vggnet_13

lucid.models.vggnet_13(num_classes: int = 1000, **kwargs) → VGGNet

The vggnet_13 function constructs a VGGNet-13 model, which is a variant of the VGGNet architecture with 13 layers. It builds a VGGNetConfig preset internally and forwards extra keyword arguments to that config.

Total Parameters: 133,047,848

Function Signature

@register_model
def vggnet_13(num_classes: int = 1000, **kwargs) -> VGGNet

Parameters

• num_classes (int, optional): The number of classes for the classification output. Defaults to 1000.

• kwargs: Additional keyword arguments passed to VGGNetConfig, such as in_channels, dropout, or classifier_hidden_features.

Returns

• VGGNet: A VGGNet-13 model initialized with the specified parameters.

Examples

from lucid.models import vggnet_13

# Create a VGGNet-13 model
model = vggnet_13(num_classes=100)

print(model)

model = vggnet_13(
    num_classes=10,
    in_channels=1,
    dropout=0.25,
    classifier_hidden_features=(512, 256),
)

print(model.config)