+
+ Source code for torchaudio.backend.common
+from typing import Any, Optional
+
+
+[docs]class SignalInfo:
+
"""Data class returned ``info`` functions.
+
+
Used by :ref:`sox backend<sox_backend>` and :ref:`soundfile backend<soundfile_backend>`
+
+
See https://fossies.org/dox/sox-14.4.2/structsox__signalinfo__t.html
+
+
:ivar Optional[int] channels: The number of channels
+
:ivar Optional[float] rate: Sampleing rate
+
:ivar Optional[int] precision: Bit depth
+
:ivar Optional[int] length: For :ref:`sox backend<sox_backend>`, the number of samples.
+
(frames * channels). For :ref:`soundfile backend<soundfile_backend>`, the number of frames.
+
"""
+
def __init__(self,
+
channels: Optional[int] = None,
+
rate: Optional[float] = None,
+
precision: Optional[int] = None,
+
length: Optional[int] = None) -> None:
+
self.channels = channels
+
self.rate = rate
+
self.precision = precision
+
self.length = length
+
+
+[docs]class EncodingInfo:
+
"""Data class returned ``info`` functions.
+
+
Used by :ref:`sox backend<sox_backend>` and :ref:`soundfile backend<soundfile_backend>`
+
+
See https://fossies.org/dox/sox-14.4.2/structsox__encodinginfo__t.html
+
+
:ivar Optional[int] encoding: sox_encoding_t
+
:ivar Optional[int] bits_per_sample: bit depth
+
:ivar Optional[float] compression: Compression option
+
:ivar Any reverse_bytes:
+
:ivar Any reverse_nibbles:
+
:ivar Any reverse_bits:
+
:ivar Optional[bool] opposite_endian:
+
"""
+
def __init__(self,
+
encoding: Any = None,
+
bits_per_sample: Optional[int] = None,
+
compression: Optional[float] = None,
+
reverse_bytes: Any = None,
+
reverse_nibbles: Any = None,
+
reverse_bits: Any = None,
+
opposite_endian: Optional[bool] = None) -> None:
+
self.encoding = encoding
+
self.bits_per_sample = bits_per_sample
+
self.compression = compression
+
self.reverse_bytes = reverse_bytes
+
self.reverse_nibbles = reverse_nibbles
+
self.reverse_bits = reverse_bits
+
self.opposite_endian = opposite_endian
+
+
+_LOAD_DOCSTRING = r"""Loads an audio file from disk into a tensor
+
+Args:
+ filepath: Path to audio file
+
+ out: An optional output tensor to use instead of creating one. (Default: ``None``)
+
+ normalization: Optional normalization.
+ If boolean `True`, then output is divided by `1 << 31`.
+ Assuming the input is signed 32-bit audio, this normalizes to `[-1, 1]`.
+ If `float`, then output is divided by that number.
+ If `Callable`, then the output is passed as a paramete to the given function,
+ then the output is divided by the result. (Default: ``True``)
+
+ channels_first: Set channels first or length first in result. (Default: ``True``)
+
+ num_frames: Number of frames to load. 0 to load everything after the offset.
+ (Default: ``0``)
+
+ offset: Number of frames from the start of the file to begin data loading.
+ (Default: ``0``)
+
+ signalinfo: A sox_signalinfo_t type, which could be helpful if the
+ audio type cannot be automatically determined. (Default: ``None``)
+
+ encodinginfo: A sox_encodinginfo_t type, which could be set if the
+ audio type cannot be automatically determined. (Default: ``None``)
+
+ filetype: A filetype or extension to be set if sox cannot determine it
+ automatically. (Default: ``None``)
+
+Returns:
+ (Tensor, int): An output tensor of size `[C x L]` or `[L x C]` where
+ L is the number of audio frames and
+ C is the number of channels.
+ An integer which is the sample rate of the audio (as listed in the metadata of the file)
+
+Example
+ >>> data, sample_rate = torchaudio.load('foo.mp3')
+ >>> print(data.size())
+ torch.Size([2, 278756])
+ >>> print(sample_rate)
+ 44100
+ >>> data_vol_normalized, _ = torchaudio.load('foo.mp3', normalization=lambda x: torch.abs(x).max())
+ >>> print(data_vol_normalized.abs().max())
+ 1.
+"""
+
+
+_LOAD_WAV_DOCSTRING = r""" Loads a wave file.
+
+It assumes that the wav file uses 16 bit per sample that needs normalization by
+shifting the input right by 16 bits.
+
+Args:
+ filepath: Path to audio file
+
+Returns:
+ (Tensor, int): An output tensor of size `[C x L]` or `[L x C]` where L is the number
+ of audio frames and C is the number of channels. An integer which is the sample rate of the
+ audio (as listed in the metadata of the file)
+"""
+
+_SAVE_DOCSTRING = r"""Saves a Tensor on file as an audio file
+
+Args:
+ filepath: Path to audio file
+ src: An input 2D tensor of shape `[C x L]` or `[L x C]` where L is
+ the number of audio frames, C is the number of channels
+ sample_rate: An integer which is the sample rate of the
+ audio (as listed in the metadata of the file)
+ precision Bit precision (Default: ``16``)
+ channels_first (bool, optional): Set channels first or length first in result. (
+ Default: ``True``)
+"""
+
+
+_INFO_DOCSTRING = r"""Gets metadata from an audio file without loading the signal.
+
+Args:
+ filepath: Path to audio file
+
+Returns:
+ (sox_signalinfo_t, sox_encodinginfo_t): A si (sox_signalinfo_t) signal
+ info as a python object. An ei (sox_encodinginfo_t) encoding info
+
+Example
+ >>> si, ei = torchaudio.info('foo.wav')
+ >>> rate, channels, encoding = si.rate, si.channels, ei.encoding
+"""
+
+
+def _impl_load(func):
+ setattr(func, '__doc__', _LOAD_DOCSTRING)
+ return func
+
+
+def _impl_load_wav(func):
+ setattr(func, '__doc__', _LOAD_WAV_DOCSTRING)
+ return func
+
+
+def _impl_save(func):
+ setattr(func, '__doc__', _SAVE_DOCSTRING)
+ return func
+
+
+def _impl_info(func):
+ setattr(func, '__doc__', _INFO_DOCSTRING)
+ return func
+
+