def stacking_classifier(model_type):
classifier = torch.nn.Linear(16*10,10)
if "binary" == model_type:
return BinaryModel(classifier, keep_activation=True)
else:
return classifier
def simpleresnet(size, model_type):
if "small" == size:
n_channels = 32
depth = 4
else:
n_channels = 96
depth = 4
if "binary" == model_type:
return BinaryModel(SimpleResNet(in_channels = 1, n_channels = n_channels, depth = depth, num_classes=10), keep_activation=True)
else:
return SimpleResNet(in_channels = 1, n_channels = n_channels, depth = depth, num_classes=10)