Differences with torchaudio.datasets.GTZAN

torchaudio.datasets.GTZAN

class torchaudio.datasets.GTZAN(
    root: str,
    url: str = 'http://opihi.cs.uvic.ca/sound/genres.tar.gz',
    folder_in_archive: str = 'genres',
    download: bool = False,
    subset: str = None)

For more information, see torchaudio.datasets.GTZAN.

mindspore.dataset.GTZANDataset

class mindspore.dataset.GTZANDataset(
    dataset_dir,
    usage=None,
    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.GTZANDataset.

Differences

PyTorch: Read the GTZAN dataset.

MindSpore: Read the GTZAN dataset. Download 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	subset	usage	-
	Parameter6	-	num_samples	The number of images to be included in the dataset
	Parameter7	-	num_parallel_workers	Number of worker threads to read the data
	Parameter8	-	shuffle	Whether to perform shuffle on the dataset
	Parameter9	-	sampler	Object used to choose samples from the dataset
	Parameter10	-	num_shards	Number of shards that the dataset will be divided into
	Parameter11	-	shard_id	The shard ID within num_shards
	Parameter12	-	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.GTZAN(root, url='http://opihi.cs.uvic.ca/sound/genres.tar.gz')
dataloader = DataLoader(dataset)

# MindSpore
import mindspore.dataset as ds

# Download GTZAN dataset files, unzip into the following structure
# .
# └── /path/to/dataset_directory/
#      ├── blues
#      │    ├──blues.00000.wav
#      │    ├──blues.00001.wav
#      │    ├──blues.00002.wav
#      │    ├──...
#      ├── disco
#      │    ├──disco.00000.wav
#      │    ├──disco.00001.wav
#      │    ├──disco.00002.wav
#      │    └──...
#      └──...
root = "/path/to/dataset_directory/"
ms_dataloader = ds.GTZANDataset(root, usage='all')