View source on GitHub |
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.