learnergy
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Package Reference

  • learnergy.core
    • Dataset
      • Dataset.__getitem__()
      • Dataset.__init__()
      • Dataset.__len__()
      • Dataset.data()
      • Dataset.targets()
      • Dataset.transform()
    • Model
      • Model.__init__()
      • Model.device()
      • Model.dump()
      • Model.history()
    • Dataset
      • __getitem__
      • __init__
      • __len__
      • data
      • targets
      • transform
    • Model
      • __init__
      • device
      • dump
      • history
  • learnergy.math
    • learnergy.math.metrics
      • calculate_ssim()
      • logger
      • calculate_ssim
      • logger
    • learnergy.math.scale
      • unitary_scale()
      • unitary_scale
  • learnergy.models
    • learnergy.models.bernoulli
      • 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()
      • ConvRBM
        • W
        • __init__
        • a
        • b
        • decay
        • energy
        • filter_shape
        • fit
        • forward
        • gibbs_sampling
        • hidden_sampling
        • hidden_shape
        • lr
        • maxpooling
        • momentum
        • n_channels
        • n_filters
        • optimizer
        • reconstruct
        • steps
        • visible_sampling
        • visible_shape
      • DiscriminativeRBM
        • U
        • __init__
        • c
        • fit
        • labels_sampling
        • loss
        • n_classes
        • predict
      • DropConnectRBM
        • __init__
        • hidden_sampling
      • DropoutRBM
        • __init__
        • hidden_sampling
        • p
        • reconstruct
      • HybridDiscriminativeRBM
        • __init__
        • alpha
        • class_sampling
        • fit
        • gibbs_sampling
        • hidden_sampling
      • RBM
        • T
        • W
        • __init__
        • a
        • b
        • decay
        • energy
        • fit
        • forward
        • gibbs_sampling
        • hidden_sampling
        • lr
        • momentum
        • n_hidden
        • n_visible
        • optimizer
        • pre_activation
        • pseudo_likelihood
        • reconstruct
        • steps
        • visible_sampling
    • learnergy.models.deep
      • 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()
      • ConvDBN
        • __init__
        • decay
        • filter_shape
        • fit
        • forward
        • lr
        • maxpooling
        • models
        • momentum
        • n_channels
        • n_filters
        • n_layers
        • reconstruct
        • steps
        • visible_shape
      • DBN
        • T
        • __init__
        • decay
        • fit
        • forward
        • lr
        • models
        • momentum
        • n_hidden
        • n_layers
        • n_visible
        • reconstruct
        • steps
      • ResidualDBN
        • __init__
        • calculate_residual
        • fit
        • forward
        • zetta1
        • zetta2
    • learnergy.models.extra
      • SigmoidRBM
        • SigmoidRBM.__init__()
        • SigmoidRBM.visible_sampling()
      • SigmoidRBM4deep
        • SigmoidRBM4deep.__init__()
        • SigmoidRBM4deep.fit()
      • SigmoidRBM
        • __init__
        • visible_sampling
      • SigmoidRBM4deep
        • __init__
        • fit
    • learnergy.models.gaussian
      • 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()
      • GaussianConvRBM
        • __init__
        • fit
        • hidden_sampling
        • normalize
        • visible_sampling
      • GaussianConvRBM4deep
        • __init__
        • fit
        • hidden_sampling
        • normalize
        • visible_sampling
      • GaussianRBM
        • __init__
        • energy
        • fit
        • forward
        • input_normalize
        • normalize
        • reconstruct
        • visible_sampling
      • GaussianRBM4deep
        • __init__
        • fit
      • GaussianReluRBM
        • __init__
        • hidden_sampling
      • GaussianReluRBM4deep
        • __init__
        • hidden_sampling
      • GaussianSeluRBM
        • __init__
        • hidden_sampling
      • VarianceGaussianRBM
        • __init__
        • energy
        • hidden_sampling
        • sigma
        • visible_sampling
  • learnergy.utils
    • learnergy.utils.constants
      • EPSILON
      • EPSILON
    • learnergy.utils.exception
      • ArgumentError
        • ArgumentError.__init__()
      • BuildError
        • BuildError.__init__()
      • Error
        • Error.__init__()
      • SizeError
        • SizeError.__init__()
      • TypeError
        • TypeError.__init__()
      • ValueError
        • ValueError.__init__()
      • logger
      • ArgumentError
        • __init__
      • BuildError
        • __init__
      • Error
        • __init__
      • SizeError
        • __init__
      • TypeError
        • __init__
      • ValueError
        • __init__
      • logger
    • learnergy.utils.logging
      • FORMATTER
      • LOG_FILE
      • get_console_handler()
      • get_logger()
      • get_timed_file_handler()
      • FORMATTER
      • LOG_FILE
      • get_console_handler
      • get_logger
      • get_timed_file_handler
  • learnergy.visual
    • learnergy.visual.convergence
      • plot()
      • plot
    • learnergy.visual.image
      • _rasterize()
      • create_mosaic()
      • create_rgb_mosaic()
      • _rasterize
      • create_mosaic
      • create_rgb_mosaic
    • learnergy.visual.tensor
      • save_tensor()
      • show_tensor()
      • save_tensor
      • show_tensor
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© Copyright 2020, Mateus Roder and Gustavo de Rosa Revision 49e0afc9.

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