mobilenet_v2

lucid.models.mobilenet_v2(num_classes: int = 1000, **kwargs) → MobileNet_V2

The mobilenet_v2 function creates a MobileNet-v2 model instance. This architecture incorporates inverted residual blocks and linear bottlenecks, making it highly efficient for mobile and embedded vision applications.

Total Parameters: 3,504,872

Function Signature

def mobilenet_v2(num_classes: int = 1000, **kwargs) -> MobileNet_V2

Parameters

  • num_classes (int, optional): Specifies the number of output classes for classification. Default is 1000, commonly used for ImageNet.

  • kwargs (dict, optional): Additional arguments passed to the MobileNet_V2 constructor for further customization.

Returns

  • MobileNet_V2: An instance of the MobileNet-v2 model configured with the specified parameters.

Example

import lucid
from lucid.models import mobilenet_v2

# Create a MobileNet-v2 model with default parameters
model = mobilenet_v2(num_classes=1000)

# Create a sample input tensor
input_tensor = lucid.random.randn(1, 3, 224, 224)

# Perform a forward pass
output = model(input_tensor)
print(output)