torchaudio.backend¶

Overview¶

torchaudio.backend module provides implementations for audio file I/O functionalities, which are torchaudio.info, torchaudio.load, torchaudio.load_wav and torchaudio.save.

There are currently four implementations available.

“sox” (deprecated, default on Linux/macOS)
“sox_io” (default on Linux/macOS from the 0.8.0 release)
“soundfile” - legacy interface (deprecated, default on Windows)
“soundfile” - new interface (default on Windows from the 0.8.0 release)

On Windows, only the "soundfile" backend (with both interfaces) are available. It is recommended to use the new interface as the legacy interface is deprecated.

On Linux/macOS, please use "sox_io" backend. The use of "sox" backend is strongly discouraged as it cannot correctly handle formats other than 16-bit integer WAV. See #726 for the detail.

Note

Instead of calling functions in torchaudio.backend directly, please use torchaudio.info, torchaudio.load, torchaudio.load_wav and torchaudio.save with proper backend set with torchaudio.set_audio_backend().

Availability¶

"sox" and "sox_io" backends require C++ extension module, which is included in Linux/macOS binary distributions. These backends are not available on Windows.

"soundfile" backend requires SoundFile. Please refer to the SoundFile documentation for the installation.

Changes in default backend and deprecation¶

Backend module is going through a major overhaul. The following table summarizes the timeline for the changes and deprecations.

Backend

0.7.0

0.8.0

0.9.0

"sox" (deprecated)

Default on Linux/macOS

Available

Removed

"sox_io"

Available

Default on Linx/macOS

Default on Linux/macOS

"soundfile" (legacy interface, deprecated)

Default on Windows

Available

Removed

"soundfile" (new interface)

Available

Default on Windows

Default on Windows

The default backend for Linux/macOS will be changed from "sox" to "sox_io" in 0.8.0 release.
The "sox" backend will be removed in the 0.9.0 release.
Starting from the 0.8.0 release, "soundfile" backend will use the new interface, which has the same interface as "sox_io" backend. The legacy interface will be removed in the 0.9.0 release.

Common Data Structure¶

Structures used to report the metadata of audio files.

AudioMetaData¶

class torchaudio.backend.common.AudioMetaData(sample_rate: int, num_frames: int, num_channels: int)[source]¶

Return type of torchaudio.info function.

This class is used by “sox_io” backend and “soundfile” backend with the new interface.

Variables

sample_rate (int) – Sample rate
num_frames (int) – The number of frames
num_channels (int) – The number of channels

SignalInfo (Deprecated)¶

class torchaudio.backend.common.SignalInfo[source]¶

One of return types of torchaudio.info functions.

This class is used by “sox” backend (deprecated) and “soundfile” backend with the legacy interface (deprecated).

See https://fossies.org/dox/sox-14.4.2/structsox__signalinfo__t.html

Variables

channels (Optional[int]) – The number of channels
rate (Optional[float]) – Sampleing rate
precision (Optional[int]) – Bit depth
length (Optional[int]) – For sox backend, the number of samples. (frames * channels). For soundfile backend, the number of frames.

EncodingInfo (Deprecated)¶

class torchaudio.backend.common.EncodingInfo[source]¶

One of return types of torchaudio.info functions.

This class is used by “sox” backend (deprecated) and “soundfile” backend with the legacy interface (deprecated).

See https://fossies.org/dox/sox-14.4.2/structsox__encodinginfo__t.html

Variables

encoding (Optional[int]) – sox_encoding_t
bits_per_sample (Optional[int]) – bit depth
compression (Optional[float]) – Compression option
reverse_bytes (Any) –
reverse_nibbles (Any) –
reverse_bits (Any) –
opposite_endian (Optional[bool]) –

Sox Backend (Deprecated)¶

The "sox" backend is available on Linux/macOS and not available on Windows. This backend is currently the default when available, but is deprecated and will be removed in 0.9.0 release.

You can switch from another backend to sox backend with the following;

torchaudio.set_audio_backend("sox")

info¶

torchaudio.backend.sox_backend.info(filepath: str) → Tuple[torchaudio.backend.common.SignalInfo, torchaudio.backend.common.EncodingInfo][source]¶

Gets metadata from an audio file without loading the signal.

Parameters

filepath – Path to audio file

Returns

A si (sox_signalinfo_t) signal: info as a python object. An ei (sox_encodinginfo_t) encoding info

Return type

(sox_signalinfo_t, sox_encodinginfo_t)

Example

>>> si, ei = torchaudio.info('foo.wav')
>>> rate, channels, encoding = si.rate, si.channels, ei.encoding

load¶

torchaudio.backend.sox_backend.load(filepath: str, out: Optional[torch.Tensor] = None, normalization: bool = True, channels_first: bool = True, num_frames: int = 0, offset: int = 0, signalinfo: torchaudio.backend.common.SignalInfo = None, encodinginfo: torchaudio.backend.common.EncodingInfo = None, filetype: Optional[str] = None) → Tuple[torch.Tensor, int][source]¶

Loads an audio file from disk into a tensor

Parameters

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

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)

Return type

(Tensor, int)

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.

torchaudio.backend.sox_backend.load_wav(filepath, **kwargs)[source]¶

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.

Parameters

filepath – Path to audio file

Returns

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)

Return type

(Tensor, int)

save¶

torchaudio.backend.sox_backend.save(filepath: str, src: torch.Tensor, sample_rate: int, precision: int = 16, channels_first: bool = True) → None[source]¶

Saves a Tensor on file as an audio file

Parameters

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)
Bit precision (Default (precision) – 16)
channels_first (bool, optional) – Set channels first or length first in result. ( Default: True)

others¶

torchaudio.backend.sox_backend.get_sox_bool(i: int = 0) → Any[source]¶

Get enum of sox_bool for sox encodinginfo options.

Parameters: i (int, optional) – Choose type or get a dict with all possible options use __members__ to see all options when not specified. (Default: sox_false or 0)
Returns: A sox_bool type
Return type: sox_bool

torchaudio.backend.sox_backend.get_sox_encoding_t(i: int = None) → torchaudio.backend.common.EncodingInfo[source]¶

Get enum of sox_encoding_t for sox encodings.

Parameters: i (int, optional) – Choose type or get a dict with all possible options use __members__ to see all options when not specified. (Default: None)
Returns: A sox_encoding_t type for output encoding
Return type: sox_encoding_t

torchaudio.backend.sox_backend.get_sox_option_t(i: int = 2) → Any[source]¶

Get enum of sox_option_t for sox encodinginfo options.

Parameters: i (int, optional) – Choose type or get a dict with all possible options use __members__ to see all options when not specified. (Default: sox_option_default or 2)
Returns: A sox_option_t type
Return type: sox_option_t

torchaudio.backend.sox_backend.save_encinfo(filepath: str, src: torch.Tensor, channels_first: bool = True, signalinfo: Optional[torchaudio.backend.common.SignalInfo] = None, encodinginfo: Optional[torchaudio.backend.common.EncodingInfo] = None, filetype: Optional[str] = None) → None[source]¶

Saves a tensor of an audio signal to disk as a standard format like mp3, wav, etc.

Parameters

filepath (str) – Path to audio file
src (Tensor) – 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
channels_first (bool, optional) – Set channels first or length first in result. (Default: True)
signalinfo (sox_signalinfo_t, optional) – A sox_signalinfo_t type, which could be helpful if the audio type cannot be automatically determined (Default: None).
encodinginfo (sox_encodinginfo_t, optional) – A sox_encodinginfo_t type, which could be set if the audio type cannot be automatically determined (Default: None).
filetype (str, optional) – A filetype or extension to be set if sox cannot determine it automatically. (Default: None)

Example

>>> data, sample_rate = torchaudio.load('foo.mp3')
>>> torchaudio.save('foo.wav', data, sample_rate)

torchaudio.backend.sox_backend.sox_encodinginfo_t() → torchaudio.backend.common.EncodingInfo[source]¶

Create a sox_encodinginfo_t object. This object can be used to set the encoding type, bit precision, compression factor, reverse bytes, reverse nibbles, reverse bits and endianness. This can be used in an effects chain to encode the final output or to save a file with a specific encoding. For example, one could use the sox ulaw encoding to do 8-bit ulaw encoding. Note in a tensor output the result will be a 32-bit number, but number of unique values will be determined by the bit precision.

Returns: sox_encodinginfo_t(object)

encoding (sox_encoding_t), output encoding
bits_per_sample (int), bit precision, same as precision in sox_signalinfo_t
compression (float), compression for lossy formats, 0.0 for default compression
reverse_bytes (sox_option_t), reverse bytes, use sox_option_default
reverse_nibbles (sox_option_t), reverse nibbles, use sox_option_default
reverse_bits (sox_option_t), reverse bytes, use sox_option_default
opposite_endian (sox_bool), change endianness, use sox_false

Example

>>> ei = torchaudio.sox_encodinginfo_t()
>>> ei.encoding = torchaudio.get_sox_encoding_t(1)
>>> ei.bits_per_sample = 16
>>> ei.compression = 0
>>> ei.reverse_bytes = torchaudio.get_sox_option_t(2)
>>> ei.reverse_nibbles = torchaudio.get_sox_option_t(2)
>>> ei.reverse_bits = torchaudio.get_sox_option_t(2)
>>> ei.opposite_endian = torchaudio.get_sox_bool(0)

torchaudio.backend.sox_backend.sox_signalinfo_t() → torchaudio.backend.common.SignalInfo[source]¶

Create a sox_signalinfo_t object. This object can be used to set the sample rate, number of channels, length, bit precision and headroom multiplier primarily for effects

Returns: sox_signalinfo_t(object)

rate (float), sample rate as a float, practically will likely be an integer float
channel (int), number of audio channels
precision (int), bit precision
length (int), length of audio in samples * channels, 0 for unspecified and -1 for unknown
mult (float, optional), headroom multiplier for effects and None for no multiplier

Example

>>> si = torchaudio.sox_signalinfo_t()
>>> si.channels = 1
>>> si.rate = 16000.
>>> si.precision = 16
>>> si.length = 0

Sox IO Backend¶

The "sox_io" backend is available on Linux/macOS and not available on Windows. This backend is recommended over the "sox" backend, and will become the default in the 0.8.0 release.

I/O functions of this backend support TorchScript.

You can switch from another backend to the sox_io backend with the following;

torchaudio.set_audio_backend("sox_io")

info¶

torchaudio.backend.sox_io_backend.info(filepath: str) → torchaudio.backend.common.AudioMetaData[source]¶

Get signal information of an audio file.

Parameters: filepath (str or pathlib.Path) – Path to audio file. This function also handles pathlib.Path objects, but is annotated as str for TorchScript compatibility.
Returns: Metadata of the given audio.
Return type: AudioMetaData

load¶

torchaudio.backend.sox_io_backend.load(filepath: str, frame_offset: int = 0, num_frames: int = -1, normalize: bool = True, channels_first: bool = True) → Tuple[torch.Tensor, int][source]¶

Load audio data from file.

Note

This function can handle all the codecs that underlying libsox can handle, however it is tested on the following formats;

WAV
- 32-bit floating-point
- 32-bit signed integer
- 16-bit signed integer
- 8-bit unsigned integer
MP3
FLAC
OGG/VORBIS
OPUS
SPHERE

To load MP3, FLAC, OGG/VORBIS, OPUS and other codecs libsox does not handle natively, your installation of torchaudio has to be linked to libsox and corresponding codec libraries such as libmad or libmp3lame etc.

By default (normalize=True, channels_first=True), this function returns Tensor with float32 dtype and the shape of [channel, time]. The samples are normalized to fit in the range of [-1.0, 1.0].

When the input format is WAV with integer type, such as 32-bit signed integer, 16-bit signed integer and 8-bit unsigned integer (24-bit signed integer is not supported), by providing normalize=False, this function can return integer Tensor, where the samples are expressed within the whole range of the corresponding dtype, that is, int32 tensor for 32-bit signed PCM, int16 for 16-bit signed PCM and uint8 for 8-bit unsigned PCM.

normalize parameter has no effect on 32-bit floating-point WAV and other formats, such as flac and mp3. For these formats, this function always returns float32 Tensor with values normalized to [-1.0, 1.0].

Parameters

filepath (str or pathlib.Path) – Path to audio file. This function also handles pathlib.Path objects, but is annotated as str for TorchScript compiler compatibility.
frame_offset (int) – Number of frames to skip before start reading data.
num_frames (int) – Maximum number of frames to read. -1 reads all the remaining samples, starting from frame_offset. This function may return the less number of frames if there is not enough frames in the given file.
normalize (bool) – When True, this function always return float32, and sample values are normalized to [-1.0, 1.0]. If input file is integer WAV, giving False will change the resulting Tensor type to integer type. This argument has no effect for formats other than integer WAV type.
channels_first (bool) – When True, the returned Tensor has dimension [channel, time]. Otherwise, the returned Tensor’s dimension is [time, channel].

Returns

If the input file has integer wav format and normalization is off, then it has integer type, else float32 type. If channels_first=True, it has [channel, time] else [time, channel].

Return type

torch.Tensor

torchaudio.backend.sox_io_backend.load_wav(filepath: str, frame_offset: int = 0, num_frames: int = -1, channels_first: bool = True) → Tuple[torch.Tensor, int][source]¶

Load wave file.

This function is defined only for the purpose of compatibility against other backend for simple usecases, such as torchaudio.load_wav(filepath). The implementation is same as load().

save¶

torchaudio.backend.sox_io_backend.save(filepath: str, src: torch.Tensor, sample_rate: int, channels_first: bool = True, compression: Optional[float] = None)[source]¶

Save audio data to file.

Note

Supported formats are;

WAV
- 32-bit floating-point
- 32-bit signed integer
- 16-bit signed integer
- 8-bit unsigned integer
MP3
FLAC
OGG/VORBIS
SPHERE

To save MP3, FLAC, OGG/VORBIS, and other codecs libsox does not handle natively, your installation of torchaudio has to be linked to libsox and corresponding codec libraries such as libmad or libmp3lame etc.

Parameters

filepath (str or pathlib.Path) – Path to save file. This function also handles pathlib.Path objects, but is annotated as str for TorchScript compiler compatibility.
tensor (torch.Tensor) – Audio data to save. must be 2D tensor.
sample_rate (int) – sampling rate
channels_first (bool) – If True, the given tensor is interpreted as [channel, time], otherwise [time, channel].
compression (Optional[float]) –
Used for formats other than WAV. This corresponds to -C option of sox command.
- MP3: Either bitrate (in kbps) with quality factor, such as 128.2, or
  
  VBR encoding with quality factor such as -4.2. Default: -4.5.
- FLAC: compression level. Whole number from 0 to 8.
  
  8 is default and highest compression.
- OGG/VORBIS: number from -1 to 10; -1 is the highest compression
  
  and lowest quality. Default: 3.
See the detail at http://sox.sourceforge.net/soxformat.html.

Soundfile Backend¶

The "soundfile" backend is available when SoundFile is installed. This backend is the default on Windows.

The "soundfile" backend has two interfaces, legacy and new.

In the 0.7.0 release, the legacy interface is used by default when switching to the "soundfile" backend.
In the 0.8.0 release, the new interface will become the default.
In the 0.9.0 release, the legacy interface will be removed.

To change the interface, set torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE flag before switching the backend.

torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE = True
torchaudio.set_audio_backend("soundfile")  # The legacy interface

torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE = False
torchaudio.set_audio_backend("soundfile")  # The new interface

Legacy Interface (Deprecated)¶

"soundfile" backend with legacy interface is currently the default on Windows, however this interface is deprecated and will be removed in the 0.9.0 release.

To switch to this backend/interface, set torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE flag before switching the backend.

torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE = True
torchaudio.set_audio_backend("soundfile")  # The legacy interface

info¶

torchaudio.backend.soundfile_backend.info(filepath: str) → Tuple[torchaudio.backend.common.SignalInfo, torchaudio.backend.common.EncodingInfo][source]¶

Gets metadata from an audio file without loading the signal.

Parameters

filepath – Path to audio file

Returns

A si (sox_signalinfo_t) signal: info as a python object. An ei (sox_encodinginfo_t) encoding info

Return type

(sox_signalinfo_t, sox_encodinginfo_t)

Example

>>> si, ei = torchaudio.info('foo.wav')
>>> rate, channels, encoding = si.rate, si.channels, ei.encoding

load¶

torchaudio.backend.soundfile_backend.load(filepath: str, out: Optional[torch.Tensor] = None, normalization: Optional[bool] = True, channels_first: Optional[bool] = True, num_frames: int = 0, offset: int = 0, signalinfo: torchaudio.backend.common.SignalInfo = None, encodinginfo: torchaudio.backend.common.EncodingInfo = None, filetype: Optional[str] = None) → Tuple[torch.Tensor, int][source]¶

Loads an audio file from disk into a tensor

Parameters

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

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)

Return type

(Tensor, int)

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.

torchaudio.backend.soundfile_backend.load_wav(filepath, **kwargs)[source]¶

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.

Parameters

filepath – Path to audio file

Returns

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)

Return type

(Tensor, int)

save¶

torchaudio.backend.soundfile_backend.save(filepath: str, src: torch.Tensor, sample_rate: int, precision: int = 16, channels_first: bool = True) → None[source]¶

Saves a Tensor on file as an audio file

Parameters

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)
Bit precision (Default (precision) – 16)
channels_first (bool, optional) – Set channels first or length first in result. ( Default: True)

New Interface¶

The "soundfile" backend with new interface will become the default in the 0.8.0 release.

To switch to this backend/interface, set torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE flag before switching the backend.

torchaudio.USE_SOUNDFILE_LEGACY_INTERFACE = False
torchaudio.set_audio_backend("soundfile")  # The new interface

info¶

torchaudio.backend._soundfile_backend.info(filepath: str) → torchaudio.backend.common.AudioMetaData[source]¶

Get signal information of an audio file.

Parameters: filepath (str or pathlib.Path) – Path to audio file. This functionalso handles pathlib.Path objects, but is annotated as str for the consistency with “sox_io” backend, which has a restriction on type annotation for TorchScript compiler compatiblity.
Returns: meta data of the given audio.
Return type: AudioMetaData

load¶

torchaudio.backend._soundfile_backend.load(filepath: str, frame_offset: int = 0, num_frames: int = -1, normalize: bool = True, channels_first: bool = True) → Tuple[torch.Tensor, int][source]¶

Load audio data from file.

Note

The formats this function can handle depend on the soundfile installation. This function is tested on the following formats;

WAV
- 32-bit floating-point
- 32-bit signed integer
- 16-bit signed integer
- 8-bit unsigned integer
FLAC
OGG/VORBIS
SPHERE

By default (normalize=True, channels_first=True), this function returns Tensor with float32 dtype and the shape of [channel, time]. The samples are normalized to fit in the range of [-1.0, 1.0].

When the input format is WAV with integer type, such as 32-bit signed integer, 16-bit signed integer and 8-bit unsigned integer (24-bit signed integer is not supported), by providing normalize=False, this function can return integer Tensor, where the samples are expressed within the whole range of the corresponding dtype, that is, int32 tensor for 32-bit signed PCM, int16 for 16-bit signed PCM and uint8 for 8-bit unsigned PCM.

normalize parameter has no effect on 32-bit floating-point WAV and other formats, such as flac and mp3. For these formats, this function always returns float32 Tensor with values normalized to [-1.0, 1.0].

Parameters

filepath (str or pathlib.Path) – Path to audio file. This functionalso handles pathlib.Path objects, but is annotated as str for the consistency with “sox_io” backend, which has a restriction on type annotation for TorchScript compiler compatiblity.
frame_offset (int) – Number of frames to skip before start reading data.
num_frames (int) – Maximum number of frames to read. -1 reads all the remaining samples, starting from frame_offset. This function may return the less number of frames if there is not enough frames in the given file.
normalize (bool) – When True, this function always return float32, and sample values are normalized to [-1.0, 1.0]. If input file is integer WAV, giving False will change the resulting Tensor type to integer type. This argument has no effect for formats other than integer WAV type.
channels_first (bool) – When True, the returned Tensor has dimension [channel, time]. Otherwise, the returned Tensor’s dimension is [time, channel].

Returns

If the input file has integer wav format and normalization is off, then it has integer type, else float32 type. If channels_first=True, it has [channel, time] else [time, channel].

Return type

torch.Tensor

torchaudio.backend._soundfile_backend.load_wav(filepath: str, frame_offset: int = 0, num_frames: int = -1, channels_first: bool = True) → Tuple[torch.Tensor, int][source]¶

Load wave file.

This function is defined only for the purpose of compatibility against other backend for simple usecases, such as torchaudio.load_wav(filepath). The implementation is same as load().

save¶

torchaudio.backend._soundfile_backend.save(filepath: str, src: torch.Tensor, sample_rate: int, channels_first: bool = True, compression: Optional[float] = None)[source]¶

Save audio data to file.

Note

The formats this function can handle depend on the soundfile installation. This function is tested on the following formats;

WAV
- 32-bit floating-point
- 32-bit signed integer
- 16-bit signed integer
- 8-bit unsigned integer
FLAC
OGG/VORBIS
SPHERE

Parameters

filepath (str or pathlib.Path) – Path to audio file. This functionalso handles pathlib.Path objects, but is annotated as str for the consistency with “sox_io” backend, which has a restriction on type annotation for TorchScript compiler compatiblity.
tensor (torch.Tensor) – Audio data to save. must be 2D tensor.
sample_rate (int) – sampling rate
channels_first (bool) – If True, the given tensor is interpreted as [channel, time], otherwise [time, channel].
compression (Optional[float]) – Not used. It is here only for interface compatibility reson with “sox_io” backend.

torchaudio.backend¶

Overview¶

Availability¶

Changes in default backend and deprecation¶

Common Data Structure¶

AudioMetaData¶

SignalInfo (Deprecated)¶

EncodingInfo (Deprecated)¶

Sox Backend (Deprecated)¶

info¶

load¶

save¶

others¶

Sox IO Backend¶

info¶

load¶

save¶

Soundfile Backend¶

Legacy Interface (Deprecated)¶

info¶

load¶

save¶

New Interface¶

info¶

load¶

save¶

Docs

Tutorials

Resources

Backend	0.7.0	0.8.0	0.9.0
`"sox"` (deprecated)	Default on Linux/macOS	Available	Removed
`"sox_io"`	Available	Default on Linx/macOS	Default on Linux/macOS
`"soundfile"` (legacy interface, deprecated)	Default on Windows	Available	Removed
`"soundfile"` (new interface)	Available	Default on Windows	Default on Windows