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e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
115 lines
3.4 KiB
Python
115 lines
3.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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from typing import List, Literal, Sequence, TypedDict, Union, cast, overload
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from typing_extensions import TypeIs
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from vllm.utils import is_list_of
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from .data import (EncoderDecoderInputs, ExplicitEncoderDecoderPrompt,
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ProcessorInputs, PromptType, SingletonPrompt, TextPrompt,
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TokensPrompt)
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class ParsedText(TypedDict):
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content: str
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is_tokens: Literal[False]
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class ParsedTokens(TypedDict):
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content: List[int]
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is_tokens: Literal[True]
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@overload
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def parse_and_batch_prompt(
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prompt: Union[str, List[str]]) -> Sequence[ParsedText]:
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...
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@overload
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def parse_and_batch_prompt(
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prompt: Union[List[int], List[List[int]]]) -> Sequence[ParsedTokens]:
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...
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def parse_and_batch_prompt(
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prompt: Union[str, List[str], List[int], List[List[int]]],
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) -> Union[Sequence[ParsedText], Sequence[ParsedTokens]]:
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if isinstance(prompt, str):
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# case 1: a string
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return [ParsedText(content=prompt, is_tokens=False)]
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if isinstance(prompt, list):
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if len(prompt) == 0:
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raise ValueError("please provide at least one prompt")
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if is_list_of(prompt, str):
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# case 2: array of strings
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prompt = cast(List[str], prompt)
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return [
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ParsedText(content=elem, is_tokens=False) for elem in prompt
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]
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if is_list_of(prompt, int):
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# case 3: array of tokens
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prompt = cast(List[int], prompt)
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return [ParsedTokens(content=prompt, is_tokens=True)]
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if is_list_of(prompt, list):
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prompt = cast(List[List[int]], prompt)
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if len(prompt[0]) == 0:
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raise ValueError("please provide at least one prompt")
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if is_list_of(prompt[0], int):
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# case 4: array of token arrays
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return [
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ParsedTokens(content=elem, is_tokens=True)
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for elem in prompt
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]
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raise TypeError("prompt must be a string, array of strings, "
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"array of tokens, or array of token arrays")
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class ParsedStrPrompt(TypedDict):
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type: Literal["str"]
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content: str
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class ParsedTextPrompt(TypedDict):
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type: Literal["text"]
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content: TextPrompt
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class ParsedTokensPrompt(TypedDict):
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type: Literal["tokens"]
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content: TokensPrompt
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def parse_singleton_prompt(
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prompt: SingletonPrompt,
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) -> Union[ParsedStrPrompt, ParsedTextPrompt, ParsedTokensPrompt]:
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if isinstance(prompt, str):
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return ParsedStrPrompt(type="str", content=prompt)
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elif isinstance(prompt, dict):
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if "prompt_token_ids" in prompt:
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return ParsedTokensPrompt(type="tokens",
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content=prompt) # type: ignore
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elif "prompt" in prompt:
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return ParsedTextPrompt(type="text", content=prompt)
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raise TypeError("inputs must be a string, TextPrompt, or TokensPrompt")
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def is_token_prompt(prompt: PromptType) -> TypeIs[TokensPrompt]:
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return isinstance(prompt, dict) and "prompt_token_ids" in prompt
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def is_explicit_encoder_decoder_prompt(
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prompt: PromptType) -> TypeIs[ExplicitEncoderDecoderPrompt]:
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return isinstance(prompt, dict) and "encoder_prompt" in prompt
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def is_encoder_decoder_inputs(
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inputs: ProcessorInputs) -> TypeIs[EncoderDecoderInputs]:
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return "encoder" in inputs and "decoder" in inputs
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