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import os
from abc import ABC, abstractmethod
from typing import BinaryIO, Optional, Tuple, Union
from torch import Tensor
from torchaudio.io import CodecConfig
from .common import AudioMetaData
class Backend(ABC):
@staticmethod
@abstractmethod
def info(uri: Union[BinaryIO, str, os.PathLike], format: Optional[str], buffer_size: int = 4096) -> AudioMetaData:
raise NotImplementedError
@staticmethod
@abstractmethod
def load(
uri: Union[BinaryIO, str, os.PathLike],
frame_offset: int = 0,
num_frames: int = -1,
normalize: bool = True,
channels_first: bool = True,
format: Optional[str] = None,
buffer_size: int = 4096,
) -> Tuple[Tensor, int]:
raise NotImplementedError
@staticmethod
@abstractmethod
def save(
uri: Union[BinaryIO, str, os.PathLike],
src: Tensor,
sample_rate: int,
channels_first: bool = True,
format: Optional[str] = None,
encoding: Optional[str] = None,
bits_per_sample: Optional[int] = None,
buffer_size: int = 4096,
compression: Optional[Union[CodecConfig, float, int]] = None,
) -> None:
raise NotImplementedError
@staticmethod
@abstractmethod
def can_decode(uri: Union[BinaryIO, str, os.PathLike], format: Optional[str]) -> bool:
raise NotImplementedError
@staticmethod
@abstractmethod
def can_encode(uri: Union[BinaryIO, str, os.PathLike], format: Optional[str]) -> bool:
raise NotImplementedError
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