pull/3968/head
zxcd 8 months ago
parent c873918625
commit 720895c6ab

@ -202,9 +202,9 @@ class AudioDataset:
Examples Examples
-------- --------
>>> from audio.audiotools.data.datasets import AudioLoader >>> from paddlespeech.audiotools.data.datasets import AudioLoader
>>> from audio.audiotools.data.datasets import AudioDataset >>> from paddlespeech.audiotools.data.datasets import AudioDataset
>>> from audio.audiotools import transforms as tfm >>> from paddlespeech.audiotools import transforms as tfm
>>> import numpy as np >>> import numpy as np
>>> >>>
>>> loaders = [ >>> loaders = [
@ -237,9 +237,9 @@ class AudioDataset:
Below is an example of how one could load MUSDB multitrack data: Below is an example of how one could load MUSDB multitrack data:
>>> from audio import audiotools as at >>> from paddlespeech import audiotools as at
>>> from pathlib import Path >>> from pathlib import Path
>>> from audio.audiotools import transforms as tfm >>> from paddlespeech.audiotools import transforms as tfm
>>> import numpy as np >>> import numpy as np
>>> import torch >>> import torch
>>> >>>
@ -296,9 +296,9 @@ class AudioDataset:
Similarly, here's example code for loading Slakh data: Similarly, here's example code for loading Slakh data:
>>> from audio import audiotools as at >>> from paddlespeech import audiotools as at
>>> from pathlib import Path >>> from pathlib import Path
>>> from audio.audiotools import transforms as tfm >>> from paddlespeech.audiotools import transforms as tfm
>>> import numpy as np >>> import numpy as np
>>> import torch >>> import torch
>>> import glob >>> import glob

@ -37,7 +37,7 @@ def create_csv(audio_files: list,
You can produce a CSV file from a directory of audio files via: You can produce a CSV file from a directory of audio files via:
>>> from audio import audiotools >>> from paddlespeech import audiotools
>>> directory = ... >>> directory = ...
>>> audio_files = audiotools.util.find_audio(directory) >>> audio_files = audiotools.util.find_audio(directory)
>>> output_path = "train.csv" >>> output_path = "train.csv"

@ -6,7 +6,7 @@ import typing
import paddle import paddle
from audio.audiotools.core import AudioSignal from paddlespeech.audiotools.core import AudioSignal
def audio_table( def audio_table(

@ -197,7 +197,7 @@ def test_compose_filtering():
for _ in range(10): for _ in range(10):
_muls = np.random.choice(muls, size=s, replace=False).tolist() _muls = np.random.choice(muls, size=s, replace=False).tolist()
full_mul = np.prod(_muls) full_mul = np.prod(_muls)
with transform.filter(* [str(x) for x in _muls]): with transform.filter(*[str(x) for x in _muls]):
output = transform(signal.clone(), **kwargs) output = transform(signal.clone(), **kwargs)
expected_output = signal.audio_data * full_mul expected_output = signal.audio_data * full_mul

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