#ifdef NERV_GENERIC_CUMATRIX #include "elem_type.h" #define MATRIX_DATA_WRITE(L, data, idx, val) cuda_matrix_(write)(L, data, idx, val) #define MATRIX_DATA_READ(L, data, idx) cuda_matrix_(read)(L, data, idx) #define MATRIX_INIT(L) cuda_matrix_(init)(L) #define MATRIX_BASE_TNAME nerv_matrix_cuda_tname #define NERV_GENERIC_MATRIX #define NERV_GENERIC_CUKERNEL #include "../../lib/common.h" #include "../../lib/matrix/generic/matrix.h" #include "../../lib/matrix/generic/cumatrix.h" static int nerv_matrix_(lua_add)(lua_State *L) { Status status; Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); MATRIX_ELEM alpha = luaL_checknumber(L, 4); MATRIX_ELEM beta = luaL_checknumber(L, 5); nerv_matrix_(add)(c, a, b, alpha, beta, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_get_cublas_op)(char ch) { return (ch == 'T' || ch == 't') ? CUBLAS_OP_T : CUBLAS_OP_N; } static int nerv_matrix_(lua_mul)(lua_State *L) { Status status; Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); MATRIX_ELEM alpha = luaL_checknumber(L, 4); MATRIX_ELEM beta = luaL_checknumber(L, 5); int nargs = lua_gettop(L); int ta = nargs > 5 ? nerv_matrix_(lua_get_cublas_op)(*luaL_checkstring(L, 6)) \ : CUBLAS_OP_N; int tb = nargs > 6 ? nerv_matrix_(lua_get_cublas_op)(*luaL_checkstring(L, 7)) \ : CUBLAS_OP_N; nerv_matrix_(mul)(c, a, b, alpha, beta, ta, tb, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_create)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(create)(a->nrow, a->ncol, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_sigmoid)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); nerv_matrix_(sigmoid)(a, b, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_sigmoid_grad)(lua_State *L) { Status status; Matrix *nerr = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *err = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *output = luaT_checkudata(L, 3, nerv_matrix_(tname)); nerv_matrix_(sigmoid_grad)(nerr, err, output, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_softmax)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *max_idx = nerv_matrix_(softmax)(b, a, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, max_idx, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_rowsum)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(rowsum)(a, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_colsum)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(colsum)(a, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_colsame)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *ref = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(colsame)(a, ref, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_rowmax)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(rowmax)(a, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_rowmax_idx)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b; Matrix *idx; nerv_matrix_(rowmax_idx)(a, &b, &idx, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); luaT_pushudata(L, idx, nerv_matrix_(tname)); return 2; } static int nerv_matrix_(lua_add_row)(lua_State *L) { Status status; const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); double beta = luaL_checknumber(L, 3); nerv_matrix_(add_row)(b, a, beta, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_fill)(lua_State *L) { Status status; Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); double val = luaL_checknumber(L, 2); nerv_matrix_(fill)(self, val, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_clip)(lua_State *L) { Status status; Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname)); double val_1 = luaL_checknumber(L, 2); double val_2 = luaL_checknumber(L, 3); nerv_matrix_(clip)(self, val_1, val_2, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_copy_fromd)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); int nargs = lua_gettop(L); int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow; int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; nerv_matrix_(copy_fromd)(a, b, a_begin, b_begin, b_end, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } extern const char *MATRIX_CUMATRIX_HOST_TNAME; static int nerv_matrix_(lua_copy_fromh)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); int nargs = lua_gettop(L); int b_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; int b_end = nargs > 3 ? luaL_checkinteger(L, 4) : b->nrow; int a_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; nerv_matrix_(copy_fromh)(a, b, a_begin, b_begin, b_end, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_copy_toh)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); int nargs = lua_gettop(L); int a_begin = nargs > 2 ? luaL_checkinteger(L, 3) : 0; int a_end = nargs > 3 ? luaL_checkinteger(L, 4) : a->nrow; int b_begin = nargs > 4 ? luaL_checkinteger(L, 5) : 0; nerv_matrix_(copy_toh)(a, b, a_begin, a_end, b_begin, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_trans)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = nerv_matrix_(trans)(a, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } static int nerv_matrix_(lua_mul_elem)(lua_State *L) { Status status; const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); nerv_matrix_(mul_elem)(c, a, b, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_log_elem)(lua_State *L) { Status status; const Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname)); nerv_matrix_(log_elem)(b, a, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_decompress)(lua_State *L) { Status status; const Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); int orig_col = luaL_checkinteger(L, 2); Matrix *b = nerv_matrix_(decompress)(a, orig_col, &status); NERV_LUA_CHECK_STATUS(L, status); luaT_pushudata(L, b, nerv_matrix_(tname)); return 1; } extern const char *nerv_matrix_host_int_tname; static int nerv_matrix_(lua_copy_rows_fromh_by_idx)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME); const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_int_tname); long nrow = a->nrow; int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0; nerv_matrix_(copy_rows_fromh_by_idx)(a, b, idx, b_begin, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_expand_frm)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); int context = luaL_checkinteger(L, 3); nerv_matrix_(expand_frm)(a, b, context, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_rearrange_frm)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); int step = luaL_checkinteger(L, 3); nerv_matrix_(rearrange_frm)(a, b, step, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_scale_rows_by_col)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); nerv_matrix_(scale_rows_by_col)(a, b, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static int nerv_matrix_(lua_scale_rows_by_row)(lua_State *L) { Status status; Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); nerv_matrix_(scale_rows_by_row)(a, b, &status); NERV_LUA_CHECK_STATUS(L, status); return 0; } static const luaL_Reg nerv_matrix_(extra_methods)[] = { {"create", nerv_matrix_(lua_create)}, {"colsum", nerv_matrix_(lua_colsum)}, {"colsame", nerv_matrix_(lua_colsame)}, {"rowsum", nerv_matrix_(lua_rowsum)}, {"rowmax", nerv_matrix_(lua_rowmax)}, {"rowmax_idx", nerv_matrix_(lua_rowmax_idx)}, {"trans", nerv_matrix_(lua_trans)}, {"decompress", nerv_matrix_(lua_decompress)}, /* in-place calc */ {"copy_fromh", nerv_matrix_(lua_copy_fromh)}, {"copy_fromd", nerv_matrix_(lua_copy_fromd)}, {"copy_toh", nerv_matrix_(lua_copy_toh)}, {"add", nerv_matrix_(lua_add)}, {"mul", nerv_matrix_(lua_mul)}, {"add_row", nerv_matrix_(lua_add_row)}, {"clip", nerv_matrix_(lua_clip)}, {"fill", nerv_matrix_(lua_fill)}, {"sigmoid", nerv_matrix_(lua_sigmoid)}, {"sigmoid_grad", nerv_matrix_(lua_sigmoid_grad)}, {"softmax", nerv_matrix_(lua_softmax)}, {"mul_elem", nerv_matrix_(lua_mul_elem)}, {"log_elem", nerv_matrix_(lua_log_elem)}, {"copy_rows_fromh_by_idx", nerv_matrix_(lua_copy_rows_fromh_by_idx)}, {"expand_frm", nerv_matrix_(lua_expand_frm)}, {"rearrange_frm", nerv_matrix_(lua_rearrange_frm)}, {"scale_rows_by_row", nerv_matrix_(lua_scale_rows_by_row)}, {"scale_rows_by_col", nerv_matrix_(lua_scale_rows_by_col)}, {NULL, NULL} }; static void cuda_matrix_(init)(lua_State *L) { luaN_append_methods(L, nerv_matrix_(extra_methods)); } int nerv_matrix_(lua_get_elem)(lua_State *L) { return nerv_error_method_not_implemented(L); } int nerv_matrix_(lua_set_elem)(lua_State *L) { return nerv_error_method_not_implemented(L); } static MATRIX_ELEM cuda_matrix_(read)(lua_State *L, MATRIX_ELEM *data, int idx) { cudaError_t err; MATRIX_ELEM res; err = cudaMemcpy(&res, data + idx, sizeof(MATRIX_ELEM), cudaMemcpyDeviceToHost); if (err != cudaSuccess) nerv_error(L, "cuda error: error while reading element"); cudaDeviceSynchronize(); return res; } static void cuda_matrix_(write)(lua_State *L, MATRIX_ELEM *data, int idx, MATRIX_ELEM val) { cudaError_t err; err = cudaMemcpy(data + idx, &val, sizeof(MATRIX_ELEM), cudaMemcpyHostToDevice); if (err != cudaSuccess) nerv_error(L, "cuda error: error while writing element"); cudaDeviceSynchronize(); } #include "matrix.c" #endif