tiny_dnn
1.0.0
A header only, dependency-free deep learning framework in C++11
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This is the complete list of members for tiny_dnn::network< NetType >, including all inherited members.
at(size_t index) const | tiny_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() const | tiny_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) const | tiny_dnn::network< NetType > | inline |
in_data_size() const | tiny_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() const | tiny_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() const | tiny_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) const | tiny_dnn::network< NetType > | inline |
operator[](size_t index) | tiny_dnn::network< NetType > | inline |
out_data_size() const | tiny_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) const | tiny_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() const | 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, 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 |