AIfES 2 2.0.0
aifes_core.h
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1
31#ifndef AIFES_CORE
32#define AIFES_CORE
33
34#include "aifes_math.h"
35#include "aifes_config.h"
36
37#define TRUE 1
38#define FALSE 0
39
40// ToDo: Make enum from the values
41#define AILAYER_RESULT_LOWER_BOUND 0
42#define AILAYER_RESULT_UPPER_BOUND 1
43#define AILAYER_DELTAS_LOWER_BOUND 2
44#define AILAYER_DELTAS_UPPER_BOUND 3
45
46typedef struct ailayer ailayer_t;
47typedef struct ailoss ailoss_t;
48typedef struct aimodel aimodel_t;
49typedef struct aiopti aiopti_t;
50
54
55
83 const char *name;
92 void (*print_specs)(const ailayer_t *self);
93};
94
122 const char *name;
131 void (*print_specs)(const ailoss_t *self);
132};
133
161 const char *name;
170 void (*print_specs)(const aiopti_t *self);
171};
172
181struct aimodel {
185 uint16_t layer_count;
189};
190
191
252struct ailayer {
260 ailayer_t *input_layer;
261 //ailayer_t *brother_input_layer; /**< (NOT_IN_USE) Chained list if multiple input layer are present else NULL. */
262
263 ailayer_t *output_layer;
264 //ailayer_t *brother_output_layer; /**< (NOT_IN_USE) Chained list if multiple output layer are present else NULL. */
266
271 ailayer_t *next_scheduled;
272 ailayer_t *prev_scheduled;
274
284
293
298 void (*forward)(ailayer_t *self);
299
300 // Maybe for later purpose
301 //void (*sizeof_infmem)(struct aifes_layer_t *, void *);
302 //void (*set_infmem)(struct aifes_layer_t *, void *);
303
304 // ------------------ Used for training only: -----------------------
305
317 void **optimem;
319
324 void (*backward)(ailayer_t *self);
325
334 uint32_t (*sizeof_paramem)(const ailayer_t *self);
335 void (*set_paramem)(ailayer_t *self, void* memory_ptr);
337
345 uint32_t (*sizeof_trainmem)(const ailayer_t *self);
346 void (*set_trainmem)(ailayer_t *self, void* memory_ptr);
348};
349
350
358struct ailoss {
370 void (*calc_loss)(ailoss_t *self, const aitensor_t *target_data, void *result);
371
377 void (*calc_delta)(ailoss_t *self, const aitensor_t *target_data);
378};
379
380
411struct aiopti {
423 uint32_t (*sizeof_optimem)(aiopti_t *self, const aitensor_t *params);
424
432 void (*init_optimem)(aiopti_t *self, const aitensor_t *params, const aitensor_t *gradients, void *optimem);
433
439 void (*zero_gradients)(aiopti_t *self, aitensor_t *gradients);
440
445 void (*begin_step)(aiopti_t *self);
446
454 void (*update_params)(aiopti_t *self, aitensor_t *params, const aitensor_t *gradients, void *optimem);
455
460 void (*end_step)(aiopti_t *self);
461};
462
463
464#endif // AIFES_CORE
AIfES 2 math interface.
Type indicator of the layer.
Definition: aifes_core.h:82
void(* print_specs)(const ailayer_t *self)
Set a function to print specs of the layer (for example size, constants)
Definition: aifes_core.h:92
const char * name
Name of the layer type (for example "Dense")
Definition: aifes_core.h:83
Type indicator of the loss to check for the loss type.
Definition: aifes_core.h:121
void(* print_specs)(const ailoss_t *self)
Set a function to print specs of the loss.
Definition: aifes_core.h:131
const char * name
Name of the loss type (for example "Mean Squared Error")
Definition: aifes_core.h:122
Type indicator of the optimizer to check for the optimizer type.
Definition: aifes_core.h:160
void(* print_specs)(const aiopti_t *self)
Set a function to print specs of the optimizer.
Definition: aifes_core.h:170
const char * name
Name of the optimizer type (for example "ADAM")
Definition: aifes_core.h:161
AIfES layer interface.
Definition: aifes_core.h:252
void ** optimem
Array of memory pointers with length trainable_params_count.
Definition: aifes_core.h:317
aitensor_t result
The result of the forward function is stored here.
Definition: aifes_core.h:275
void(* set_paramem)(ailayer_t *self, void *memory_ptr)
Set and distribute the memory block internally.
Definition: aifes_core.h:335
void(* backward)(ailayer_t *self)
Calculate the backward pass and write the result to the deltas tensor.
Definition: aifes_core.h:324
const aicore_layertype_t * layer_type
Type of the layer (for example ailayer_dense_type)
Definition: aifes_core.h:253
void * layer_configuration
Layer specific configurations (back-link from abstract layer class to implementation)
Definition: aifes_core.h:254
uint8_t trainable_params_count
Number of trainable parameter tensors.
Definition: aifes_core.h:314
void(* set_trainmem)(ailayer_t *self, void *memory_ptr)
Set and distribute the memory block internally.
Definition: aifes_core.h:346
void(* forward)(ailayer_t *self)
Calculate the forward pass and write the result to the result tensor.
Definition: aifes_core.h:298
void(* calc_result_shape)(ailayer_t *self)
Calculate and write the shape to the result tensor.
Definition: aifes_core.h:283
aitensor_t deltas
The result of the backward function is stored here.
Definition: aifes_core.h:306
aitensor_t ** trainable_params
Array of tensor pointers with length trainable_params_count.
Definition: aifes_core.h:315
void(* calc_result_tensor_params)(ailayer_t *self)
If available, calculate and set the tensor_params of the result tensor.
Definition: aifes_core.h:292
uint32_t(* sizeof_paramem)(const ailayer_t *self)
Size of required memory (in bytes).
Definition: aifes_core.h:334
aitensor_t ** gradients
Array of tensor pointers with length trainable_params_count.
Definition: aifes_core.h:316
uint32_t(* sizeof_trainmem)(const ailayer_t *self)
Size of required memory (in bytes).
Definition: aifes_core.h:345
AIfES loss interface.
Definition: aifes_core.h:358
void * loss_configuration
Loss specific configurations (back-link from abstract loss class to implementation)
Definition: aifes_core.h:360
const aicore_losstype_t * loss_type
Type of the loss (for example ailoss_mse_type)
Definition: aifes_core.h:359
ailayer_t connection_layer
Dummy layer for docking to the layer structure.
Definition: aifes_core.h:362
void(* calc_delta)(ailoss_t *self, const aitensor_t *target_data)
Calculate the error on the target data and write it to the deltas tensor of connection layer.
Definition: aifes_core.h:377
void(* calc_loss)(ailoss_t *self, const aitensor_t *target_data, void *result)
Calculate the loss / cost for the model on the given targets.
Definition: aifes_core.h:370
Indicator for the used datatype.
Definition: aifes_math.h:47
AIfES artificial neural network model.
Definition: aifes_core.h:181
uint16_t trainable_params_count
Total number of trainable parameter tensors.
Definition: aifes_core.h:186
uint16_t layer_count
Total number of layers of the model (usually autogenerated).
Definition: aifes_core.h:185
ailayer_t * input_layer
Input layer of the model that gets the input data.
Definition: aifes_core.h:182
ailayer_t * output_layer
Output layer of the model.
Definition: aifes_core.h:183
ailoss_t * loss
The loss or cost function of the model (only for training).
Definition: aifes_core.h:188
AIfES optimizer interface.
Definition: aifes_core.h:411
void * optimizer_configuration
Optimizer specific configurations (back-link from abstract aiopti class to implementation)
Definition: aifes_core.h:413
void(* init_optimem)(aiopti_t *self, const aitensor_t *params, const aitensor_t *gradients, void *optimem)
Initialize the optimization memory for a trainable parameter tensor.
Definition: aifes_core.h:432
void(* begin_step)(aiopti_t *self)
Called in the beginning of every model optimization step for parameter initialization.
Definition: aifes_core.h:445
const aicore_optitype_t * optimizer_type
Type of the optimizer (for example aiopti_sgd_type)
Definition: aifes_core.h:412
void(* update_params)(aiopti_t *self, aitensor_t *params, const aitensor_t *gradients, void *optimem)
Performs an optimization step on the given tensor.
Definition: aifes_core.h:454
uint32_t(* sizeof_optimem)(aiopti_t *self, const aitensor_t *params)
Calculates the optimization memory size for a trainable parameter tensor.
Definition: aifes_core.h:423
void * learning_rate
The learning rate configures the training speed.
Definition: aifes_core.h:416
const aimath_dtype_t * dtype
The data-type of the parameter that the optimizer can optimize and the learning rate.
Definition: aifes_core.h:414
void(* zero_gradients)(aiopti_t *self, aitensor_t *gradients)
Set the gradient tensor to zero.
Definition: aifes_core.h:439
void(* end_step)(aiopti_t *self)
Called in the end of every model optimization step.
Definition: aifes_core.h:460
A tensor in AIfES.
Definition: aifes_math.h:92