def alltrainDL(
*args) -> "Matrix< float > **, Matrix< float > **, Vector< int > **":
"""
alltrainDL(Data< double > * X, bool in_memory, bool return_model, Matrix< double > * m_A, Matrix< double > * m_B, int m_iter, Matrix< double > * D1, Vector< double > * eta_g, SpMatrix< bool > * groups, SpMatrix< bool > * groups_var, Vector< int > * own_variables, Vector< int > * N_own_variables, int num_threads, double tol, bool fixed_step, bool ista, int batch_size, int K, double lambda1, double lambda2, double lambda3, int iter, double t0, constraint_type mode, char * name_regul, bool posAlpha, bool posD, bool expand, constraint_type_D modeD, bool whiten, bool clean, bool verbose, double gamma1, double gamma2, double rho, int iter_updateD, bool stochastic, int modeParam, bool batch, bool log, char * logName) -> Matrix< double >
alltrainDL(Data< float > * X, bool in_memory, bool return_model, Matrix< float > * m_A, Matrix< float > * m_B, int m_iter, Matrix< float > * D1, Vector< float > * eta_g, SpMatrix< bool > * groups, SpMatrix< bool > * groups_var, Vector< int > * own_variables, Vector< int > * N_own_variables, int num_threads, float tol, bool fixed_step, bool ista, int batch_size, int K, double lambda1, double lambda2, double lambda3, int iter, double t0, constraint_type mode, char * name_regul, bool posAlpha, bool posD, bool expand, constraint_type_D modeD, bool whiten, bool clean, bool verbose, double gamma1, double gamma2, float rho, int iter_updateD, bool stochastic, int modeParam, bool batch, bool log, char * logName) -> Matrix< float > *
"""
return _spams_wrap.alltrainDL(*args)
def alltrainDL(*args):
"""
alltrainDL(Data<(double)> X, bool in_memory, bool return_model,
Matrix<(double)> m_A, Matrix<(double)> m_B,
int m_iter, Matrix<(double)> D1, Vector<(double)> eta_g,
SpMatrix<(bool)> groups, SpMatrix<(bool)> groups_var,
Vector<(int)> own_variables,
Vector<(int)> N_own_variables, int num_threads,
double tol, bool fixed_step, bool ista,
int batch_size, int K, double lambda1, double lambda2,
double lambda3, int iter, double t0,
constraint_type mode, char name_regul,
bool posAlpha, bool posD, bool expand, constraint_type_D modeD,
bool whiten, bool clean, bool verbose,
double gamma1, double gamma2, double rho,
int iter_updateD, bool stochastic,
int modeParam, bool batch, bool log, char logName) -> Matrix<(double)>
alltrainDL(Data<(float)> X, bool in_memory, bool return_model,
Matrix<(float)> m_A, Matrix<(float)> m_B, int m_iter,
Matrix<(float)> D1, Vector<(float)> eta_g,
SpMatrix<(bool)> groups, SpMatrix<(bool)> groups_var,
Vector<(int)> own_variables,
Vector<(int)> N_own_variables, int num_threads,
float tol, bool fixed_step, bool ista, int batch_size,
int K, double lambda1, double lambda2,
double lambda3, int iter, double t0,
constraint_type mode, char name_regul, bool posAlpha,
bool posD, bool expand, constraint_type_D modeD,
bool whiten, bool clean, bool verbose,
double gamma1, double gamma2, float rho,
int iter_updateD, bool stochastic, int modeParam,
bool batch, bool log, char logName) -> Matrix<(float)>
"""
return _spams_wrap.alltrainDL(*args)