alibi.models.tensorflow.autoencoder

This module contains a Tensorflow 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, TensorFlowTrainer, Trainer, Layer, TFLayer, KerasAutoTrackable, AutoTrackable, Trackable, Operation, KerasSaveable

Autoencoder. Standard autoencoder architecture. The model is composed from two submodules, the encoder and the decoder. The forward pass consists 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: keras.src.models.model.Model, decoder: keras.src.models.model.Model, **kwargs) -> None

Name	Type	Default	Description
encoder	keras.src.models.model.Model		Encoder network.
decoder	keras.src.models.model.Model		Decoder network.

Methods

call

call(x: tensorflow.python.framework.tensor.Tensor, kwargs) -> Union[tensorflow.python.framework.tensor.Tensor, List[tensorflow.python.framework.tensor.Tensor]]

Name	Type	Default	Description
x	tensorflow.python.framework.tensor.Tensor		Input tensor.
**kwargs			Other arguments passed to encoder/decoder call method.

Returns

• Type: Union[tensorflow.python.framework.tensor.Tensor, List[tensorflow.python.framework.tensor.Tensor]]

HeAE

Inherits from: AE, Model, TensorFlowTrainer, Trainer, Layer, TFLayer, KerasAutoTrackable, AutoTrackable, Trackable, Operation, KerasSaveable

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: keras.src.models.model.Model, decoder: keras.src.models.model.Model, **kwargs) -> None

Name	Type	Default	Description
encoder	keras.src.models.model.Model		Encoder network.
decoder	keras.src.models.model.Model		Decoder network.

Methods

build

build(input_shape: Tuple[int, .Ellipsis]) -> None

Name	Type	Default	Description
input_shape	Tuple[int, .Ellipsis]		Tensor's input shape.

Returns

• Type: None

call

call(x: tensorflow.python.framework.tensor.Tensor, kwargs) -> List[tensorflow.python.framework.tensor.Tensor]

Name	Type	Default	Description
x	tensorflow.python.framework.tensor.Tensor		Input tensor.
**kwargs			Other arguments passed to the encoder/decoder.

Returns

• Type: List[tensorflow.python.framework.tensor.Tensor]