nichecompass.nn.AddOnMaskedLayer
- class nichecompass.nn.AddOnMaskedLayer(n_input, n_output, mask, addon_mask, masked_features_idx, bias=False, n_addon_input=0, n_cat_covariates_embed_input=0, activation=torch.nn.Softmax)
Add-on masked layer class.
Parts of the implementation are adapted from https://github.com/theislab/scarches/blob/7980a187294204b5fb5d61364bb76c0b809eb945/scarches/models/expimap/modules.py#L28; 01.10.2022.
- Parameters:
n_input (
int) – Number of mask input nodes to the add-on masked layer.n_output (
int) – Number of output nodes from the add-on masked layer.mask (
Tensor) – Mask that is used to mask the node connections for mask inputs from the input layer to the output layer.addon_mask (
Tensor) – Mask that is used to mask the node connections for add-on inputs from the input layer to the output layer.masked_features_idx (
List) – Index of input features that are included in the mask.bias (
bool(default:False)) – If ´True´, use a bias for the mask input nodes.n_addon_input (
int(default:0)) – Number of add-on input nodes to the add-on masked layer.n_cat_covariates_embed_input (
int(default:0)) – Number of categorical covariates embedding input nodes to the addon masked layer.activation (
Module(default:torch.nn.Softmax)) – Activation function used at the end of the ad-on masked layer.
Methods table
|
Forward pass of the add-on masked layer. |
Methods
- AddOnMaskedLayer.forward(input, dynamic_mask=None)
Forward pass of the add-on masked layer.
- Parameters:
input (
Tensor) – Input features to the add-on masked layer. Includes add-on input nodes and categorical covariates embedding input nodes if specified.dynamic_mask (
Optional[Tensor] (default:None)) – Additional optional dynamic mask for the masked layer.
- Return type:
Tensor- Returns:
output: Output of the add-on masked layer.