efficientnet_b2¶

lucid.models.efficientnet_b2(num_classes: int = 1000, **kwargs) → EfficientNet¶

The efficientnet_b2 function creates an instance of the EfficientNet-B2 model, a lightweight and efficient convolutional neural network preconfigured with parameters suitable for EfficientNet-B2.

Total Parameters: 9,111,370

Function Signature¶

@register_model
def efficientnet_b2(num_classes: int = 1000, **kwargs) -> EfficientNet:

Parameters¶

num_classes (int, optional):
The number of output classes for the classification task. Defaults to 1000 (e.g., for ImageNet).
kwargs (dict, optional):
Additional keyword arguments passed to the EfficientNet class for further customization.

Returns¶

EfficientNet:
An instance of the EfficientNet class configured with parameters for EfficientNet-B2.

Examples¶

from lucid.models import efficientnet_b2

# Create an EfficientNet-B2 model
model = efficientnet_b2(num_classes=1000)

# Forward pass with a random input
input_tensor = lucid.random.randn(1, 3, 224, 224)  # Batch size of 1, ImageNet resolution
output = model(input_tensor)
print(output.shape)  # Output shape: (1, 1000)