nnbma package

Subpackages

• nnbma.dataset package
  • Submodules
  • nnbma.dataset.regression_dataset module
    • RegressionDataset
      • RegressionDataset.apply_transf()
      • RegressionDataset.from_pandas()
      • RegressionDataset.getall()
      • RegressionDataset.has_nan()
      • RegressionDataset.has_nonfinite()
      • RegressionDataset.inputs_names
      • RegressionDataset.inputs_size()
      • RegressionDataset.join()
      • RegressionDataset.load()
      • RegressionDataset.n_inputs
      • RegressionDataset.n_outputs
      • RegressionDataset.outputs_names
      • RegressionDataset.outputs_size()
      • RegressionDataset.save()
      • RegressionDataset.stats()
      • RegressionDataset.substract()
      • RegressionDataset.to_pandas()
      • RegressionDataset.x
      • RegressionDataset.y
    • RegressionSubset
      • RegressionSubset.dataset
      • RegressionSubset.indices
      • RegressionSubset.issubsetof()
      • RegressionSubset.x
      • RegressionSubset.y
  • nnbma.dataset.mask_dataset module
    • MaskDataset
      • MaskDataset.features_names
      • MaskDataset.features_size()
      • MaskDataset.from_pandas()
      • MaskDataset.getall()
      • MaskDataset.join()
      • MaskDataset.load()
      • MaskDataset.m
      • MaskDataset.n_features
      • MaskDataset.save()
      • MaskDataset.stats()
      • MaskDataset.substract()
      • MaskDataset.to_pandas()
    • MaskSubset
      • MaskSubset.issubsetof()
      • MaskSubset.m
  • Module contents
• nnbma.layers package
  • Submodules
  • nnbma.layers.additional_module module
    • AdditionalModule
      • AdditionalModule.forward()
      • AdditionalModule.training
    • AdditionalModuleFromExisting
      • AdditionalModuleFromExisting.forward()
      • AdditionalModuleFromExisting.training
  • nnbma.layers.polynomial_expansion module
    • PolynomialExpansion
      • PolynomialExpansion.expanded_features()
      • PolynomialExpansion.forward()
      • PolynomialExpansion.training
      • PolynomialExpansion.update_standardization()
  • nnbma.layers.restrictable_linear module
    • RestrictableLinear
      • RestrictableLinear.forward()
      • RestrictableLinear.in_features
      • RestrictableLinear.out_features
      • RestrictableLinear.restrict_to_output_subset()
      • RestrictableLinear.train()
      • RestrictableLinear.weight
  • Module contents
• nnbma.learning package
  • Submodules
  • nnbma.learning.batch_scheduler module
    • BatchScheduler
      • BatchScheduler.get_batch_size()
      • BatchScheduler.set_epoch()
      • BatchScheduler.step()
    • ConstantBatch
      • ConstantBatch.get_batch_size()
    • ExponentialBatchScheduler
      • ExponentialBatchScheduler.get_batch_size()
    • LinearBatchScheduler
      • LinearBatchScheduler.get_batch_size()
  • nnbma.learning.loss_functions module
    • CauchyLoss
      • CauchyLoss.forward()
      • CauchyLoss.training
    • MaskOverlay
      • MaskOverlay.forward()
      • MaskOverlay.training
    • MaskedLossFunction
      • MaskedLossFunction.forward()
      • MaskedLossFunction.training
    • MaskedMSELoss
      • MaskedMSELoss.forward()
      • MaskedMSELoss.training
    • SmoothL1Loss
      • SmoothL1Loss.forward()
      • SmoothL1Loss.training
  • nnbma.learning.network_learning module
    • LearningParameters
    • learning_procedure()
  • Module contents
• nnbma.networks package
  • Submodules
  • nnbma.networks.neural_network module
    • NeuralNetwork
      • NeuralNetwork.copy()
      • NeuralNetwork.count_bytes()
      • NeuralNetwork.count_parameters()
      • NeuralNetwork.evaluate()
      • NeuralNetwork.forward()
      • NeuralNetwork.load()
      • NeuralNetwork.restrict_to_output_subset()
      • NeuralNetwork.save()
      • NeuralNetwork.set_device()
      • NeuralNetwork.time()
      • NeuralNetwork.train()
      • NeuralNetwork.training
  • nnbma.networks.fully_connected module
    • FullyConnected
      • FullyConnected.forward()
      • FullyConnected.restrict_to_output_subset()
      • FullyConnected.training
  • nnbma.networks.densely_connected module
    • DenselyConnected
      • DenselyConnected.forward()
      • DenselyConnected.restrict_to_output_subset()
      • DenselyConnected.training
  • nnbma.networks.polynomial_network module
    • PolynomialNetwork
      • PolynomialNetwork.forward()
      • PolynomialNetwork.restrict_to_output_subset()
      • PolynomialNetwork.training
      • PolynomialNetwork.update_standardization()
  • nnbma.networks.embedding_network module
    • EmbeddingNetwork
      • EmbeddingNetwork.forward()
      • EmbeddingNetwork.training
  • nnbma.networks.merging_network module
    • MergingNetwork
      • MergingNetwork.forward()
      • MergingNetwork.restrict_to_output_subset()
      • MergingNetwork.training
  • Module contents
• nnbma.operators package
  • Submodules
  • nnbma.operators.base module
    • asinh()
    • id()
    • log10()
    • pow10()
    • sinh()
  • nnbma.operators.normalization module
    • InverseNormalizer
    • NormTypes
      • NormTypes.MEAN0
      • NormTypes.MEAN0STD1
      • NormTypes.MIN0MAX1
      • NormTypes.MIN1MAX1
      • NormTypes.NONE
      • NormTypes.STD1
    • Normalizer
  • nnbma.operators.operator module
    • ColumnwiseOperator
    • Operator
    • SequentialOperator
  • Module contents

Module contents