npvcc2016 - Python loader of npVCC2016Corpus
npvcc2016 is a Python package for loader of npVCC2016 non-parallel speech corpus.
For machine learning, corpus/dataset is indispensable - but troublesome - part.
We need portable & flexible loader for streamline development.
npvcc2016 is the one!!
Demo
Python/PyTorch
pip install npvcc2016
from npvcc2016.PyTorch.dataset.waveform import NpVCC2016_wave
dataset = NpVCC2016(train=True, download=True)
for datum in dataset:
print("Yeah, data is acquired with only two line of code!!")
print(datum) # (datum, label) tuple provided
npvcc2016 transparently downloads corpus, structures the data and provides standarized datasets.
What you have to do is only instantiating the class!
APIs
Current npvcc2016 support PyTorch.
As interface, PyTorch's Dataset and PyTorch-Lightning's DataModule are provided.
npVCC2016 corpus is speech corpus, so we provide waveform dataset and spectrogram dataset for both interfaces.
- PyTorch
- (pure PyTorch) dataset
- waveform:
NpVCC2016_wave - spectrogram:
NpVCC2016_spec
- waveform:
- PyTorch-Lightning
- waveform:
NpVCC2016_wave_DataModule - spectrogram:
NpVCC2016_spec_DataModule
- waveform:
- (pure PyTorch) dataset
Dependency Notes
PyTorch version
PyTorch version: PyTorch v1.6 is working (We checked with v1.6.0).
For dependency resolution, we do NOT explicitly specify the compatible versions.
PyTorch have several distributions for various environment (e.g. compatible CUDA version.)
Unfortunately it make dependency version management complicated for dependency management system.
In our case, the system poetry cannot handle cuda variant string (e.g. torch>=1.6.0 cannot accept 1.6.0+cu101.)
In order to resolve this problem, we use torch==*, it is equal to no version specification.
Setup.py could resolve this problem (e.g. torchaudio's setup.py), but we will not bet our effort to this hacky method.
Metadata
Release files for npvcc2016 3.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| npvcc2016-3.0.0.tar.gz | 9.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| npvcc2016-3.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 22.7 kB
Release files / npvcc2016-3.0.0.tar.gz
| Download URL | npvcc2016-3.0.0.tar.gz |
|---|---|
| Size | 9.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
poetry/1.1.4 CPython/3.6.12 Linux/4.19.104-microsoft-standard
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Release files / npvcc2016-3.0.0-py3-none-any.whl
| Download URL | npvcc2016-3.0.0-py3-none-any.whl |
|---|---|
| Size | 13.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.4 CPython/3.6.12 Linux/4.19.104-microsoft-standard
|
Security for npvcc2016 3.0.0
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