API reference

• Builders
  • NeuralNetworks
  • Models
  • Layers
  • Losses
  • Optimizers
  • Gradient
  • Datasets
  • Data
• Models
  • Sequential
  • ModelLoader
  • AbstractModel
• Layers
  • Dense
  • Activation
  • Flatten
  • ExpandDims
  • Concatenate
  • Embedding
  • RepeatVector
  • Gather
  • Max
  • Dropout
  • BatchNormalization
  • Conv1D
  • Conv2D
  • Conv3D
  • MaxPooling1D
  • MaxPooling2D
  • MaxPooling3D
  • AveragePooling1D
  • AveragePooling2D
  • AveragePooling3D
  • GlobalMaxPooling1D
  • GlobalMaxPooling2D
  • GlobalMaxPooling3D
  • GlobalAveragePooling1D
  • GlobalAveragePooling2D
  • GlobalAveragePooling3D
  • SimpleRNN
  • LSTM
  • GRU
  • Attention
• Activations
  • ReLU
  • Sigmoid
  • Softmax
  • Tanh
• Losses
  • MeanSquaredError
  • BinaryCrossEntropy
  • CategoricalCrossEntropy
  • SparseCategoricalCrossEntropy
  • Huber
• Optimizers
  • SGD
  • Adam
  • RMSprop
• Gradient
  • Variable
  • GradientTape
  • GraphFunction
  • add
  • sub
  • mul
  • div
  • square
  • sqrt
  • exp
  • log
  • matmul
  • reduceMean
• Datasets
  • MNIST
  • Fashion-MNIST
  • CIFAR-10
• Data\Dataset
  • NDArrayDataset
  • CSVDataset
  • ClassifiedDirectoryDataset
• Data\Sequence
  • Preprocessor
  • Tokenizer
  • TextClassifiedDataset
• Data\Image
  • ImageFilter
  • ImageDataGenerator
  • ImageClassifiedDataset