Documentation for ruby-dnn (0.16.0)

Alphabetic Index

File Listing

README

Namespace Listing A-Z

A

AdaBound (DNN::Optimizers)
AdaDelta (DNN::Optimizers)
AdaGrad (DNN::Optimizers)
Adam (DNN::Optimizers)
Add (DNN::Layers)
AvgPool2D (DNN::Layers)

B

BatchNormalization (DNN::Layers)

C

CIFAR10 (DNN)
CIFAR100 (DNN)
Callback (DNN::Callbacks)
Callbacks (DNN)
Chain (DNN::Models)
CheckPoint (DNN::Callbacks)
Concatenate (DNN::Layers)
Connection (DNN::Layers)
Const (DNN::Initializers)
Conv2D (DNN::Layers)
Conv2DTranspose (DNN::Layers)
Conv2DUtils (DNN::Layers)

D

DNN
DNN_CIFAR100_LoadError (DNN::CIFAR100)
DNN_CIFAR10_LoadError (DNN::CIFAR10)
DNN_DownloadError (DNN)
DNN_Error (DNN)
DNN_Iris_LoadError (DNN)
DNN_MNIST_LoadError (DNN::MNIST)
DNN_MNIST_LoadError (DNN::FashionMNIST)
DNN_STL10_LoadError (DNN::STL10)
DNN_ShapeError (DNN)
Dense (DNN::Layers)
Div (DNN::Layers)
Dot (DNN::Layers)
Downloader (DNN)
Dropout (DNN::Layers)

E

ELU (DNN::Layers)
EarlyStopping (DNN::Callbacks)
Embedding (DNN::Layers)
Exp (DNN::Layers)

F

FashionMNIST (DNN)
Flatten (DNN::Layers)
Float

G

GRU (DNN::Layers)
GRUDense (DNN::Layers)
GlobalAvgPool2D (DNN::Layers)

H

He (DNN::Initializers)
Hinge (DNN::Losses)
HuberLoss (DNN::Losses)

I

Image (DNN)
ImageError (DNN::Image)
ImageReadError (DNN::Image)
ImageShapeError (DNN::Image)
ImageWriteError (DNN::Image)
Initializer (DNN::Initializers)
Initializers (DNN)
InputLayer (DNN::Layers)
Integer
Iris (DNN)
Iterator (DNN)

J

JSONLoader (DNN::Loaders)
JSONSaver (DNN::Savers)

L

L1 (DNN::Regularizers)
L1L2 (DNN::Regularizers)
L2 (DNN::Regularizers)
LSTM (DNN::Layers)
LSTMDense (DNN::Layers)
LambdaCallback (DNN::Callbacks)
Lasso (DNN::Layers)
Layer (DNN::Layers)
LayerNode (DNN::Layers)
Layers (DNN)
LayersList (DNN::Models)
LeakyReLU (DNN::Layers)
Link (DNN)
Loader (DNN::Loaders)
Loaders (DNN)
Log (DNN::Layers)
Logger (DNN::Callbacks)
Loss (DNN::Losses)
Losses (DNN)

M

MNIST (DNN)
MarshalLoader (DNN::Loaders)
MarshalSaver (DNN::Savers)
MaxPool2D (DNN::Layers)
Mean (DNN::Layers)
MeanAbsoluteError (DNN::Losses)
MeanSquaredError (DNN::Losses)
MergeLayer (DNN::Layers)
MergeLayerNode (DNN::Layers)
Mish (DNN::Layers)
Model (DNN::Models)
Models (DNN)
Mul (DNN::Layers)

N

NaNStopping (DNN::Callbacks)
Nesterov (DNN::Optimizers)

O

Optimizer (DNN::Optimizers)
Optimizers (DNN)

P

Param (DNN)
Pool2D (DNN::Layers)
Pow (DNN::Layers)

R

RMSProp (DNN::Optimizers)
RMSPropGraves (DNN::Optimizers)
RNN (DNN::Layers)
RandomNormal (DNN::Initializers)
RandomUniform (DNN::Initializers)
ReLU (DNN::Layers)
Regularizer (DNN::Regularizers)
Regularizers (DNN)
Reshape (DNN::Layers)
Ridge (DNN::Layers)

S

SGD (DNN::Optimizers)
STL10 (DNN)
Saver (DNN::Savers)
Savers (DNN)
Sequential (DNN::Models)
Sigmoid (DNN::Layers)
SigmoidCrossEntropy (DNN::Losses)
SimpleRNN (DNN::Layers)
SimpleRNNDense (DNN::Layers)
SoftmaxCrossEntropy (DNN::Losses)
Softplus (DNN::Layers)
Softsign (DNN::Layers)
Sqrt (DNN::Layers)
Stb (DNN)
Sub (DNN::Layers)
Sum (DNN::Layers)
Swish (DNN::Layers)

T

Tanh (DNN::Layers)
Tensor (DNN)
TrainableLayer (DNN::Layers)
TwoInputLink (DNN)

U

UnPool2D (DNN::Layers)
Utils (DNN)

X

Xavier (DNN::Initializers)

Z

Zeros (DNN::Initializers)