fusilli.fusionmodels.tabularfusion.concat_feature_mapsο
Concatenating the feature maps of the two tabular modalities.
Classes
|
Concatenating the feature maps of the two tabular modalities. |
- class ConcatTabularFeatureMaps(prediction_task, data_dims, multiclass_dimensions)[source]ο
Bases:
ParentFusionModel
,Module
Concatenating the feature maps of the two tabular modalities.
- prediction_taskο
Type of prediction to be performed.
- Type:
str
- mod1_layersο
Dictionary containing the layers of the first modality. Calculated in the
set_mod1_layers()
method.- Type:
nn.ModuleDict
- mod2_layersο
Dictionary containing the layers of the second modality. Calculated in the
set_mod2_layers()
method.- Type:
nn.ModuleDict
- fused_dimο
Number of features of the fused layers. In this method, itβs the size of the tabular 1 layers output plus the size of the tabular 2 layers output.
- Type:
int
- fused_layersο
Sequential layer containing the fused layers. Calculated in the
calc_fused_layers()
method.- Type:
nn.Sequential
- final_predictionο
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)[source]ο
- Parameters:
prediction_task (str) β Type of prediction to be performed.
data_dims (list) β List containing the dimensions of the data.
multiclass_dimensions (int) β Number of classes in the multiclass classification task.
- forward(x)[source]ο
Forward pass of the model.
- Parameters:
x (tuple) β Tuple containing the input data.
- Returns:
List containing the output of the model.
- Return type:
list
- fusion_type = 'operation'ο
Type of fusion.
- Type:
str
- method_name = 'Concatenating tabular feature maps'ο
Name of the method.
- Type:
str
- modality_type = 'tabular_tabular'ο
Type of modality.
- Type:
str