dgld.modules.dglAug.transforms.feature_dropout

Feature Dropout

class dgld.modules.dglAug.transforms.feature_dropout.FeatureDropout(p=0.5)[source]

Bases: BaseTransform

Augment features by randomly masking node feautres with 0.

Parameters: p (float, optional) – Probability of a node feautre to be masked.

Example

>>> import dgl
>>> import torch
>>> from dglAug import FeatureDropout

>>> transform = FeatureDropout(p=0.2)
>>> g = dgl.rand_graph(4,2)
>>> g.ndata['feat'] = torch.rand((4,5))
>>> print(g.ndata['feat'])
tensor([[0.7706, 0.3505, 0.1246, 0.5076, 0.3071],
    [0.5388, 0.6082, 0.5088, 0.8058, 0.4955],
    [0.7638, 0.3115, 0.4265, 0.5507, 0.4404],
    [0.3127, 0.0056, 0.1876, 0.9971, 0.6389]])
>>> g = transform(g)
>>> print(g.ndata['feat'])
tensor([[0.0000, 0.0000, 0.1558, 0.6345, 0.3839],
    [0.0000, 0.7603, 0.6360, 0.0000, 0.6194],
    [0.0000, 0.3893, 0.5331, 0.0000, 0.5505],
    [0.3909, 0.0070, 0.2345, 1.2464, 0.0000]])