openGPMP
Open Source Mathematics Package
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Variables | |
mtx = linalg.Mtx() | |
list | A = [1,2,3,4] |
list | B = [2,3,1,4] |
list | C = [] |
list | A_int = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] |
list | B_int = [[9, 8, 7], [6, 5, 4], [3, 2, 1]] |
list | C_int = [] |
res = mtx.std_mtx_add_int(A_int, B_int, C_int) | |
since the Matrix class is a template class, there are classes created for both Doubles and Integers The template Matrix class and mtx struct were converted to type double methods instead of declaring a method for each type. *NOTE* there is a respective 'INTEGER' version of each method that defaulted to type double, my recommendation is to use the default methods that converted to type double as data will more than likely follow the scheme. SCHEMES: class Matrix (int) -> class MatrixI an INTEGER type mtx struct is not possible given floating point requirements for certain cases of cassert
list python.linalg.A = [1,2,3,4] |
Definition at line 22 of file linalg.py.
Referenced by BOOST_PYTHON_MODULE(), gpmp::nt::RC5.decrypt(), RC6.decrypt_block(), gpmp::linalg::DGEMM.dgemm_micro_kernel(), gpmp::linalg::DGEMM.dgemm_nn(), gpmp::nt::RC5.encrypt(), RC6.encrypt_block(), gpu_mtx_add(), gpmp::linalg::IGEMM.igemm_micro_kernel(), gpmp::linalg::IGEMM.igemm_nn(), RC6.key_schedule(), main(), matrixMul(), mtx_add_f90(), multiply_matrices(), multiply_matrices_std(), gpmp::linalg::DGEMM.pack_buffer_A(), gpmp::linalg::SGEMM.pack_buffer_A(), gpmp::linalg::IGEMM.pack_buffer_A(), gpmp::linalg::DGEMM.pack_micro_A(), gpmp::linalg::SGEMM.pack_micro_A(), gpmp::linalg::IGEMM.pack_micro_A(), run_mtx_add(), run_mtx_add_arr(), run_mtx_add_doub(), run_mtx_add_flt(), gpmp::linalg::SGEMM.sgemm_micro_kernel(), gpmp::linalg::SGEMM.sgemm_nn(), gpmp::linalg::Mtx.std_mtx_add(), gpmp::linalg::Mtx.std_mtx_mult(), gpmp::linalg::Mtx.std_mtx_sub(), and gpmp::linalg::Mtx.std_mtx_tpose().
list python.linalg.A_int = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] |
list python.linalg.B = [2,3,1,4] |
Definition at line 23 of file linalg.py.
Referenced by BOOST_PYTHON_MODULE(), gpmp::nt::RC5.decrypt(), RC6.decrypt_block(), gpmp::linalg::DGEMM.dgemm_micro_kernel(), gpmp::linalg::DGEMM.dgemm_nn(), gpmp::nt::RC5.encrypt(), RC6.encrypt_block(), gpu_mtx_add(), gpmp::linalg::IGEMM.igemm_micro_kernel(), gpmp::linalg::IGEMM.igemm_nn(), RC6.key_schedule(), main(), matrixMul(), mtx_add_f90(), multiply_matrices(), multiply_matrices_std(), gpmp::linalg::DGEMM.pack_buffer_B(), gpmp::linalg::SGEMM.pack_buffer_B(), gpmp::linalg::IGEMM.pack_buffer_B(), gpmp::linalg::DGEMM.pack_micro_B(), gpmp::linalg::SGEMM.pack_micro_B(), gpmp::linalg::IGEMM.pack_micro_B(), run_mtx_add(), run_mtx_add_arr(), run_mtx_add_doub(), run_mtx_add_flt(), gpmp::linalg::SGEMM.sgemm_micro_kernel(), gpmp::linalg::SGEMM.sgemm_nn(), gpmp::linalg::Mtx.std_mtx_add(), gpmp::linalg::Mtx.std_mtx_mult(), and gpmp::linalg::Mtx.std_mtx_sub().
list python.linalg.B_int = [[9, 8, 7], [6, 5, 4], [3, 2, 1]] |
list python.linalg.C = [] |
Definition at line 24 of file linalg.py.
Referenced by BOOST_PYTHON_MODULE(), gpmp::ml::SVC.compute_loss(), gpmp::linalg::DGEMM.dgemm_macro_kernel(), gpmp::linalg::DGEMM.dgemm_micro_kernel(), gpmp::linalg::DGEMM.dgemm_nn(), gpu_mtx_add(), gpmp::linalg::IGEMM.igemm_macro_kernel(), gpmp::linalg::IGEMM.igemm_micro_kernel(), gpmp::linalg::IGEMM.igemm_nn(), main(), matrixMul(), mtx_add_f90(), multiply_matrices(), multiply_matrices_std(), run_mtx_add(), run_mtx_add_arr(), run_mtx_add_doub(), run_mtx_add_flt(), gpmp::linalg::SGEMM.sgemm_macro_kernel(), gpmp::linalg::SGEMM.sgemm_micro_kernel(), gpmp::linalg::SGEMM.sgemm_nn(), gpmp::linalg::Mtx.std_mtx_add(), gpmp::linalg::Mtx.std_mtx_mult(), gpmp::linalg::Mtx.std_mtx_sub(), and gpmp::ml::SVC.update_weights().
python.linalg.mtx = linalg.Mtx() |
Definition at line 20 of file linalg.py.
Referenced by mtx_add_f90(), run_mtx_add(), run_mtx_add_arr(), run_mtx_add_doub(), and run_mtx_add_flt().
Definition at line 29 of file linalg.py.
Referenced by gpmp::linalg::Matrix< Type >.add(), add_vec_cpu(), add_vec_gpu(), gpmp::linalg::Matrix< Type >.apply_func(), gpmp::linalg::Matrix< Type >.concatenate(), gpmp::linalg::Matrix< Type >.diag(), gpmp::core::ThreadPool.enqueue(), gpmp::linalg::Matrix< Type >.hadamard(), main(), gpmp::PrimalityTest.mod_mul(), gpmp::PrimalityTest.mod_pow(), gpmp::linalg::Matrix< Type >.mult(), multiply_matrices(), gpmp::linalg::Matrix< Type >.operator-(), gpmp::linalg::Matrix< Type >.operator==(), gpmp::linalg::Matrix< Type >.scalar_add(), gpmp::linalg::Matrix< Type >.scalar_mult(), gpmp::linalg::Matrix< Type >.sqr_err(), and gpmp::linalg::Matrix< Type >.sum().