Package Reference
Dataset
Dataset.__getitem__()
Dataset.__init__()
Dataset.__len__()
Dataset.data()
Dataset.targets()
Dataset.transform()
Model
Model.__init__()
Model.device()
Model.dump()
Model.history()
calculate_ssim()
logger
unitary_scale()
ConvRBM
ConvRBM.W()
ConvRBM.__init__()
ConvRBM.a()
ConvRBM.b()
ConvRBM.decay()
ConvRBM.energy()
ConvRBM.filter_shape()
ConvRBM.fit()
ConvRBM.forward()
ConvRBM.gibbs_sampling()
ConvRBM.hidden_sampling()
ConvRBM.hidden_shape()
ConvRBM.lr()
ConvRBM.maxpooling()
ConvRBM.momentum()
ConvRBM.n_channels()
ConvRBM.n_filters()
ConvRBM.optimizer()
ConvRBM.reconstruct()
ConvRBM.steps()
ConvRBM.visible_sampling()
ConvRBM.visible_shape()
DiscriminativeRBM
DiscriminativeRBM.U()
DiscriminativeRBM.__init__()
DiscriminativeRBM.c()
DiscriminativeRBM.fit()
DiscriminativeRBM.labels_sampling()
DiscriminativeRBM.loss()
DiscriminativeRBM.n_classes()
DiscriminativeRBM.predict()
DropConnectRBM
DropConnectRBM.__init__()
DropConnectRBM.hidden_sampling()
DropoutRBM
DropoutRBM.__init__()
DropoutRBM.hidden_sampling()
DropoutRBM.p()
DropoutRBM.reconstruct()
HybridDiscriminativeRBM
HybridDiscriminativeRBM.__init__()
HybridDiscriminativeRBM.alpha()
HybridDiscriminativeRBM.class_sampling()
HybridDiscriminativeRBM.fit()
HybridDiscriminativeRBM.gibbs_sampling()
HybridDiscriminativeRBM.hidden_sampling()
RBM
RBM.T()
RBM.W()
RBM.__init__()
RBM.a()
RBM.b()
RBM.decay()
RBM.energy()
RBM.fit()
RBM.forward()
RBM.gibbs_sampling()
RBM.hidden_sampling()
RBM.lr()
RBM.momentum()
RBM.n_hidden()
RBM.n_visible()
RBM.optimizer()
RBM.pre_activation()
RBM.pseudo_likelihood()
RBM.reconstruct()
RBM.steps()
RBM.visible_sampling()
ConvDBN
ConvDBN.__init__()
ConvDBN.decay()
ConvDBN.filter_shape()
ConvDBN.fit()
ConvDBN.forward()
ConvDBN.lr()
ConvDBN.maxpooling()
ConvDBN.models()
ConvDBN.momentum()
ConvDBN.n_channels()
ConvDBN.n_filters()
ConvDBN.n_layers()
ConvDBN.reconstruct()
ConvDBN.steps()
ConvDBN.visible_shape()
DBN
DBN.T()
DBN.__init__()
DBN.decay()
DBN.fit()
DBN.forward()
DBN.lr()
DBN.models()
DBN.momentum()
DBN.n_hidden()
DBN.n_layers()
DBN.n_visible()
DBN.reconstruct()
DBN.steps()
ResidualDBN
ResidualDBN.__init__()
ResidualDBN.calculate_residual()
ResidualDBN.fit()
ResidualDBN.forward()
ResidualDBN.zetta1()
ResidualDBN.zetta2()
SigmoidRBM
SigmoidRBM.__init__()
SigmoidRBM.visible_sampling()
SigmoidRBM4deep
SigmoidRBM4deep.__init__()
SigmoidRBM4deep.fit()
GaussianConvRBM
GaussianConvRBM.__init__()
GaussianConvRBM.fit()
GaussianConvRBM.hidden_sampling()
GaussianConvRBM.normalize()
GaussianConvRBM.visible_sampling()
GaussianConvRBM4deep
GaussianConvRBM4deep.__init__()
GaussianConvRBM4deep.fit()
GaussianConvRBM4deep.hidden_sampling()
GaussianConvRBM4deep.normalize()
GaussianConvRBM4deep.visible_sampling()
GaussianRBM
GaussianRBM.__init__()
GaussianRBM.energy()
GaussianRBM.fit()
GaussianRBM.forward()
GaussianRBM.input_normalize()
GaussianRBM.normalize()
GaussianRBM.reconstruct()
GaussianRBM.visible_sampling()
GaussianRBM4deep
GaussianRBM4deep.__init__()
GaussianRBM4deep.fit()
GaussianReluRBM
GaussianReluRBM.__init__()
GaussianReluRBM.hidden_sampling()
GaussianReluRBM4deep
GaussianReluRBM4deep.__init__()
GaussianReluRBM4deep.hidden_sampling()
GaussianSeluRBM
GaussianSeluRBM.__init__()
GaussianSeluRBM.hidden_sampling()
VarianceGaussianRBM
VarianceGaussianRBM.__init__()
VarianceGaussianRBM.energy()
VarianceGaussianRBM.hidden_sampling()
VarianceGaussianRBM.sigma()
VarianceGaussianRBM.visible_sampling()
EPSILON
ArgumentError
ArgumentError.__init__()
BuildError
BuildError.__init__()
Error
Error.__init__()
SizeError
SizeError.__init__()
TypeError
TypeError.__init__()
ValueError
ValueError.__init__()
FORMATTER
LOG_FILE
get_console_handler()
get_logger()
get_timed_file_handler()
plot()
_rasterize()
create_mosaic()
create_rgb_mosaic()
save_tensor()
show_tensor()
Scaling-related mathematical functions.
Scales an array between 0 and 1.
x – A numpy array to be scaled.
Scaled array.
(np.array)