braindecode.modules.Conv2dWithConstraint

class braindecode.modules.Conv2dWithConstraint(*args, max_norm=1, **kwargs)

2D convolution with max-norm constraint on the weights.

Examples

>>> import torch
>>> from braindecode.modules import Conv2dWithConstraint
>>> module = Conv2dWithConstraint(4, 8, kernel_size=(1, 3), padding=(0, 1), bias=False)
>>> inputs = torch.randn(2, 4, 1, 64)
>>> outputs = module(inputs)
>>> outputs.shape
torch.Size([2, 8, 1, 64])