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Unverified Commit 4d52106f authored by moto's avatar moto Committed by GitHub
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Move all SoX I/O functions to _sox_backend for better modularity (#695)

parent e5eb4857
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Showing with 196 additions and 191 deletions
torchaudio/__init__.py
View file @ 4d52106f
import os.path
from pathlib import Path
from typing import Any, Callable, Optional, Tuple, Union
import torch
from torch import Tensor
from torchaudio import (
compliance,
......@@ -16,6 +14,14 @@ from torchaudio._backend import (
get_audio_backend,
set_audio_backend,
)
from torchaudio._sox_backend import (
save_encinfo,
sox_signalinfo_t,
sox_encodinginfo_t,
get_sox_option_t,
get_sox_encoding_t,
get_sox_bool,
)
from torchaudio._soundfile_backend import SignalInfo, EncodingInfo
from torchaudio._internal import (
module_utils as _mod_utils,
......@@ -130,77 +136,6 @@ def save(filepath: str, src: Tensor, sample_rate: int, precision: int = 16, chan
)
@_mod_utils.requires_module('torchaudio._torchaudio')
def save_encinfo(filepath: str,
src: Tensor,
channels_first: bool = True,
signalinfo: Optional[SignalInfo] = None,
encodinginfo: Optional[EncodingInfo] = None,
filetype: Optional[str] = None) -> None:
r"""Saves a tensor of an audio signal to disk as a standard format like mp3, wav, etc.
Args:
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)
"""
ch_idx, len_idx = (0, 1) if channels_first else (1, 0)
# check if save directory exists
abs_dirpath = os.path.dirname(os.path.abspath(filepath))
if not os.path.isdir(abs_dirpath):
raise OSError("Directory does not exist: {}".format(abs_dirpath))
# check that src is a CPU tensor
_misc_ops.check_input(src)
# Check/Fix shape of source data
if src.dim() == 1:
# 1d tensors as assumed to be mono signals
src.unsqueeze_(ch_idx)
elif src.dim() > 2 or src.size(ch_idx) > 16:
# assumes num_channels < 16
raise ValueError(
"Expected format where C < 16, but found {}".format(src.size()))
# sox stores the sample rate as a float, though practically sample rates are almost always integers
# convert integers to floats
if signalinfo:
if signalinfo.rate and not isinstance(signalinfo.rate, float):
if float(signalinfo.rate) == signalinfo.rate:
signalinfo.rate = float(signalinfo.rate)
else:
raise TypeError('Sample rate should be a float or int')
# check if the bit precision (i.e. bits per sample) is an integer
if signalinfo.precision and not isinstance(signalinfo.precision, int):
if int(signalinfo.precision) == signalinfo.precision:
signalinfo.precision = int(signalinfo.precision)
else:
raise TypeError('Bit precision should be an integer')
# programs such as librosa normalize the signal, unnormalize if detected
if src.min() >= -1.0 and src.max() <= 1.0:
src = src * (1 << 31)
src = src.long()
# set filetype and allow for files with no extensions
extension = os.path.splitext(filepath)[1]
filetype = extension[1:] if len(extension) > 0 else filetype
# transpose from C x L -> L x C
if channels_first:
src = src.transpose(1, 0)
# save data to file
src = src.contiguous()
_torchaudio.write_audio_file(filepath, src, signalinfo, encodinginfo, filetype)
def info(filepath: str) -> Tuple[SignalInfo, EncodingInfo]:
r"""Gets metadata from an audio file without loading the signal.
......@@ -216,117 +151,3 @@ def info(filepath: str) -> Tuple[SignalInfo, EncodingInfo]:
>>> rate, channels, encoding = si.rate, si.channels, ei.encoding
"""
return _get_audio_backend_module().info(filepath)
@_mod_utils.requires_module('torchaudio._torchaudio')
def sox_signalinfo_t() -> SignalInfo:
r"""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
"""
return _torchaudio.sox_signalinfo_t()
@_mod_utils.requires_module('torchaudio._torchaudio')
def sox_encodinginfo_t() -> EncodingInfo:
r"""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)
"""
ei = _torchaudio.sox_encodinginfo_t()
sdo = get_sox_option_t(2) # sox_default_option
ei.reverse_bytes = sdo
ei.reverse_nibbles = sdo
ei.reverse_bits = sdo
return ei
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_encoding_t(i: int = None) -> EncodingInfo:
r"""Get enum of sox_encoding_t for sox encodings.
Args:
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:
sox_encoding_t: A sox_encoding_t type for output encoding
"""
if i is None:
# one can see all possible values using the .__members__ attribute
return _torchaudio.sox_encoding_t
else:
return _torchaudio.sox_encoding_t(i)
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_option_t(i: int = 2) -> Any:
r"""Get enum of sox_option_t for sox encodinginfo options.
Args:
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:
sox_option_t: A sox_option_t type
"""
if i is None:
return _torchaudio.sox_option_t
else:
return _torchaudio.sox_option_t(i)
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_bool(i: int = 0) -> Any:
r"""Get enum of sox_bool for sox encodinginfo options.
Args:
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:
sox_bool: A sox_bool type
"""
if i is None:
return _torchaudio.sox_bool
else:
return _torchaudio.sox_bool(i)
torchaudio/_sox_backend.py
View file @ 4d52106f
import os.path
from typing import Optional, Tuple
from typing import Any, Optional, Tuple
import torch
from torch import Tensor
import torchaudio
from torchaudio._internal import (
module_utils as _mod_utils,
misc_ops as _misc_ops,
......@@ -65,16 +64,201 @@ def load(filepath: str,
def save(filepath: str, src: Tensor, sample_rate: int, precision: int = 16, channels_first: bool = True) -> None:
r"""See torchaudio.save"""
si = torchaudio.sox_signalinfo_t()
si = sox_signalinfo_t()
ch_idx = 0 if channels_first else 1
si.rate = sample_rate
si.channels = 1 if src.dim() == 1 else src.size(ch_idx)
si.length = src.numel()
si.precision = precision
return torchaudio.save_encinfo(filepath, src, channels_first, si)
return save_encinfo(filepath, src, channels_first, si)
@_mod_utils.requires_module('torchaudio._torchaudio')
def info(filepath: str) -> Tuple[SignalInfo, EncodingInfo]:
r"""See torchaudio.info"""
return _torchaudio.get_info(filepath)
@_mod_utils.requires_module('torchaudio._torchaudio')
def save_encinfo(filepath: str,
src: Tensor,
channels_first: bool = True,
signalinfo: Optional[SignalInfo] = None,
encodinginfo: Optional[EncodingInfo] = None,
filetype: Optional[str] = None) -> None:
r"""Saves a tensor of an audio signal to disk as a standard format like mp3, wav, etc.
Args:
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)
"""
ch_idx, len_idx = (0, 1) if channels_first else (1, 0)
# check if save directory exists
abs_dirpath = os.path.dirname(os.path.abspath(filepath))
if not os.path.isdir(abs_dirpath):
raise OSError("Directory does not exist: {}".format(abs_dirpath))
# check that src is a CPU tensor
_misc_ops.check_input(src)
# Check/Fix shape of source data
if src.dim() == 1:
# 1d tensors as assumed to be mono signals
src.unsqueeze_(ch_idx)
elif src.dim() > 2 or src.size(ch_idx) > 16:
# assumes num_channels < 16
raise ValueError(
"Expected format where C < 16, but found {}".format(src.size()))
# sox stores the sample rate as a float, though practically sample rates are almost always integers
# convert integers to floats
if signalinfo:
if signalinfo.rate and not isinstance(signalinfo.rate, float):
if float(signalinfo.rate) == signalinfo.rate:
signalinfo.rate = float(signalinfo.rate)
else:
raise TypeError('Sample rate should be a float or int')
# check if the bit precision (i.e. bits per sample) is an integer
if signalinfo.precision and not isinstance(signalinfo.precision, int):
if int(signalinfo.precision) == signalinfo.precision:
signalinfo.precision = int(signalinfo.precision)
else:
raise TypeError('Bit precision should be an integer')
# programs such as librosa normalize the signal, unnormalize if detected
if src.min() >= -1.0 and src.max() <= 1.0:
src = src * (1 << 31)
src = src.long()
# set filetype and allow for files with no extensions
extension = os.path.splitext(filepath)[1]
filetype = extension[1:] if len(extension) > 0 else filetype
# transpose from C x L -> L x C
if channels_first:
src = src.transpose(1, 0)
# save data to file
src = src.contiguous()
_torchaudio.write_audio_file(filepath, src, signalinfo, encodinginfo, filetype)
@_mod_utils.requires_module('torchaudio._torchaudio')
def sox_signalinfo_t() -> SignalInfo:
r"""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
"""
return _torchaudio.sox_signalinfo_t()
@_mod_utils.requires_module('torchaudio._torchaudio')
def sox_encodinginfo_t() -> EncodingInfo:
r"""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)
"""
ei = _torchaudio.sox_encodinginfo_t()
sdo = get_sox_option_t(2) # sox_default_option
ei.reverse_bytes = sdo
ei.reverse_nibbles = sdo
ei.reverse_bits = sdo
return ei
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_encoding_t(i: int = None) -> EncodingInfo:
r"""Get enum of sox_encoding_t for sox encodings.
Args:
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:
sox_encoding_t: A sox_encoding_t type for output encoding
"""
if i is None:
# one can see all possible values using the .__members__ attribute
return _torchaudio.sox_encoding_t
else:
return _torchaudio.sox_encoding_t(i)
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_option_t(i: int = 2) -> Any:
r"""Get enum of sox_option_t for sox encodinginfo options.
Args:
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:
sox_option_t: A sox_option_t type
"""
if i is None:
return _torchaudio.sox_option_t
else:
return _torchaudio.sox_option_t(i)
@_mod_utils.requires_module('torchaudio._torchaudio')
def get_sox_bool(i: int = 0) -> Any:
r"""Get enum of sox_bool for sox encodinginfo options.
Args:
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:
sox_bool: A sox_bool type
"""
if i is None:
return _torchaudio.sox_bool
else:
return _torchaudio.sox_bool(i)
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