Hierarchy For All Packages

Package Hierarchies:

• classification,
• graphClassification,
• mklab.JGNN,
• mklab.JGNN.adhoc,
• mklab.JGNN.adhoc.datasets,
• mklab.JGNN.adhoc.parsers,
• mklab.JGNN.adhoc.train,
• mklab.JGNN.core,
• mklab.JGNN.core.distribution,
• mklab.JGNN.core.empty,
• mklab.JGNN.core.matrix,
• mklab.JGNN.core.tensor,
• mklab.JGNN.core.util,
• mklab.JGNN.nn,
• mklab.JGNN.nn.activations,
• mklab.JGNN.nn.initializers,
• mklab.JGNN.nn.inputs,
• mklab.JGNN.nn.loss,
• mklab.JGNN.nn.loss.report,
• mklab.JGNN.nn.operations,
• mklab.JGNN.nn.optimizers,
• mklab.JGNN.nn.pooling,
• nodeClassification,
• primitives,
• tutorial

Class Hierarchy

• java.lang.Object
  • mklab.JGNN.nn.optimizers.Adam (implements mklab.JGNN.nn.Optimizer)
  • nodeClassification.APPNP
  • mklab.JGNN.adhoc.BatchData
  • mklab.JGNN.nn.optimizers.BatchOptimizer (implements mklab.JGNN.nn.Optimizer)
  • Benchmarks
  • mklab.JGNN.core.matrix.ColumnRepetition.Repeat1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.ColumnRepetition.Repeat2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.adhoc.Dataset
    • mklab.JGNN.adhoc.datasets.Citeseer
    • mklab.JGNN.adhoc.datasets.Cora
    • mklab.JGNN.adhoc.datasets.Pubmed
  • mklab.JGNN.core.matrix.Diagonal.Diagonal1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.Diagonal.Diagonal2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.util.FastEntry<K,V> (implements java.util.Map.Entry<K,V>)
  • nodeClassification.GAT
  • nodeClassification.GCN
  • nodeClassification.GCNII
  • mklab.JGNN.nn.optimizers.GradientDescent (implements mklab.JGNN.nn.Optimizer)
  • nodeClassification.HetGCN
  • mklab.JGNN.adhoc.IdConverter
  • mklab.JGNN.nn.Initializer
    • mklab.JGNN.nn.initializers.VariancePreservingInitializer
      • mklab.JGNN.nn.initializers.KaimingNormal
      • mklab.JGNN.nn.initializers.KaimingUniform
      • mklab.JGNN.nn.initializers.XavierNormal
      • mklab.JGNN.nn.initializers.XavierUniform
  • tutorial.Learning
  • classification.LogisticRegression
  • mklab.JGNN.nn.Loss
    • mklab.JGNN.nn.loss.Accuracy
    • mklab.JGNN.nn.loss.BinaryCrossEntropy
    • mklab.JGNN.nn.loss.CategoricalCrossEntropy
    • mklab.JGNN.nn.loss.report.VerboseLoss
  • mklab.JGNN.core.util.LossTest
  • mklab.JGNN.nn.operations.LSTM
  • mklab.JGNN.nn.operations.LSTM.LSTMState
  • mklab.JGNN.core.MatrixTest
  • graphClassification.MeanPooling
  • mklab.JGNN.core.Memory
  • mklab.JGNN.core.Memory.Scope
  • nodeClassification.MessagePassing
  • graphClassification.MessageSortPooling
  • classification.MLP
  • mklab.JGNN.nn.Model
  • mklab.JGNN.adhoc.ModelBuilder
    • mklab.JGNN.adhoc.parsers.FastBuilder
    • mklab.JGNN.adhoc.parsers.LayeredBuilder
    • mklab.JGNN.adhoc.parsers.Neuralang
  • primitives.ModelBuilderInternals
  • mklab.JGNN.adhoc.ModelTraining
    • mklab.JGNN.adhoc.train.AGFTraining
    • mklab.JGNN.adhoc.train.SampleClassification
  • tutorial.NN
  • mklab.JGNN.nn.NNOperation
    • mklab.JGNN.nn.operations.Add
    • mklab.JGNN.nn.operations.Attention
    • mklab.JGNN.nn.operations.Complement
    • mklab.JGNN.nn.operations.Concat
    • mklab.JGNN.nn.operations.Dropout
    • mklab.JGNN.nn.activations.Exp
    • mklab.JGNN.nn.operations.From
    • mklab.JGNN.nn.operations.Gather
    • mklab.JGNN.nn.operations.Identity
    • mklab.JGNN.nn.activations.L1
    • mklab.JGNN.nn.operations.Log
    • mklab.JGNN.nn.activations.LRelu
    • mklab.JGNN.nn.operations.MatMul
    • mklab.JGNN.nn.pooling.Max
    • mklab.JGNN.nn.pooling.Mean
    • mklab.JGNN.nn.operations.Multiply
    • mklab.JGNN.nn.activations.NExp
    • mklab.JGNN.nn.inputs.Parameter
      • mklab.JGNN.nn.inputs.Constant
    • mklab.JGNN.nn.activations.PRelu
    • mklab.JGNN.nn.operations.Reduce
    • mklab.JGNN.nn.activations.Relu
    • mklab.JGNN.nn.operations.Repeat
    • mklab.JGNN.nn.operations.Reshape
    • mklab.JGNN.nn.activations.Sigmoid
    • mklab.JGNN.nn.pooling.SoftMax
    • mklab.JGNN.nn.pooling.Sort
    • mklab.JGNN.nn.pooling.Sum
    • mklab.JGNN.nn.activations.Tanh
    • mklab.JGNN.nn.operations.To
    • mklab.JGNN.nn.operations.Transpose
    • mklab.JGNN.nn.inputs.Variable
  • mklab.JGNN.nn.NNOperation.ThreadData
  • mklab.JGNN.core.distribution.Normal (implements mklab.JGNN.core.Distribution)
  • tutorial.Quickstart
  • mklab.JGNN.core.util.Range (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.util.Range2D (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.nn.optimizers.Regularization (implements mklab.JGNN.nn.Optimizer)
  • mklab.JGNN.core.matrix.RowRepetition.Repeat1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.RowRepetition.Repeat2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • nodeClassification.Scripting
  • primitives.SimpleNetwork
  • mklab.JGNN.core.Slice (implements java.lang.Iterable<T>)
  • mklab.JGNN.core.util.Sort
  • graphClassification.SortPooling
  • graphClassification.SortPoolingManual
  • mklab.JGNN.core.matrix.SparseMatrix.Sparse2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.Tensor (implements java.lang.Iterable<T>)
    • mklab.JGNN.core.matrix.AccessCol
    • mklab.JGNN.core.matrix.AccessRow
    • mklab.JGNN.core.tensor.AccessSubtensor
    • mklab.JGNN.core.tensor.DenseTensor
    • mklab.JGNN.core.empty.EmptyTensor
    • mklab.JGNN.core.Matrix
      • mklab.JGNN.core.matrix.ColumnRepetition
      • mklab.JGNN.core.matrix.DenseMatrix
      • mklab.JGNN.core.matrix.Diagonal
      • mklab.JGNN.core.empty.EmptyMatrix
      • mklab.JGNN.core.matrix.RepeatMatrix
      • mklab.JGNN.core.matrix.RowRepetition
      • mklab.JGNN.core.matrix.SparseMatrix
      • mklab.JGNN.core.matrix.SparseSymmetric
      • mklab.JGNN.core.matrix.TransposedMatrix
      • mklab.JGNN.core.matrix.VectorizedMatrix
      • mklab.JGNN.core.matrix.WrapCols
      • mklab.JGNN.core.matrix.WrapRows
    • mklab.JGNN.core.tensor.RepeatTensor
    • mklab.JGNN.core.tensor.SparseTensor
    • mklab.JGNN.core.tensor.VectorizedTensor
  • mklab.JGNN.core.TensorTest
  • mklab.JGNN.TensorTest
  • mklab.JGNN.core.ThreadPool
  • graphClassification.TrajectoryData
  • mklab.JGNN.core.matrix.TransposedMatrix.Transposed1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.TransposedMatrix.Transposed2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.distribution.Uniform (implements mklab.JGNN.core.Distribution)
  • mklab.JGNN.core.matrix.WrapCols.Wrap1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.WrapCols.Wrap2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.WrapRows.Wrap1DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)
  • mklab.JGNN.core.matrix.WrapRows.Wrap2DIterator (implements java.lang.Iterable<T>, java.util.Iterator<E>)

Interface Hierarchy

• mklab.JGNN.core.Distribution
• mklab.JGNN.core.util.Loss
• mklab.JGNN.nn.Optimizer