alibi.models.pytorch.autoencoder

This module contains a Pytorch general implementation of an autoencoder, by combining the encoder and the decoder module. In addition it provides an implementation of a heterogeneous autoencoder which includes a type checking of the output.

AE

Inherits from: Model, Module

Autoencoder. Standard autoencoder architecture. The model is composed from two submodules, the encoder and the decoder. The forward pass consist of passing the input to the encoder, obtain the input embedding and pass the embedding through the decoder. The abstraction can be used for multiple data modalities.

Constructor

AE(self, encoder: torch.nn.modules.module.Module, decoder: torch.nn.modules.module.Module, **kwargs)

Name	Type	Default	Description
encoder	torch.nn.modules.module.Module		Encoder network.
decoder	torch.nn.modules.module.Module		Decoder network.

Methods

forward

forward(x: torch.Tensor) -> Union[torch.Tensor, List[torch.Tensor]]

Name	Type	Default	Description
x	torch.Tensor		Input tensor.

Returns

• Type: Union[torch.Tensor, List[torch.Tensor]]

HeAE

Inherits from: AE, Model, Module

Heterogeneous autoencoder. The model follows the standard autoencoder architecture and includes and additional type check to ensure that the output of the model is a list of tensors. For more details, see :py:class:alibi.models.pytorch.autoencoder.AE.

Constructor

HeAE(self, encoder: torch.nn.modules.module.Module, decoder: torch.nn.modules.module.Module, **kwargs)

Name	Type	Default	Description
encoder	torch.nn.modules.module.Module		Encoder network.
decoder	torch.nn.modules.module.Module		Decoder network.

Methods

forward

forward(x: torch.Tensor) -> List[torch.Tensor]

Name	Type	Default	Description
x	torch.Tensor		Input tensor.

Returns

• Type: List[torch.Tensor]