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#<< DNN::Model
#accurate DNN::Model
#backward DNN::Activations::SigmoidWithLoss
#backward DNN::Activations::ReLU
#backward DNN::Layers::Conv2D
#backward DNN::Layers::Reshape
#backward DNN::Activations::Tanh
#backward DNN::Activations::Sigmoid
#backward DNN::Layers::InputLayer
#backward DNN::Layers::MaxPool2D
#backward DNN::Layers::BatchNormalization
#backward DNN::Layers::Dense
#backward DNN::Activations::IdentityWithLoss
#backward DNN::Activations::SoftmaxWithLoss
#backward DNN::Layers::Layer
#backward DNN::Activations::LeakyReLU
#backward DNN::Layers::Dropout
#backward DNN::Layers::Flatten
#batch_size DNN::Model
#beta1 DNN::Optimizers::Adam
#beta2 DNN::Optimizers::Adam
#col2im DNN::Layers::Convert
#compile DNN::Model
dir DNN::CIFAR10
download DNN::MNIST
downloads DNN::MNIST
#forward DNN::Activations::SoftmaxWithLoss
#forward DNN::Activations::IdentityWithLoss
#forward DNN::Layers::MaxPool2D
#forward DNN::Activations::LeakyReLU
#forward DNN::Layers::Reshape
#forward DNN::Layers::BatchNormalization
#forward DNN::Layers::Dropout
#forward DNN::Activations::SigmoidFunction
#forward DNN::Layers::Flatten
#forward DNN::Activations::ReLU
#forward DNN::Layers::Layer
#forward DNN::Layers::Conv2D
#forward DNN::Layers::InputLayer
#forward DNN::Activations::Tanh
#forward DNN::Layers::Dense
get_minibatch DNN::Util
#grads DNN::Layers::HasParamLayer
#im2col DNN::Layers::Convert
#init DNN::Layers::HasParamLayer
#init DNN::Layers::Layer
#init DNN::Layers::MaxPool2D
#init DNN::Layers::Conv2D
#init_param DNN::Initializers::He
#init_param DNN::Initializers::Xavier
#init_param DNN::Initializers::Initializer
#init_param DNN::Initializers::Zeros
#init_param DNN::Initializers::RandomNormal
#initialize DNN::Layers::InputLayer
#initialize DNN::Layers::HasParamLayer
#initialize DNN::Optimizers::AdaGrad
#initialize DNN::Initializers::RandomNormal
#initialize DNN::Model
#initialize DNN::Optimizers::Adam
#initialize DNN::Optimizers::RMSProp
#initialize DNN::DNN_GradUnfairError
#initialize DNN::Layers::MaxPool2D
#initialize DNN::Layers::Dropout
#initialize DNN::Layers::Dense
#initialize DNN::Layers::Reshape
#initialize DNN::Layers::Conv2D
#initialize DNN::Activations::LeakyReLU
#initialize DNN::Optimizers::Optimizer
#initialize DNN::Optimizers::SGD
#layers DNN::Model
#learning_rate DNN::Optimizers::Optimizer
load DNN::Model
load_images DNN::MNIST
load_labels DNN::MNIST
load_test DNN::MNIST
load_test DNN::CIFAR10
load_train DNN::CIFAR10
load_train DNN::MNIST
#loss DNN::Activations::SoftmaxWithLoss
#loss DNN::Activations::IdentityWithLoss
#loss DNN::Activations::SigmoidWithLoss
mnist_dir DNN::MNIST
#momentum DNN::Optimizers::SGD
#muse DNN::Optimizers::RMSProp
#num_nodes DNN::Layers::Dense
numerical_grad DNN::Util
#optimizer DNN::Model
#padding DNN::Layers::Convert
#params DNN::Layers::HasParamLayer
#predict DNN::Model
#prev_layer DNN::Layers::Layer
read DNN::ImageIO
#save DNN::Model
#shape DNN::Layers::Reshape
#shape DNN::Layers::Flatten
#shape DNN::Layers::MaxPool2D
#shape DNN::Layers::Conv2D
#shape DNN::Layers::Dense
#shape DNN::Layers::InputLayer
#shape DNN::Layers::Layer
#test DNN::Model
to_categorical DNN::Util
#train DNN::Model
#train_on_batch DNN::Model
#training DNN::Model
#update DNN::Optimizers::AdaGrad
#update DNN::Optimizers::RMSProp
#update DNN::Optimizers::Adam
#update DNN::Optimizers::Optimizer
#update DNN::Optimizers::SGD
#update DNN::Layers::HasParamLayer
url_to_file_name DNN::MNIST
#weight_decay DNN::Layers::Dense
write DNN::ImageIO