fusilli.fusionmodels.tabularfusion.activation

Activation-function fusion model for tabular data.

Classes

ActivationFusion(prediction_task, data_dims, ...)

Performs an element wise product of the feature maps of the two tabular modalities, tanh activation function and sigmoid activation function.

class ActivationFusion(prediction_task, data_dims, multiclass_dimensions)

Bases: ParentFusionModel, Module

Performs an element wise product of the feature maps of the two tabular modalities, tanh activation function and sigmoid activation function. Afterwards the the first tabular modality feature map is concatenated with the fused feature map.

prediction_task

Type of prediction to be performed.

Type:

str

mod1_layers

Dictionary containing the layers of the first modality. Calculated in the set_mod1_layers() method.

Type:

nn.ModuleDict

mod2_layers

Dictionary containing the layers of the second modality. Calculated in the set_mod2_layers() method.

Type:

nn.ModuleDict

fused_dim

Number of features of the fused layers. In this method, it’s the size of the tabular 1 layers output plus the size of the tabular 2 layers output.

Type:

int

fused_layers

Sequential layer containing the fused layers. Calculated in the calc_fused_layers() method.

Type:

nn.Sequential

final_prediction

Sequential layer containing the final prediction layers. The final prediction layers take in the number of features of the fused layers as input. Calculated in the calc_fused_layers() method.

Type:

nn.Sequential

__init__(prediction_task, data_dims, multiclass_dimensions)

Parameters:

• prediction_task (str) – Type of prediction to be performed.

• data_dims (list) – List containing the dimensions of the data.

• multiclass_dimensions (int) – Number of classes in the multiclass classification problem.

calc_fused_layers()

Calculate the fused layers.

Return type:

None

forward(x)

Forward pass of the model.

Parameters:

x (tuple) – Tuple containing the input data.

Returns:

List containing the output of the model.

Return type:

list

fusion_type = 'operation'

Type of fusion.

Type:

str

get_fused_dim()

Get the number of features of the fused layers. Assuming mod1_layers and mod2_layers output the same dimension.

method_name = 'Activation function map fusion'

Name of the method.

Type:

str

modality_type = 'tabular_tabular'

Type of modality.

Type:

str