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Tools for building neural networks.
Modules
initializers module: Initializer functions for building neural networks.
losses module: Loss functions for neural networks.
util module: Utilitity functions for building neural networks.
Classes
class Affine: Basic affine layer.
class AffineVariationalFlipout: Densely-connected layer class with Flipout estimator.
class AffineVariationalReparameterization: Densely-connected layer class with reparameterization estimator.
class AffineVariationalReparameterizationLocal: Densely-connected layer class with local reparameterization estimator.
class Convolution: Convolution layer.
class ConvolutionTranspose: ConvolutionTranspose layer.
class ConvolutionTransposeVariationalFlipout: ConvolutionTranspose layer class with Flipout estimator.
class ConvolutionTransposeVariationalReparameterization: ConvolutionTranspose layer class with reparameterization estimator.
class ConvolutionV2: Convolution layer.
class ConvolutionVariationalFlipout: Convolution layer class with Flipout estimator.
class ConvolutionVariationalFlipoutV2: Convolution layer class with Flipout estimator.
class ConvolutionVariationalReparameterization: Convolution layer class with reparameterization estimator.
class ConvolutionVariationalReparameterizationV2: Convolution layer class with reparameterization estimator.
class Layer: A callable tf.Module.
class Sequential: A Layer characterized by iteratively given functions.
class VariationalLayer: Base class for all variational layers.