aifes_core.h

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#ifndef AIFES_CORE
#define AIFES_CORE
 
#include "aifes_math.h"
#include "aifes_config.h"
 
#define TRUE    1
#define FALSE   0
 
#define AILAYER_SETTINGS_TRAINING_MODE                  0
#define AILAYER_SETTINGS_TRAINABLE                      1
#define AILAYER_SETTINGS_BATCH_MODE                     2 // When true, a whole batch is processed in a single forward pass
#define AILAYER_SETTINGS_NO_INPUT_GRADIENT              3 // When true, no input gradient is calculated
#define AILAYER_SETTINGS_KEEP_INPUT_BUFFER_FOR_RESULT   4 // When true, no input gradient is calculated
 
#define AILAYER_SETTINGS_SET(settings, mask, selector, value)   (settings = ((settings) & ~(mask << (selector))) | ((value) << (selector)))
#define AILAYER_SETTINGS_IS(settings, mask, selector)           (((settings) >> (selector)) & mask)
 
typedef struct ailayer  ailayer_t;
typedef struct ailoss   ailoss_t;
typedef struct aimodel  aimodel_t;
typedef struct aiopti   aiopti_t;
 
typedef struct aicore_layertype aicore_layertype_t;
typedef struct aicore_losstype aicore_losstype_t;
typedef struct aicore_optitype aicore_optitype_t;
 
 
struct aicore_layertype {
    const char *name; 
    void (*print_specs)(const ailayer_t *self);
};
 
struct aicore_losstype {
    const char *name; 
    void (*print_specs)(const ailoss_t *self);
};
 
struct aicore_optitype {
    const char *name; 
    void (*print_specs)(const aiopti_t *self);
};
 
struct aimodel {
    ailayer_t *input_layer; 
    ailayer_t *output_layer; 
    uint16_t layer_count; 
    uint16_t trainable_params_count; 
    ailoss_t *loss; 
};
 
 
struct ailayer {
    const aicore_layertype_t *layer_type; 
    void *layer_configuration; 
    uint32_t settings; 
    ailayer_t *input_layer;
    //ailayer_t *brother_input_layer; /**< (NOT_IN_USE) Chained list if multiple input layer are present else NULL. */
 
    ailayer_t *output_layer;
    //ailayer_t *brother_output_layer; /**< (NOT_IN_USE) Chained list if multiple output layer are present else NULL. */
 
    ailayer_t *next_scheduled;
    ailayer_t *prev_scheduled;
 
    aitensor_t result; 
    void (*calc_result_shape)(ailayer_t *self);
 
    void (*calc_result_tensor_params)(ailayer_t *self);
 
    void (*forward)(ailayer_t *self);
 
    // Maybe for later purpose
    //void (*sizeof_infmem)(struct aifes_layer_t *, void *);
    //void (*set_infmem)(struct aifes_layer_t *, void *);
 
    // ------------------ Used for training only: -----------------------
 
    aitensor_t deltas; 
    uint8_t trainable_params_count; 
    aitensor_t **trainable_params; 
    aitensor_t **gradients; 
    void **optimem; 
 
    void (*backward)(ailayer_t *self);
 
    uint32_t (*sizeof_paramem)(const ailayer_t *self); 
    void (*set_paramem)(ailayer_t *self, void* memory_ptr); 
    void (*init_params)(ailayer_t *self); 
 
    uint32_t (*sizeof_fwdmem)(const ailayer_t *self); 
    uint32_t (*sizeof_bwdmem)(const ailayer_t *self); 
    void *tempmem; 
 
    uint32_t (*sizeof_trainmem)(const ailayer_t *self); 
    void (*set_trainmem)(ailayer_t *self, void* memory_ptr); 
};
 
 
struct ailoss {
    const aicore_losstype_t *loss_type; 
    void *loss_configuration; 
    ailayer_t connection_layer; 
    void (*calc_loss)(ailoss_t *self, const aitensor_t *target_data, void *result);
 
    void (*calc_delta)(ailoss_t *self, const aitensor_t *target_data);
};
 
 
struct aiopti {
    const aicore_optitype_t *optimizer_type; 
    void *optimizer_configuration; 
    const aimath_dtype_t *dtype; 
    void *learning_rate; 
    uint32_t (*sizeof_optimem)(aiopti_t *self, const aitensor_t *params);
 
    void (*init_optimem)(aiopti_t *self, const aitensor_t *params, const aitensor_t *gradients, void *optimem);
 
    void (*zero_gradients)(aiopti_t *self, aitensor_t *gradients);
 
    void (*begin_step)(aiopti_t *self);
 
    void (*update_params)(aiopti_t *self, aitensor_t *params, const aitensor_t *gradients, void *optimem);
 
    void (*end_step)(aiopti_t *self);
};
 
 
#endif // AIFES_CORE