ai-content-maker/.venv/Lib/site-packages/torchaudio/_backend/soundfile.py

55 lines
1.7 KiB
Python

import os
from typing import BinaryIO, Optional, Tuple, Union
import torch
from torchaudio.io import CodecConfig
from . import soundfile_backend
from .backend import Backend
from .common import AudioMetaData
class SoundfileBackend(Backend):
@staticmethod
def info(uri: Union[BinaryIO, str, os.PathLike], format: Optional[str], buffer_size: int = 4096) -> AudioMetaData:
return soundfile_backend.info(uri, format)
@staticmethod
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[torch.Tensor, int]:
return soundfile_backend.load(uri, frame_offset, num_frames, normalize, channels_first, format)
@staticmethod
def save(
uri: Union[BinaryIO, str, os.PathLike],
src: torch.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:
if compression:
raise ValueError("soundfile backend does not support argument `compression`.")
soundfile_backend.save(
uri, src, sample_rate, channels_first, format=format, encoding=encoding, bits_per_sample=bits_per_sample
)
@staticmethod
def can_decode(uri, format) -> bool:
return True
@staticmethod
def can_encode(uri, format) -> bool:
return True