EmbedsPrompt]:
return isinstance(prompt, dict) and "prompt_embeds" in prompt
def is_explicit_encoder_decoder_prompt(
prompt: PromptType) -> TypeIs[ExplicitEncoderDecoderPrompt]:
return isinstance(prompt, dict) and "encoder_prompt" in prompt
def is_embeds_inputs(inputs: SingletonInputs) -> TypeIs[EmbedsInputs]:
return isinstance(inputs, dict) and inputs["type"] == "embeds"
def split_enc_dec_inputs(
inputs: ProcessorInputs,
) -> tuple[Optional[SingletonInputs], SingletonInputs]:
if "encoder" in inputs and "decoder" in inputs:
# NOTE: This passes pyright but not mypy
return (
inputs["encoder"], # type: ignore[typeddict-item]
inputs["decoder"], # type: ignore[typeddict-item]
)
return None, inputs