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#ifdef NERV_GENERIC_MMATRIX
#include "../matrix.h"
#include "../../lib/matrix/generic/matrix.h"
#include "../../lib/matrix/generic/elem_type.h"
#define MATRIX_DATA_WRITE(L, data, idx, val) (data[idx] = val)
#define MATRIX_DATA_READ(L, data, idx) (data[idx])
#define MATRIX_INIT(L) host_matrix_(init)(L)
#define MATRIX_BASE_TNAME nerv_matrix_host_tname
#define NERV_GENERIC_MATRIX
#include "../../lib/common.h"
#include "../../lib/cblas.h"
#include "../../lib/matrix/generic/mmatrix.h"
#include "../../io/chunk_file.h"
#include <string.h>
#define BLAS_OP_N CblasNoTrans
static int nerv_matrix_(lua_get_blas_op)(char ch) {
return (ch == 'T' || ch == 't') ? CblasTrans : CblasNoTrans;
}
static int nerv_matrix_(lua_get_elem)(lua_State *L) {
Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname));
int idx = luaL_checkinteger(L, 2);
if (idx < 0 || idx >= self->nmax)
nerv_error(L, "index must be within range [0, %d)", self->nmax);
lua_pushnumber(L, MATRIX_ELEM_PTR(self)[idx]);
return 1;
}
static int nerv_matrix_(lua_set_elem)(lua_State *L) {
Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname));
int idx = luaL_checkinteger(L, 2);
MATRIX_ELEM v = luaL_checknumber(L, 3);
if (idx < 0 || idx >= self->nmax)
nerv_error(L, "index must be within range [0, %d)", self->nmax);
MATRIX_ELEM_PTR(self)[idx] = v;
return 0;
}
static const luaL_Reg nerv_matrix_(extra_methods)[];
static void host_matrix_(init)(lua_State *L) {
luaN_append_methods(L, nerv_matrix_(extra_methods));
#ifdef MMATRIX_INIT
MMATRIX_INIT(L);
#endif
}
#include "matrix.c"
static int nerv_matrix_(lua_load)(lua_State *L) {
Status status;
MATRIX_CONTEXT *context;
MATRIX_GET_CONTEXT(L, 2);
ChunkData *cdp = luaT_checkudata(L, 1, nerv_chunk_data_tname);
Matrix *self = nerv_matrix_(load)(cdp, context, &status);
NERV_LUA_CHECK_STATUS(L, status);
luaT_pushudata(L, self, nerv_matrix_(tname));
return 1;
}
static int nerv_matrix_(lua_save)(lua_State *L) {
Status status;
MATRIX_CONTEXT *context;
MATRIX_GET_CONTEXT(L, 3);
ChunkFile *cfp = luaT_checkudata(L, 2,
nerv_chunk_file_handle_tname);
Matrix *self = luaT_checkudata(L, 1, nerv_matrix_(tname));
nerv_matrix_(save)(self, cfp, context, &status);
NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
static int nerv_matrix_(lua_copy_fromh)(lua_State *L) {
Status status;
MATRIX_CONTEXT *context;
MATRIX_GET_CONTEXT(L, 6);
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_fromh)(a, b, a_begin, b_begin, b_end, context, &status);
NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
static int nerv_matrix_(lua_copy_rows_fromh_by_idx)(lua_State *L)
{
Status status;
MATRIX_CONTEXT *context;
MATRIX_GET_CONTEXT(L, 5);
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_(tname));
int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0;
nerv_matrix_(copy_rows_fromh_by_idx)(a, b, idx, b_begin, context, &status);
NERV_LUA_CHECK_STATUS(L, status);
return 0;
}
static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"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)},
/* alias for copy_from */
{"copy_from", nerv_matrix_(lua_copy_fromh)},
{"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)},
{"diagonalize", nerv_matrix_(lua_diagonalize)},
{"set_values_by_mask", nerv_matrix_(lua_set_values_by_mask)},
{"sigmoid", nerv_matrix_(lua_sigmoid)},
{"sigmoid_grad", nerv_matrix_(lua_sigmoid_grad)},
{"tanh", nerv_matrix_(lua_tanh)},
{"tanh_grad", nerv_matrix_(lua_tanh_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)},
{"copy_rows_from_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)},
{"load", nerv_matrix_(lua_load)},
{"save", nerv_matrix_(lua_save)},
{NULL, NULL}
};
#endif
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