tiny_dnn  1.0.0
A header only, dependency-free deep learning framework in C++11
tiny_dnn::network< NetType > Member List

This is the complete list of members for tiny_dnn::network< NetType >, including all inherited members.

at(size_t index) consttiny_dnn::network< NetType >inline
at(size_t index) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
begin() (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
begin() const (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
bias_init(const BiasInit &f)tiny_dnn::network< NetType >inline
const_iterator typedef (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >
construct_graph (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >friend
construct_graph (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >friend
depth() consttiny_dnn::network< NetType >inline
end() (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
end() const (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
fast_load(const char *filepath)tiny_dnn::network< NetType >inline
fit(Optimizer &optimizer, const std::vector< T > &inputs, const std::vector< U > &desired_outputs, size_t batch_size, int epoch, OnBatchEnumerate on_batch_enumerate, OnEpochEnumerate on_epoch_enumerate, const bool reset_weights=false, const int n_threads=CNN_TASK_SIZE, const std::vector< U > &t_cost=std::vector< U >())tiny_dnn::network< NetType >inline
fit(Optimizer &optimizer, const std::vector< T > &inputs, const std::vector< U > &desired_outputs, size_t batch_size=1, int epoch=1)tiny_dnn::network< NetType >inline
fprop_max(const vec_t &in, int idx=0) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inlineprotected
fprop_max_index(const vec_t &in) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inlineprotected
from_archive(InputArchive &ar, content_type what=content_type::weights_and_model) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
from_json(const std::string &json_string)tiny_dnn::network< NetType >inline
get_loss(const std::vector< vec_t > &in, const std::vector< vec_t > &t)tiny_dnn::network< NetType >inline
get_loss(const std::vector< T > &in, const std::vector< tensor_t > &t)tiny_dnn::network< NetType >inline
gradient_check(const std::vector< tensor_t > &in, const std::vector< std::vector< label_t >> &t, float_t eps, grad_check_mode mode)tiny_dnn::network< NetType >inline
has_same_weights(const network< T > &rhs, float_t eps) consttiny_dnn::network< NetType >inline
in_data_size() consttiny_dnn::network< NetType >inline
init_weight()tiny_dnn::network< NetType >inline
iterator typedef (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >
layer_size() consttiny_dnn::network< NetType >inline
load(const std::string &filename, content_type what=content_type::weights_and_model, file_format format=file_format::binary) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
load(std::istream &is) (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
name() consttiny_dnn::network< NetType >inline
network(const std::string &name="") (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inlineexplicit
operator<< (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >friend
operator[](size_t index) consttiny_dnn::network< NetType >inline
operator[](size_t index)tiny_dnn::network< NetType >inline
out_data_size() consttiny_dnn::network< NetType >inline
predict(const vec_t &in)tiny_dnn::network< NetType >inline
predict(const tensor_t &in)tiny_dnn::network< NetType >inline
predict(const std::vector< tensor_t > &in)tiny_dnn::network< NetType >inline
predict(const Range &in)tiny_dnn::network< NetType >inline
predict_label(const vec_t &in)tiny_dnn::network< NetType >inline
predict_max_value(const vec_t &in)tiny_dnn::network< NetType >inline
save(const std::string &filename, content_type what=content_type::weights_and_model, file_format format=file_format::binary) const (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
save(std::ostream &os) consttiny_dnn::network< NetType >inline
set_netphase(net_phase phase)tiny_dnn::network< NetType >inline
test(const std::vector< vec_t > &in, const std::vector< label_t > &t)tiny_dnn::network< NetType >inline
test(const std::vector< vec_t > &in)tiny_dnn::network< NetType >inline
to_archive(OutputArchive &ar, content_type what=content_type::weights_and_model) const (defined in tiny_dnn::network< NetType >)tiny_dnn::network< NetType >inline
to_json() consttiny_dnn::network< NetType >inline
train(Optimizer &optimizer, const std::vector< vec_t > &inputs, const std::vector< label_t > &class_labels, size_t batch_size, int epoch, OnBatchEnumerate on_batch_enumerate, OnEpochEnumerate on_epoch_enumerate, const bool reset_weights=false, const int n_threads=CNN_TASK_SIZE, const std::vector< vec_t > &t_cost=std::vector< vec_t >())tiny_dnn::network< NetType >inline
train(Optimizer &optimizer, const std::vector< vec_t > &inputs, const std::vector< label_t > &class_labels, size_t batch_size=1, int epoch=1)tiny_dnn::network< NetType >inline
train(Optimizer &optimizer, const std::vector< vec_t > &in, const std::vector< vec_t > &t, size_t batch_size=1, int epoch=1)tiny_dnn::network< NetType >inline
weight_init(const WeightInit &f)tiny_dnn::network< NetType >inline