dmlfw (Daniyal Machine Learning Framework)
dmlfw_ml_configurations.h
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1#ifndef __DMLFW__ML_CONFIGURATIONS__
2#define __DMLFW__ML_CONFIGURATIONS__
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91 uint64_t iteration_number,
92 void *y,
93 void *predicted_y,
94 void *model,
95 double regularization_parameter);
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109 void *x,
110 void *y,
111 uint64_t from_row_index,
112 uint32_t how_many_rows);
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121typedef struct _dmlfw_gradient_descent_options dmlfw_gradient_descent_options;
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407#endif // __DMLFW__ML_CONFIGURATIONS__
uint64_t dmlfw_gradient_descent_options_get_number_of_iterations(dmlfw_gradient_descent_options *gd_options)
Gets the number of iterations.
dmlfw_gradient_descent_lin_reg_data_provider_t dmlfw_gradient_descent_options_get_data_provider(dmlfw_gradient_descent_options *gd_options)
Gets the data provider callback pointer.
dmlfw_gradient_descent_lin_reg_progress_callback_t dmlfw_gradient_descent_options_get_progress_callback(dmlfw_gradient_descent_options *gd_options)
Gets the progress callback pointer.
void dmlfw_gradient_descent_options_set_mini_batch_size(dmlfw_gradient_descent_options *gd_options, uint32_t mini_batch_size)
Sets the mini-batch size for mini-batch gradient descent.
void dmlfw_gradient_descent_options_set_data_provider(dmlfw_gradient_descent_options *gd_options, dmlfw_gradient_descent_lin_reg_data_provider_t data_provider)
Sets the data provider callback.
double dmlfw_gradient_descent_options_get_learning_rate(dmlfw_gradient_descent_options *gd_options)
Gets the learning rate.
MLFW_GRADIENT_DESCENT_TYPE
Gradient descent algorithm types.
Definition dmlfw_ml_configurations.h:70
@ MLFW_BATCH_GRADIENT_DESCENT
Full batch gradient descent.
Definition dmlfw_ml_configurations.h:71
@ MLFW_MINI_BATCH_GRADIENT_DESCENT
Mini-batch gradient descent.
Definition dmlfw_ml_configurations.h:73
@ MLFW_STOCHASTIC_GRADIENT_DESCENT
Stochastic gradient descent.
Definition dmlfw_ml_configurations.h:72
void dmlfw_gradient_descent_options_set_number_of_iterations(dmlfw_gradient_descent_options *gd_options, uint64_t number_of_iterations)
Sets the number of iterations.
void dmlfw_gradient_descent_options_set_progress_callback(dmlfw_gradient_descent_options *gd_options, dmlfw_gradient_descent_lin_reg_progress_callback_t progress_callback)
Sets the progress callback.
uint32_t dmlfw_gradient_descent_options_get_mini_batch_size(dmlfw_gradient_descent_options *gd_options)
Gets the mini-batch size.
int dmlfw_gradient_descent_options_get_gradient_descent_type(dmlfw_gradient_descent_options *gd_options)
Gets the gradient descent type.
void dmlfw_gradient_descent_options_destroy(dmlfw_gradient_descent_options *gd_options)
Destroys a gradient descent options object and frees associated memory.
void dmlfw_gradient_descent_options_set_gradient_descent_type(dmlfw_gradient_descent_options *gd_options, int gradient_descent_type)
Sets the gradient descent type.
struct _dmlfw_gradient_descent_options dmlfw_gradient_descent_options
Opaque structure representing gradient descent configuration options.
Definition dmlfw_ml_configurations.h:121
dmlfw_gradient_descent_options * dmlfw_gradient_descent_options_create_new(void)
Creates a new gradient descent options object with default values.
void(* dmlfw_gradient_descent_lin_reg_data_provider_t)(void *x, void *y, uint64_t from_row_index, uint32_t how_many_rows)
Data provider callback for gradient descent linear regression.
Definition dmlfw_ml_configurations.h:108
void dmlfw_gradient_descent_options_set_learning_rate(dmlfw_gradient_descent_options *gd_options, double learning_rate)
Sets the learning rate.
int(* dmlfw_gradient_descent_lin_reg_progress_callback_t)(uint64_t iteration_number, void *y, void *predicted_y, void *model, double regularization_parameter)
Progress callback for gradient descent linear regression.
Definition dmlfw_ml_configurations.h:90