Deep network
- a -
ActivationLayer() :
Layer::ActivationLayer< A >
- b -
back_propagation() :
Layer::ActivationLayer< A >
,
Layer::ConvolutionLayer
,
Layer::FullConnectedLayer
,
Layer::Layer
,
Layer::Pooling
,
Network
- c -
compute_last_delta() :
Network
ConvolutionLayer() :
Layer::ConvolutionLayer
- d -
Dataset() :
Dataset
- e -
eval() :
Network
- f -
feed_forward() :
Layer::ActivationLayer< A >
,
Layer::ConvolutionLayer
,
Layer::FullConnectedLayer
,
Layer::Layer
,
Layer::Pooling
,
Network
FullConnectedLayer() :
Layer::FullConnectedLayer
- g -
get_input_size() :
Layer::Layer
get_output() :
Layer::Layer
get_output_size() :
Layer::Layer
get_test() :
Dataset
,
Mnist
get_test_size() :
Dataset
get_train() :
Dataset
,
Mnist
get_train_size() :
Dataset
get_y_size() :
Dataset
- i -
init() :
Layer::ConvolutionLayer
,
Layer::FullConnectedLayer
init_nabla() :
Layer::ActivationLayer< A >
,
Layer::ConvolutionLayer
,
Layer::FullConnectedLayer
,
Layer::Layer
,
Layer::Pooling
init_standard() :
Layer::FullConnectedLayer
is_done() :
Network
- l -
Layer() :
Layer::Layer
- m -
Mnist() :
Mnist
- n -
Network() :
Network
- p -
Pooling() :
Layer::Pooling
push_layer() :
Network
- s -
set_cost() :
Network
Shape() :
Shape
shuffle() :
Network
size() :
Shape
- t -
train() :
Network
- u -
update() :
Layer::ActivationLayer< A >
,
Layer::ConvolutionLayer
,
Layer::FullConnectedLayer
,
Layer::Layer
,
Layer::Pooling
update_batch() :
Network
- ~ -
~ActivationLayer() :
Layer::ActivationLayer< A >
~ConvolutionLayer() :
Layer::ConvolutionLayer
~FullConnectedLayer() :
Layer::FullConnectedLayer
~Layer() :
Layer::Layer
~Pooling() :
Layer::Pooling
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