[misc] upgrade format to py39 (#7256)
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@@ -13,8 +13,9 @@
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# limitations under the License.
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from abc import ABC, abstractmethod
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from collections.abc import AsyncGenerator, Sequence
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from dataclasses import dataclass
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from typing import TYPE_CHECKING, Any, AsyncGenerator, Dict, List, Literal, Optional, Sequence, Union
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from typing import TYPE_CHECKING, Any, Literal, Optional, Union
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if TYPE_CHECKING:
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@@ -36,8 +37,7 @@ class Response:
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class BaseEngine(ABC):
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r"""
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Base class for inference engine of chat models.
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r"""Base class for inference engine of chat models.
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Must implements async methods: chat(), stream_chat() and get_scores().
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"""
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@@ -47,7 +47,7 @@ class BaseEngine(ABC):
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tokenizer: "PreTrainedTokenizer"
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can_generate: bool
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template: "Template"
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generating_args: Dict[str, Any]
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generating_args: dict[str, Any]
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@abstractmethod
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def __init__(
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@@ -57,31 +57,27 @@ class BaseEngine(ABC):
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finetuning_args: "FinetuningArguments",
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generating_args: "GeneratingArguments",
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) -> None:
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r"""
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Initializes an inference engine.
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"""
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r"""Initialize an inference engine."""
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...
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@abstractmethod
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async def chat(
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self,
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messages: Sequence[Dict[str, str]],
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messages: Sequence[dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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images: Optional[Sequence["ImageInput"]] = None,
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videos: Optional[Sequence["VideoInput"]] = None,
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audios: Optional[Sequence["AudioInput"]] = None,
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**input_kwargs,
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) -> List["Response"]:
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r"""
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Gets a list of responses of the chat model.
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"""
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) -> list["Response"]:
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r"""Get a list of responses of the chat model."""
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...
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@abstractmethod
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async def stream_chat(
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self,
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messages: Sequence[Dict[str, str]],
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messages: Sequence[dict[str, str]],
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system: Optional[str] = None,
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tools: Optional[str] = None,
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images: Optional[Sequence["ImageInput"]] = None,
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@@ -89,18 +85,14 @@ class BaseEngine(ABC):
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audios: Optional[Sequence["AudioInput"]] = None,
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**input_kwargs,
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) -> AsyncGenerator[str, None]:
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r"""
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Gets the response token-by-token of the chat model.
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"""
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r"""Get the response token-by-token of the chat model."""
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...
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@abstractmethod
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async def get_scores(
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self,
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batch_input: List[str],
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batch_input: list[str],
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**input_kwargs,
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) -> List[float]:
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r"""
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Gets a list of scores of the reward model.
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"""
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) -> list[float]:
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r"""Get a list of scores of the reward model."""
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...
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