efficientnet_b1

lucid.models.efficientnet_b1(num_classes: int = 1000, **kwargs) → EfficientNet

The efficientnet_b1 function creates an instance of the EfficientNet-B1 model, a lightweight and efficient convolutional neural network preconfigured with parameters suitable for EfficientNet-B1.

Total Parameters: 7,795,560

Function Signature

@register_model
def efficientnet_b1(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-B1.

Examples

from lucid.models import efficientnet_b1

# Create an EfficientNet-B1 model
model = efficientnet_b1(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)