Differences with torchaudio.datasets.LJSPEECH

torchaudio.datasets.LJSPEECH

class torchaudio.datasets.LJSPEECH(
    root: str,
    url: str = 'https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2',
    folder_in_archive: str = 'wavs',
    download: bool = False)

For more information, see torchaudio.datasets.LJSPEECH.

mindspore.dataset.LJSpeechDataset

class mindspore.dataset.LJSpeechDataset(
    dataset_dir,
    num_samples=None,
    num_parallel_workers=None,
    shuffle=None,
    sampler=None,
    num_shards=None,
    shard_id=None,
    cache=None)

For more information, see mindspore.dataset.LJSpeechDataset.

Differences

PyTorch: Read the LJSpeech dataset.

MindSpore: Read the LJSpeech dataset. Downloading dataset from web is not supported.

Categories	Subcategories	PyTorch	MindSpore	Difference
Parameter	Parameter1	root	dataset_dir	-
	Parameter2	url	-	Not supported by MindSpore
	Parameter3	folder_in_archive	-	Not supported by MindSpore
	Parameter4	download	-	Not supported by MindSpore
	Parameter5	-	num_samples	The number of images to be included in the dataset
	Parameter6	-	num_parallel_workers	Number of worker threads to read the data
	Parameter7	-	shuffle	Whether to perform shuffle on the dataset
	Parameter8	-	sampler	Object used to choose samples from the dataset
	Parameter9	-	num_shards	Number of shards that the dataset will be divided into
	Parameter10	-	shard_id	The shard ID within num_shards
	Parameter11	-	cache	Use tensor caching service to speed up dataset processing

Code Example

# PyTorch
import torchaudio.datasets as datasets
from torch.utils.data import DataLoader

root = "/path/to/dataset_directory/"
dataset = datasets.LJSPEECH(root, url='https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2')
dataloader = DataLoader(dataset)

# MindSpore
import mindspore.dataset as ds

# Download LJSpeech dataset files, unzip into the following structure
# .
# └── /path/to/dataset_directory/
#      ├── README
#      ├── metadata.csv
#      └── wavs
#          ├── LJ001-0001.wav
#          ├── LJ001-0002.wav
#          ├── LJ001-0003.wav
#          ├── LJ001-0004.wav
#          ├── LJ001-0005.wav
#          ├── LJ001-0006.wav
#          ├── LJ001-0007.wav
#          ├── LJ001-0008.wav
#           ...
#          ├── LJ050-0277.wav
#          └── LJ050-0278.wav
root = "/path/to/dataset_directory/"
ms_dataloader = ds.LJSpeechDataset(root)