EnhancedLinear#

class EnhancedLinear(layer, activation=None, dropout=None)[source]

Bases: Module

A wrapper class for enhancing a linear layer with activation and/or dropout.

Parameters:

  • layer (torch.nn.Module) – The linear layer to be enhanced.

  • activation (torch.nn.Module) – The activation function to be applied after the linear layer.

  • dropout (float) – The dropout probability to be applied after the activation (if provided).

Example:

>>> linear_layer = torch.nn.Linear(10, 20)
>>> activation = torch.nn.ReLU()
>>> dropout_prob = 0.5
>>> enhanced_linear = EnhancedLinear(linear_layer, activation, dropout_prob)

Initializes the EnhancedLinear module.

Parameters:

  • layer (torch.nn.Module) – The linear layer to be enhanced.

  • activation (torch.nn.Module) – The activation function to be applied after the linear layer.

  • dropout (float) – The dropout probability to be applied after the activation (if provided).

forward(x)[source]

Forward pass through the enhanced linear module.

Parameters:

x (torch.Tensor) – Input tensor.

Returns:

Output tensor after passing through the enhanced linear module.

Return type:

torch.Tensor