pytorch dataset for nsynth data
- Free software: MIT license
- Documentation: https://pytorch-nsynth.readthedocs.io.
- install pytorch, scipy
- clone this repo: git clone https://github.com/kwon-young/pytorch-nsynth.git
- add module directory to PYTHONPATH: export PYTHONPATH=pytorch-nsynth_dir:$PYTHONPATH
- download tar.gz files from https://magenta.tensorflow.org/datasets/nsynth
- unpack archive
import torch.utils.data as data
import torchvision.transforms as transforms
from pytorch_nsynth.nsynth import NSynth
# audio samples are loaded as an int16 numpy array
# rescale intensity range as float [-1, 1]
toFloat = transforms.Lambda(lambda x: x / np.iinfo(np.int16).max)
# use instrument_family and instrument_source as classification targets
dataset = NSynth(
"../nsynth-test",
transform=toFloat,
blacklist_pattern=["string"], # blacklist string instrument
categorical_field_list=["instrument_family", "instrument_source"])
loader = data.DataLoader(dataset, batch_size=32, shuffle=True)
for samples, instrument_family_target, instrument_source_target, targets \
in loader:
print(samples.shape, instrument_family_target.shape,
instrument_source_target.shape)
print(torch.min(samples), torch.max(samples))This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.