Inheritance diagram for micNode:
Public Member Functions | |
| int | init_wgts_rand (float min_range, float max_range) |
| int | init_wgts_rand_normal (float mean, float std) |
| int | fill_input_node (int *perm, int len, MedMat< float > &x_mat, int last_is_bias_flag) |
| int | fill_output_node (int *perm, int len, MedMat< float > &y_mat, vector< float > &sample_weights) |
| int | get_input_batch (int do_grad_flag) |
| int | forward_batch (int do_grad_flag) |
| int | forward_batch_leaky_relu (int do_grad_flag) |
| int | forward_batch_normalization (int do_grad_flag) |
| int | forward_batch_softmax (int do_grad_flag) |
| int | forward_batch_regression (int do_grad_flag) |
| void | forward_batch (const vector< MedMat< float > > &nodes_outputs, MedMat< float > &out) const |
| void | get_input_batch (const vector< MedMat< float > > &nodes_out, MedMat< float > &in) const |
| void | forward_batch_leaky_relu (const MedMat< float > &in, MedMat< float > &out) const |
| void | forward_batch_normalization (const MedMat< float > &in, MedMat< float > &out) const |
| void | forward_batch_softmax (const MedMat< float > &in, MedMat< float > &out) const |
| void | forward_batch_regression (const MedMat< float > &in, MedMat< float > &out) const |
| int | back_propagete_from (micNode *next) |
| int | get_backprop_delta () |
| int | weights_gd_step () |
| int | weights_normalization_step () |
| void | print (const string &prefix, int i_state, int i_in) |
 Public Member Functions inherited from SerializableObject | |
| virtual int | version () const |
| Relevant for serializations. | |
| virtual string | my_class_name () const |
| For better handling of serializations it is highly recommended that each SerializableObject inheriting class will implement the next method. | |
| virtual void | serialized_fields_name (vector< string > &field_names) const |
| The names of the serialized fields. | |
| virtual void * | new_polymorphic (string derived_name) |
| for polymorphic classes that want to be able to serialize/deserialize a pointer * to the derived class given its type one needs to implement this function to return a new to the derived class given its type (as in my_type) | |
| virtual void | pre_serialization () |
| virtual void | post_deserialization () |
| virtual size_t | get_size () |
| Gets bytes sizes for serializations. | |
| virtual size_t | serialize (unsigned char *blob) |
| Serialiazing object to blob memory. return number ob bytes wrote to memory. | |
| virtual size_t | deserialize (unsigned char *blob) |
| Deserialiazing blob to object. returns number of bytes read. | |
| size_t | serialize_vec (vector< unsigned char > &blob) |
| size_t | deserialize_vec (vector< unsigned char > &blob) |
| virtual size_t | serialize (vector< unsigned char > &blob) |
| virtual size_t | deserialize (vector< unsigned char > &blob) |
| virtual int | read_from_file (const string &fname) |
| read and deserialize model | |
| virtual int | write_to_file (const string &fname) |
| serialize model and write to file | |
| virtual int | read_from_file_unsafe (const string &fname) |
| read and deserialize model without checking version number - unsafe read | |
| int | init_from_string (string init_string) |
| Init from string. | |
| int | init_params_from_file (string init_file) |
| int | init_param_from_file (string file_str, string ¶m) |
| virtual int | init (map< string, string > &map) |
| Virtual to init object from parsed fields. | |
| int | update_from_string (const string &init_string) |
| virtual int | update (map< string, string > &map) |
| Virtual to update object from parsed fields. | |
| virtual string | object_json () const |
Data Fields | |
| int | id |
| string | type |
| string | subtype |
| string | name |
| string | loss |
| int | n_in |
| int | k_out |
| MedMat< float > | wgt |
| vector< float > | dropout_in |
| vector< float > | dropout_out |
| MedMat< int > | sparse_bit |
| InputRules | ir |
| vector< int > | forward_nodes |
| int | is_terminal |
| MedMat< float > | lr_params |
| MedMat< float > | lambda |
| MedMat< float > | learn_rates |
| float | momentum |
| float | rate_factor |
| float | max_wgt_norm |
| float | min_wgt_norm |
| float | dropout_prob_in |
| float | dropout_prob_out |
| float | sparse_zero_prob |
| MedMat< float > | batch_in |
| MedMat< float > | batch_out |
| MedMat< float > | grad_w |
| MedMat< float > | grad_s |
| MedMat< float > | delta |
| MedMat< float > | prev_grad_w |
| vector< float > | b_mean |
| vector< float > | b_var |
| vector< float > | alpha |
| vector< float > | beta |
| float | normalization_update_factor |
| vector< double > | curr_mean |
| vector< double > | curr_var |
| int | n_categ |
| int | n_per_categ |
| MedMat< float > | full_probs |
| int | data_node |
| micNode * | data_node_p |
| micNet * | my_net |
| MedMat< float > | y |
| vector< float > | sweights |
| int | update_weights_flag |
| int | only_forward_flag |
| std::default_random_engine | gen |
The documentation for this class was generated from the following files:
- Internal/micNet/micNet/micNet.h
- Internal/micNet/micNet/micNet.cpp
