Differences with torchaudio.datasets.YESNO

torchaudio.datasets.YESNO

class torchaudio.datasets.YESNO(
    root: str,
    url: str = 'http://www.openslr.org/resources/1/waves_yesno.tar.gz',
    folder_in_archive: str = 'waves_yesno',
    download: bool = False)

For more information, see torchaudio.datasets.YESNO.

mindspore.dataset.YesNoDataset

class mindspore.dataset.YesNoDataset(
    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.YesNoDataset.

Differences

PyTorch: Read the YesNo dataset.

MindSpore: Read the YesNo 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	-	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.YESNO(root, url='http://www.openslr.org/resources/1/waves_yesno.tar.gz')
dataloader = DataLoader(dataset)

# MindSpore
import mindspore.dataset as ds

# Download YesNo dataset files, unzip into the following structure
# .
# └── /path/to/dataset_directory/
#      ├── 1_1_0_0_1_1_0_0.wav
#      ├── 1_0_0_0_1_1_0_0.wav
#      ├── 1_1_0_0_1_1_0_0.wav
#      └──....
root = "/path/to/dataset_directory/"
ms_dataloader = ds.YesNoDataset(root)