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#* DNN::Param
#* DNN::Tensor
#* Float
#* Integer
#** DNN::Param
#** DNN::Tensor
#+ DNN::Param
#+ Integer
#+ DNN::Tensor
#+ Float
#+@ DNN::Param
#+@ DNN::Tensor
#- DNN::Tensor
#- Float
#- Integer
#- DNN::Param
#-@ DNN::Tensor
#-@ DNN::Param
#/ DNN::Param
#/ Float
#/ Integer
#/ DNN::Tensor
#<< DNN::Layers::Layer
#>> DNN::Tensor
#_backward_cpu DNN::Layers::Reshape
#_backward_gpu DNN::Layers::Reshape
#_forward_cpu DNN::Layers::Reshape
#_forward_gpu DNN::Layers::Reshape
#activation DNN::Layers::SimpleRNN
#add DNN::Models::Sequential
#add_callback DNN::Models::Model
#add_lambda_callback DNN::Models::Model
#after_epoch DNN::Callbacks::CheckPoint
#after_epoch DNN::Callbacks::EarlyStopping
#after_epoch DNN::Callbacks::Logger
#after_train_on_batch DNN::Callbacks::EarlyStopping
#after_train_on_batch DNN::Callbacks::NaNStopping
#after_train_on_batch DNN::Callbacks::Logger
align_ndim DNN::Layers::MathUtils
#alpha DNN::Layers::LeakyReLU
#alpha DNN::Optimizers::Adam
#alpha DNN::Optimizers::RMSPropGraves
#alpha DNN::Optimizers::RMSProp
#alpha DNN::Layers::ELU
#amsgrad DNN::Optimizers::Adam
#axis DNN::Layers::BatchNormalization
#axis DNN::Layers::Mean
#axis DNN::Layers::Split
#axis DNN::Layers::Sum
#axis DNN::Layers::Concatenate
#backward DNN::Param
#backward DNN::Link
#backward DNN::Layers::GRUCell
#backward DNN::Layers::SimpleRNNCell
#backward DNN::Layers::LSTMCell
#backward_node DNN::Layers::Lasso
#backward_node DNN::Layers::Conv2D
#backward_node DNN::Layers::LeakyReLU
#backward_node DNN::Layers::Div
#backward_node DNN::Losses::Hinge
#backward_node DNN::Losses::MeanAbsoluteError
#backward_node DNN::Losses::HuberLoss
#backward_node DNN::Layers::Neg
#backward_node DNN::Layers::BatchNormalization
#backward_node DNN::Layers::Sum
#backward_node DNN::Losses::MeanSquaredError
#backward_node DNN::Layers::Embedding
#backward_node DNN::Layers::Exp
#backward_node DNN::Layers::Dropout
#backward_node DNN::Layers::Mean
#backward_node DNN::Layers::Log
#backward_node DNN::Layers::Sub
#backward_node DNN::Layers::Dense
#backward_node DNN::Layers::Sigmoid
#backward_node DNN::Layers::Dot
#backward_node DNN::Layers::LayerNode
#backward_node DNN::Layers::Softplus
#backward_node DNN::Layers::Swish
#backward_node DNN::Layers::Reshape
#backward_node DNN::Layers::ReLU
#backward_node DNN::Layers::Pow
#backward_node DNN::Losses::SoftmaxCrossEntropy
#backward_node DNN::Layers::Softsign
#backward_node DNN::Layers::Mul
#backward_node DNN::Layers::Conv2DTranspose
#backward_node DNN::Layers::AvgPool2D
#backward_node DNN::Layers::UnPool2D
#backward_node DNN::Layers::Sqrt
#backward_node DNN::Layers::Ridge
#backward_node DNN::Layers::Mish
#backward_node DNN::Layers::LSTM
#backward_node DNN::Layers::Tanh
#backward_node DNN::Losses::SigmoidCrossEntropy
#backward_node DNN::Layers::Concatenate
#backward_node DNN::Layers::MaxPool2D
#backward_node DNN::Layers::Split
#backward_node DNN::Layers::Add
#backward_node DNN::Layers::RNN
#backward_node DNN::Layers::ELU
#beta DNN::Layers::BatchNormalization
#beta1 DNN::Optimizers::Adam
#beta2 DNN::Optimizers::Adam
#bias DNN::Layers::Connection
#bias_initializer DNN::Layers::Connection
#bias_regularizer DNN::Layers::Connection
broadcast_to DNN::Layers::MathUtils
broadcast_to DNN::Utils
#build DNN::Layers::GRU
#build DNN::Layers::Dense
#build DNN::Layers::GlobalAvgPool2D
#build DNN::Layers::RNN
#build DNN::Layers::InputLayer
#build DNN::Layers::SimpleRNN
#build DNN::Layers::Conv2DTranspose
#build DNN::Layers::Conv2D
#build DNN::Layers::LSTM
#build DNN::Layers::UnPool2D
#build DNN::Layers::BatchNormalization
#build DNN::Layers::Pool2D
#build DNN::Layers::Layer
#build DNN::Layers::Embedding
#built? DNN::Models::Model
#built? DNN::Layers::Layer
calc_conv2d_out_size DNN::Layers::Conv2DUtils
calc_conv2d_padding_size DNN::Layers::Conv2DUtils
calc_conv2d_transpose_out_size DNN::Layers::Conv2DUtils
calc_conv2d_transpose_padding_size DNN::Layers::Conv2DUtils
#call DNN::Models::Model
#call DNN::Models::Chain
call DNN::Layers::Layer
#call DNN::Layers::MergeLayer
#call DNN::Losses::Loss
call DNN::Losses::Loss
call DNN::Layers::MergeLayer
#call DNN::Layers::Layer
#call_callbacks DNN::Models::Model
#cell DNN::Layers::LSTM
#check_early_stop_requested DNN::Models::Model
check_input_data_type DNN::Utils
#clean DNN::Losses::Loss
#clean DNN::Layers::Layer
#clean DNN::Layers::TrainableLayer
#clean_layers DNN::Models::Model
#clear_callbacks DNN::Models::Model
#clip_norm DNN::Optimizers::Optimizer
col2im DNN::Layers::Conv2DUtils
col2im_cpu DNN::Layers::Conv2DUtils
col2im_gpu DNN::Layers::Conv2DUtils
#compute_output_shape DNN::Layers::Conv2DTranspose
#compute_output_shape DNN::Layers::Reshape
#compute_output_shape DNN::Layers::UnPool2D
#compute_output_shape DNN::Layers::Conv2D
#compute_output_shape DNN::Layers::Flatten
#compute_output_shape DNN::Layers::Dense
#compute_output_shape DNN::Layers::Layer
#compute_output_shape DNN::Layers::Pool2D
#compute_output_shape DNN::Layers::RNN
#const DNN::Initializers::Const
convert DNN::Tensor
#convert KerasModelConvertor
#convert_layers KerasModelConvertor
#copy DNN::Models::Model
#create_hidden_layer DNN::Layers::SimpleRNN
#create_hidden_layer DNN::Layers::GRU
#create_hidden_layer DNN::Layers::LSTM
cudnn_available? DNN
cumo2numo DNN::Utils
#data DNN::Tensor
#data DNN::Param
#dim DNN::Layers::Split
#dnn__add Float
#dnn__add Integer
#dnn__div Integer
#dnn__div Float
#dnn__mul Integer
#dnn__mul Float
#dnn__sub Integer
#dnn__sub Float
#dnn__to_h Hash
#download DNN::Downloader
download DNN::Downloader
downloads DNN::STL10
downloads DNN::Iris
downloads DNN::CIFAR100
downloads DNN::CIFAR10
downloads DNN::FashionMNIST
downloads DNN::MNIST
#dropout_ratio DNN::Layers::Dropout
#dump_bin DNN::Savers::MarshalSaver
#dump_bin DNN::Savers::JSONSaver
#dump_bin DNN::Savers::Saver
#eps DNN::Optimizers::RMSPropGraves
#eps DNN::Optimizers::AdaGrad
#eps DNN::Optimizers::Adam
#eps DNN::Layers::BatchNormalization
#eps DNN::Optimizers::RMSProp
#eps DNN::Optimizers::AdaDelta
#eps DNN::Losses::SigmoidCrossEntropy
#eps DNN::Losses::SoftmaxCrossEntropy
#evaluate DNN::Models::Model
#evaluate_by_iterator DNN::Models::Model
#evaluating? DNN::Models::ModelEvaluator
#filter_size DNN::Layers::Conv2D
#filter_size DNN::Layers::Conv2DTranspose
#filters DNN::Layers::Conv2DTranspose
#filters DNN::Layers::Conv2D
#filters= DNN::Layers::Conv2D
#filters= DNN::Layers::Conv2DTranspose
#final_lr DNN::Optimizers::AdaBound
#foreach DNN::Iterator
#forward DNN::Models::FixedModel
#forward DNN::Models::Sequential
#forward DNN::Layers::LayerNode
#forward DNN::Layers::Softmax
#forward DNN::Layers::Layer
#forward DNN::Layers::LSTMCell
#forward DNN::Layers::InputLayer
#forward DNN::Layers::SimpleRNNCell
#forward DNN::Regularizers::L1L2
#forward DNN::Layers::GlobalAvgPool2D
#forward DNN::Layers::Flatten
#forward DNN::Models::Chain
#forward DNN::Regularizers::Regularizer
#forward DNN::Losses::Loss
#forward DNN::Link
#forward DNN::Regularizers::L1
#forward DNN::Regularizers::L2
#forward DNN::Layers::GRUCell
#forward_node DNN::Layers::Sub
#forward_node DNN::Layers::Embedding
#forward_node DNN::Layers::Sqrt
#forward_node DNN::Layers::Sum
#forward_node DNN::Layers::Conv2D
#forward_node DNN::Layers::Mish
#forward_node DNN::Layers::Log
#forward_node DNN::Layers::Dropout
#forward_node DNN::Layers::LayerNode
#forward_node DNN::Layers::Exp
#forward_node DNN::Layers::Neg
#forward_node DNN::Layers::Pow
#forward_node DNN::Layers::Split
#forward_node DNN::Layers::Concatenate
#forward_node DNN::Layers::ReLU
#forward_node DNN::Losses::SigmoidCrossEntropy
#forward_node DNN::Layers::Add
#forward_node DNN::Layers::Reshape
#forward_node DNN::Layers::AvgPool2D
#forward_node DNN::Losses::MeanAbsoluteError
#forward_node DNN::Losses::Hinge
#forward_node DNN::Losses::HuberLoss
#forward_node DNN::Losses::SoftmaxCrossEntropy
#forward_node DNN::Losses::MeanSquaredError
#forward_node DNN::Layers::Mul
#forward_node DNN::Layers::Dot
#forward_node DNN::Layers::Sigmoid
#forward_node DNN::Layers::Mean
#forward_node DNN::Layers::Div
#forward_node DNN::Layers::LSTM
#forward_node DNN::Layers::RNN
#forward_node DNN::Layers::Softsign
#forward_node DNN::Layers::Ridge
#forward_node DNN::Layers::Lasso
#forward_node DNN::Layers::BatchNormalization
#forward_node DNN::Layers::LeakyReLU
#forward_node DNN::Layers::UnPool2D
#forward_node DNN::Layers::ELU
#forward_node DNN::Layers::Conv2DTranspose
#forward_node DNN::Layers::Softplus
#forward_node DNN::Layers::MaxPool2D
#forward_node DNN::Layers::Dense
#forward_node DNN::Layers::Swish
#forward_node DNN::Layers::Tanh
from_binary DNN::Image
from_hash DNN::Initializers::Initializer
from_hash DNN::Layers::Layer
from_hash DNN::Losses::Loss
from_hash DNN::Regularizers::Regularizer
from_hash DNN::Optimizers::Optimizer
from_hash_list DNN::Models::LayersList
from_na Numpy
#gamma DNN::Optimizers::AdaBound
#gamma DNN::Layers::BatchNormalization
#get_all_params_data DNN::Models::Model
#get_all_trainable_params DNN::Models::Model
#get_layer DNN::Models::Model
#get_log DNN::Callbacks::Logger
#get_params DNN::Layers::RNN
#get_params DNN::Layers::TrainableLayer
#get_params DNN::Layers::Embedding
#get_params DNN::Layers::BatchNormalization
#get_params DNN::Layers::LSTM
#get_params DNN::Layers::Connection
#grad DNN::Param
#has_next? DNN::Iterator
hash_to_obj DNN::Utils
#hidden DNN::Layers::RNN
im2col DNN::Layers::Conv2DUtils
im2col_cpu DNN::Layers::Conv2DUtils
im2col_gpu DNN::Layers::Conv2DUtils
#init_param DNN::Initializers::He
#init_param DNN::Initializers::Xavier
#init_param DNN::Initializers::RandomNormal
#init_param DNN::Initializers::Const
#init_param DNN::Initializers::Zeros
#init_param DNN::Initializers::RandomUniform
#init_param DNN::Initializers::Initializer
#initialize DNN::Initializers::He
#initialize DNN::Initializers::Xavier
#initialize DNN::Initializers::RandomNormal
#initialize DNN::Initializers::RandomUniform
#initialize DNN::Initializers::Const
#initialize DNN::Initializers::Initializer
#initialize DNN::Layers::RNNCell
#initialize DNN::Optimizers::AdaBound
#initialize DNN::Optimizers::Adam
#initialize DNN::Layers::RNN
#initialize DNN::Optimizers::RMSPropGraves
#initialize DNN::Optimizers::AdaDelta
#initialize DNN::Layers::Pow
#initialize DNN::Optimizers::RMSProp
#initialize DNN::Optimizers::AdaGrad
#initialize DNN::Optimizers::Nesterov
#initialize DNN::Layers::Ridge
#initialize DNN::Optimizers::SGD
#initialize DNN::Optimizers::Optimizer
#initialize DNN::Layers::InputLayer
#initialize DNN::Callbacks::LambdaCallback
#initialize DNN::Callbacks::CheckPoint
#initialize DNN::Callbacks::EarlyStopping
#initialize DNN::Callbacks::Logger
#initialize DNN::Iterator
#initialize DNN::Layers::Concatenate
#initialize DNN::Tensor
#initialize DNN::Savers::MarshalSaver
#initialize DNN::Savers::Saver
#initialize DNN::Models::FixedModel
#initialize DNN::Models::Sequential
#initialize DNN::Loaders::Loader
#initialize DNN::Layers::Conv2D
#initialize DNN::Layers::Connection
#initialize DNN::Models::ModelEvaluator
#initialize DNN::Layers::Mean
#initialize DNN::Models::ModelTrainer
#initialize DNN::Layers::ELU
#initialize DNN::Layers::Reshape
#initialize DNN::Models::Model
#initialize DNN::Layers::LSTMCell
#initialize DNN::Models::Chain
#initialize DNN::Losses::SigmoidCrossEntropy
#initialize DNN::Layers::Pool2D
#initialize DNN::Losses::SoftmaxCrossEntropy
#initialize DNN::Layers::BatchNormalization
#initialize DNN::Layers::Dense
#initialize DNN::Layers::SimpleRNNCell
#initialize DNN::Layers::Dropout
#initialize DNN::Layers::Sum
#initialize DNN::Param
#initialize DNN::Link
#initialize DNN::Layers::GRUCell
#initialize DNN::Layers::Split
#initialize DNN::Layers::Layer
#initialize DNN::Layers::SimpleRNN
#initialize DNN::Layers::LSTM
#initialize KerasModelConvertor
#initialize DNN::Layers::Embedding
#initialize DNN::Layers::UnPool2D
#initialize DNN::Layers::TrainableLayer
#initialize DNN::Layers::GRU
#initialize DNN::Layers::LeakyReLU
#initialize DNN::Downloader
#initialize DNN::Layers::Lasso
#initialize DNN::Regularizers::L1L2
#initialize DNN::Regularizers::L2
#initialize DNN::Regularizers::L1
#initialize DNN::Layers::Conv2DTranspose
#input_length DNN::Layers::Embedding
#input_shape DNN::Layers::Layer
#insert DNN::Models::Sequential
#keepdims DNN::Layers::Mean
#keepdims DNN::Layers::Sum
#l1_lambda DNN::Regularizers::L1L2
#l1_lambda DNN::Regularizers::L1
#l1_lambda DNN::Layers::Lasso
#l1_lambda= DNN::Regularizers::L1L2
#l1_lambda= DNN::Regularizers::L1
#l2_lambda DNN::Layers::Ridge
#l2_lambda DNN::Regularizers::L1L2
#l2_lambda DNN::Regularizers::L2
#l2_lambda= DNN::Regularizers::L2
#l2_lambda= DNN::Regularizers::L1L2
#last_log DNN::Models::Model
#last_round_down DNN::Iterator
#layer_node DNN::Link
#layers DNN::Models::FixedModel
#layers DNN::Models::Chain
#layers DNN::Models::LayersList
learning_phase DNN
learning_phase= DNN
#link DNN::Tensor
#load DNN::Loaders::Loader
load DNN::Models::Model
load DNN::Iris
load KerasModelConvertor
#load_bin DNN::Loaders::JSONLoader
#load_bin DNN::Loaders::Loader
#load_bin DNN::Loaders::MarshalLoader
#load_hash DNN::Initializers::RandomUniform
#load_hash DNN::Initializers::RandomNormal
#load_hash DNN::Layers::Reshape
#load_hash DNN::Initializers::Initializer
#load_hash DNN::Initializers::Const
#load_hash DNN::Optimizers::AdaBound
#load_hash DNN::Optimizers::Adam
#load_hash DNN::Layers::Lasso
#load_hash DNN::Optimizers::RMSPropGraves
#load_hash DNN::Optimizers::AdaDelta
#load_hash DNN::Optimizers::RMSProp
#load_hash DNN::Optimizers::SGD
#load_hash DNN::Optimizers::AdaGrad
#load_hash DNN::Optimizers::Optimizer
#load_hash DNN::Layers::Dropout
#load_hash DNN::Layers::Ridge
#load_hash DNN::Layers::Sum
#load_hash DNN::Layers::Split
#load_hash DNN::Layers::UnPool2D
#load_hash DNN::Models::Chain
#load_hash DNN::Losses::SigmoidCrossEntropy
#load_hash DNN::Losses::SoftmaxCrossEntropy
#load_hash DNN::Losses::Loss
#load_hash DNN::Layers::Concatenate
#load_hash DNN::Layers::ELU
#load_hash DNN::Layers::BatchNormalization
#load_hash DNN::Layers::Layer
#load_hash DNN::Layers::LeakyReLU
#load_hash DNN::Layers::Mean
#load_hash DNN::Layers::Pool2D
#load_hash DNN::Layers::Dense
#load_hash DNN::Layers::Conv2DTranspose
#load_hash DNN::Layers::InputLayer
#load_hash DNN::Layers::Conv2D
#load_hash DNN::Layers::Embedding
#load_hash DNN::Regularizers::L1L2
#load_hash DNN::Regularizers::L2
#load_hash DNN::Regularizers::L1
#load_hash DNN::Regularizers::Regularizer
#load_hash DNN::Layers::SimpleRNN
#load_hash DNN::Layers::RNN
#load_params DNN::Models::Model
load_test DNN::CIFAR10
load_test DNN::FashionMNIST
load_test DNN::STL10
load_test DNN::MNIST
load_test DNN::CIFAR100
load_train DNN::CIFAR10
load_train DNN::STL10
load_train DNN::MNIST
load_train DNN::CIFAR100
load_train DNN::FashionMNIST
load_unlabeled DNN::STL10
#loss DNN::Losses::Loss
#loss_func DNN::Models::Model
#loss_func= DNN::Models::Model
#loss_weights DNN::Models::Model
#lr DNN::Optimizers::RMSPropGraves
#lr DNN::Optimizers::RMSProp
#lr DNN::Optimizers::AdaGrad
#lr DNN::Optimizers::SGD
#mask_zero DNN::Layers::Embedding
#max DNN::Initializers::RandomUniform
#max_steps DNN::Iterator
#mean DNN::Initializers::RandomNormal
#min DNN::Initializers::RandomUniform
#model DNN::Callbacks::Callback
#momentum DNN::Optimizers::SGD
#momentum DNN::Layers::BatchNormalization
#next DNN::Link
#next_batch DNN::Iterator
#num_datas DNN::Iterator
#num_filters DNN::Layers::Conv2DTranspose
#num_filters DNN::Layers::Conv2D
#num_outputs DNN::Link
#num_units DNN::Layers::RNN
#num_units DNN::Layers::Dense
#num_usable_datas DNN::Iterator
numerical_grad DNN::Utils
numo2cumo DNN::Utils
#optimizer DNN::Models::Model
#output_shape DNN::Layers::Layer
#padding DNN::Layers::Pool2D
#padding DNN::Layers::Conv2DTranspose
#padding DNN::Layers::Conv2D
#param DNN::Regularizers::Regularizer
#pool_size DNN::Layers::Pool2D
#predict DNN::Models::Model
#predict1 DNN::Models::Model
#prevs DNN::Link
read DNN::Image
#recurrent_weight DNN::Layers::RNN
#recurrent_weight_initializer DNN::Layers::RNN
#recurrent_weight_regularizer DNN::Layers::RNN
#regularizers DNN::Layers::RNN
#regularizers DNN::Layers::Embedding
#regularizers DNN::Layers::Connection
#regularizers_forward DNN::Losses::Loss
#remove DNN::Models::Sequential
#request_early_stop DNN::Models::Model
#reset DNN::Iterator
#reset_state DNN::Layers::LSTM
#reset_state DNN::Layers::RNN
resize DNN::Image
#return_sequences DNN::Layers::RNN
#rho DNN::Optimizers::AdaDelta
#running_mean DNN::Layers::BatchNormalization
#running_var DNN::Layers::BatchNormalization
#save DNN::Savers::Saver
#save DNN::Models::Model
#save_params DNN::Models::Model
#set_all_params_data DNN::Models::Model
#setup DNN::Models::Model
#shape DNN::Tensor
#shape DNN::Param
sigmoid DNN::Losses::SigmoidCrossEntropy
sigmoid DNN::Utils
softmax DNN::Losses::SoftmaxCrossEntropy
softmax DNN::Utils
#stack DNN::Models::Sequential
#start_evaluate DNN::Models::ModelEvaluator
#start_evaluate_by_iterator DNN::Models::ModelEvaluator
#start_train DNN::Models::ModelTrainer
#start_train_by_iterator DNN::Models::ModelTrainer
#stateful DNN::Layers::RNN
#status DNN::Optimizers::Optimizer
stbi_load DNN::Stb
stbi_write_bmp DNN::Stb
stbi_write_hdr DNN::Stb
stbi_write_jpg DNN::Stb
stbi_write_png DNN::Stb
stbi_write_tga DNN::Stb
stbir_resize_uint8 DNN::Stb
stbir_resize_uint8_srgb DNN::Stb
stbir_resize_uint8_srgb_edgemode DNN::Stb
#std DNN::Initializers::RandomNormal
#strides DNN::Layers::Pool2D
#strides DNN::Layers::Conv2DTranspose
#strides DNN::Layers::Conv2D
sum_to DNN::Layers::MathUtils
#test_on_batch DNN::Models::Model
#test_step DNN::Models::Model
to_categorical DNN::Utils
#to_cpu DNN::Models::Model
to_f DNN::Utils
#to_gpu DNN::Models::Model
to_gray_scale DNN::Image
#to_h Hash
#to_hash DNN::Layers::SimpleRNN
#to_hash DNN::Layers::RNN
#to_hash DNN::Layers::UnPool2D
#to_hash DNN::Layers::Ridge
#to_hash DNN::Layers::Pool2D
#to_hash DNN::Layers::Conv2D
#to_hash DNN::Layers::Conv2DTranspose
#to_hash DNN::Layers::Embedding
#to_hash DNN::Regularizers::L1L2
#to_hash DNN::Regularizers::L2
#to_hash DNN::Regularizers::L1
#to_hash DNN::Regularizers::Regularizer
#to_hash DNN::Initializers::RandomUniform
#to_hash DNN::Initializers::RandomNormal
#to_hash DNN::Initializers::Const
#to_hash DNN::Initializers::Initializer
#to_hash DNN::Optimizers::AdaBound
#to_hash DNN::Optimizers::Adam
#to_hash DNN::Optimizers::AdaDelta
#to_hash DNN::Optimizers::RMSPropGraves
#to_hash DNN::Optimizers::RMSProp
#to_hash DNN::Optimizers::AdaGrad
#to_hash DNN::Optimizers::SGD
#to_hash DNN::Optimizers::Optimizer
#to_hash DNN::Layers::BatchNormalization
#to_hash DNN::Layers::Split
#to_hash DNN::Models::Chain
#to_hash DNN::Losses::SigmoidCrossEntropy
#to_hash DNN::Losses::SoftmaxCrossEntropy
#to_hash DNN::Losses::Loss
#to_hash DNN::Layers::Lasso
#to_hash DNN::Layers::Reshape
#to_hash DNN::Layers::Dense
#to_hash DNN::Layers::Connection
#to_hash DNN::Layers::InputLayer
#to_hash DNN::Layers::Layer
#to_hash DNN::Layers::Mean
#to_hash DNN::Layers::ELU
#to_hash DNN::Layers::LeakyReLU
#to_hash DNN::Layers::Sum
#to_hash DNN::Layers::Concatenate
#to_hash DNN::Layers::Dropout
#to_hash_list DNN::Models::LayersList
to_na Numpy
#to_proc DNN::Layers::InputLayer
to_rgb DNN::Image
to_rgba DNN::Image
#train DNN::Models::Model
#train_by_iterator DNN::Models::Model
#train_on_batch DNN::Models::Model
#train_step DNN::Models::Model
#trainable DNN::Layers::RNNCell
#trainable DNN::Param
#trainable DNN::Layers::TrainableLayer
#trainable_layers DNN::Models::Model
#training? DNN::Models::ModelTrainer
trim DNN::Image
#unpool_size DNN::Layers::UnPool2D
#update DNN::Optimizers::Optimizer
#update DNN::Models::ModelTrainer
#update DNN::Models::ModelEvaluator
#update_layers DNN::Optimizers::Optimizer
#use_bias DNN::Layers::Connection
use_cudnn? DNN
use_cumo? DNN
#use_scale DNN::Layers::Dropout
#weight DNN::Layers::Embedding
#weight DNN::Layers::Connection
#weight_initializer DNN::Layers::Embedding
#weight_initializer DNN::Layers::Connection
#weight_regularizer DNN::Layers::Embedding
#weight_regularizer DNN::Layers::Connection
write DNN::Image
zero_padding DNN::Layers::Conv2DUtils
zero_padding_bwd DNN::Layers::Conv2DUtils