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-rw-r--r--matrix/cuda_helper.h2
-rw-r--r--matrix/cukernel.h1
-rw-r--r--matrix/generic/cukernel.cu19
-rw-r--r--matrix/generic/cumatrix.c87
-rw-r--r--matrix/generic/mmatrix.c20
-rw-r--r--matrix/init.lua3
6 files changed, 100 insertions, 32 deletions
diff --git a/matrix/cuda_helper.h b/matrix/cuda_helper.h
index c0fa618..cedc643 100644
--- a/matrix/cuda_helper.h
+++ b/matrix/cuda_helper.h
@@ -23,7 +23,7 @@
#define CHECK_SAME_DIMENSION(a, b) \
do { \
if (!(a->nrow == b->nrow && a->ncol == b->ncol)) \
- nerv_error(L, "Matrices should be of the same dimension"); \
+ nerv_error(L, "matrices should be of the same dimension"); \
} while (0)
static const char *cublasGetErrorString(cublasStatus_t err) {
diff --git a/matrix/cukernel.h b/matrix/cukernel.h
index 178b7d3..7d2168e 100644
--- a/matrix/cukernel.h
+++ b/matrix/cukernel.h
@@ -13,4 +13,5 @@ void cudak_(cuda_fill)(Matrix *a, double val);
void cudak_(cuda_expand_frm)(const Matrix *a, Matrix *b, int context);
void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step);
void cudak_(cuda_scale_row)(const Matrix *a, Matrix *b);
+void cudak_(cuda_decompress)(const Matrix *a, Matrix *b);
#endif
diff --git a/matrix/generic/cukernel.cu b/matrix/generic/cukernel.cu
index 1d8b983..05a1e78 100644
--- a/matrix/generic/cukernel.cu
+++ b/matrix/generic/cukernel.cu
@@ -187,6 +187,15 @@ __global__ void cudak_(scale_row)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
b[j + i * stride] *= a[j];
}
+__global__ void cudak_(decompress)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
+ int nrow, int ncol,
+ int stride_a, int stride_b) {
+ int j = blockIdx.x * blockDim.x + threadIdx.x;
+ int i = blockIdx.y * blockDim.y + threadIdx.y;
+ if (i >= nrow || j >= ncol) return;
+ b[lrintf(a[j + i * stride_a]) + i * stride_b] = 1.0;
+}
+
extern "C" {
#include "../cukernel.h"
void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b) {
@@ -385,5 +394,15 @@ extern "C" {
(MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b),
b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM));
}
+
+ void cudak_(cuda_decompress)(const Matrix *a, Matrix *b) {
+ dim3 threadsPerBlock(1, CUDA_THREADS_NN);
+ dim3 numBlocks(1, CEIL_DIV(a->nrow, threadsPerBlock.y));
+ cudak_(decompress)<<<numBlocks, threadsPerBlock>>> \
+ (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b),
+ a->nrow, a->ncol,
+ a->stride / sizeof(MATRIX_ELEM),
+ b->stride / sizeof(MATRIX_ELEM));
+ }
}
#endif
diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c
index 0df1bd7..373fc42 100644
--- a/matrix/generic/cumatrix.c
+++ b/matrix/generic/cumatrix.c
@@ -74,7 +74,8 @@ static int nerv_matrix_(mul)(lua_State *L) {
if (an != bm)
nerv_error(L, "Wrong dimension of multipliers");
/* MATRIX_ELEM alpha = 1.0f, beta = 0.0f; */
- CUBLAS_SAFE_CALL( //Because matrix in Nerv is row-major, here b comes first
+ /* Because matrix in Nerv is row-major, here b comes first */
+ CUBLAS_SAFE_CALL(
NERV_CUBLAS_(gemm)(cublas_handle, tb, ta,
bn, am, bm,
&alpha,
@@ -113,9 +114,11 @@ static int nerv_matrix_(sigmoid_grad)(lua_State *L) {
static int nerv_matrix_(softmax)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *max = nerv_matrix_(new_)(L, a->nrow, 1);
- Matrix *dno = nerv_matrix_(new_)(L, a->nrow, 1);
+ Matrix *max;
+ Matrix *dno;
CHECK_SAME_DIMENSION(a, b);
+ max = nerv_matrix_(new_)(L, a->nrow, 1);
+ dno = nerv_matrix_(new_)(L, a->nrow, 1);
cudak_(cuda_rowmax)(a, max);
cudak_(cuda_softmax_denominator)(a, max, dno);
cudak_(cuda_softmax_final)(a, max, dno, b);
@@ -168,26 +171,22 @@ static int nerv_matrix_(fill)(lua_State *L) {
return 0;
}
-static int nerv_matrix_(copy_fromd)(lua_State *L) {
+static int nerv_matrix_(copy_fromd)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
- CHECK_SAME_DIMENSION(a, b);
- CUDA_SAFE_SYNC_CALL(
- cudaMemcpy2D(MATRIX_ELEM_PTR(a), a->stride,
- MATRIX_ELEM_PTR(b), b->stride,
- sizeof(MATRIX_ELEM) * b->ncol, b->nrow,
- cudaMemcpyDeviceToDevice));
- return 0;
-}
-
-static int nerv_matrix_(copy_tod)(lua_State *L) {
- Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
- CHECK_SAME_DIMENSION(a, b);
+ 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;
+ if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow &&
+ a_begin + b_end - b_begin <= a->nrow))
+ nerv_error(L, "invalid copy interval");
+ if (a->ncol != b->ncol)
+ nerv_error(L, "matrices should be of the same dimension");
CUDA_SAFE_SYNC_CALL(
- cudaMemcpy2D(MATRIX_ELEM_PTR(b), b->stride,
- MATRIX_ELEM_PTR(a), a->stride,
- sizeof(MATRIX_ELEM) * a->ncol, a->nrow,
+ cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride,
+ MATRIX_ROW_PTR(b, b_begin), b->stride,
+ sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin,
cudaMemcpyDeviceToDevice));
return 0;
}
@@ -196,11 +195,19 @@ extern const char *MATRIX_CUMATRIX_HOST_TNAME;
static int nerv_matrix_(copy_fromh)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- CHECK_SAME_DIMENSION(a, b);
+ 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;
+ if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow &&
+ a_begin + b_end - b_begin <= a->nrow))
+ nerv_error(L, "invalid copy interval");
+ if (a->ncol != b->ncol)
+ nerv_error(L, "matrices should be of the same dimension");
CUDA_SAFE_SYNC_CALL(
- cudaMemcpy2D(MATRIX_ELEM_PTR(a), a->stride,
- MATRIX_ELEM_PTR(b), b->stride,
- sizeof(MATRIX_ELEM) * b->ncol, b->nrow,
+ cudaMemcpy2D(MATRIX_ROW_PTR(a, a_begin), a->stride,
+ MATRIX_ROW_PTR(b, b_begin), b->stride,
+ sizeof(MATRIX_ELEM) * b->ncol, b_end - b_begin,
cudaMemcpyHostToDevice));
return 0;
}
@@ -208,11 +215,19 @@ static int nerv_matrix_(copy_fromh)(lua_State *L) {
static int nerv_matrix_(copy_toh)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- CHECK_SAME_DIMENSION(a, b);
+ 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;
+ if (!(0 <= a_begin && a_begin < a_end && a_end <= a->nrow &&
+ b_begin + a_end - a_begin <= b->nrow))
+ nerv_error(L, "invalid copy interval");
+ if (b->ncol != a->ncol)
+ nerv_error(L, "matrices should be of the same dimension");
CUDA_SAFE_SYNC_CALL(
- cudaMemcpy2D(MATRIX_ELEM_PTR(b), b->stride,
- MATRIX_ELEM_PTR(a), a->stride,
- sizeof(MATRIX_ELEM) * a->ncol, a->nrow,
+ cudaMemcpy2D(MATRIX_ROW_PTR(b, b_begin), b->stride,
+ MATRIX_ROW_PTR(a, a_begin), a->stride,
+ sizeof(MATRIX_ELEM) * a->ncol, a_end - a_begin,
cudaMemcpyDeviceToHost));
return 0;
}
@@ -221,6 +236,7 @@ static int nerv_matrix_(trans)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = nerv_matrix_(new_)(L, a->ncol, a->nrow);
MATRIX_ELEM alpha = 1, beta = 0;
+ /* FIXME: possible memory leak when lua error is raised */
CUBLAS_SAFE_CALL(
NERV_CUBLAS_(geam)(cublas_handle, CUBLAS_OP_T, CUBLAS_OP_T,
a->nrow, a->ncol,
@@ -251,6 +267,19 @@ static int nerv_matrix_(log_elem)(lua_State *L) {
return 0;
}
+static int nerv_matrix_(decompress)(lua_State *L) {
+ Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+ Matrix *b;
+ int orig_col = luaL_checkinteger(L, 2);
+ if (a->ncol != 1)
+ nerv_error(L, "the compressed matrix must be a column vector");
+ b = nerv_matrix_(new_)(L, a->nrow, orig_col);
+ cudak_(cuda_fill)(b, 0.0);
+ cudak_(cuda_decompress)(a, b);
+ luaT_pushudata(L, b, nerv_matrix_(tname));
+ return 1;
+}
+
extern const char *nerv_matrix_host_int_tname;
static int nerv_matrix_(copy_rows_fromh_by_idx)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
@@ -322,11 +351,11 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"rowsum", nerv_matrix_(rowsum)},
{"rowmax", nerv_matrix_(rowmax)},
{"trans", nerv_matrix_(trans)},
+ {"decompress", nerv_matrix_(decompress)},
/* in-place calc */
{"copy_fromh", nerv_matrix_(copy_fromh)},
{"copy_fromd", nerv_matrix_(copy_fromd)},
{"copy_toh", nerv_matrix_(copy_toh)},
- {"copy_tod", nerv_matrix_(copy_tod)},
{"add", nerv_matrix_(add)},
{"mul", nerv_matrix_(mul)},
{"add_row", nerv_matrix_(add_row)},
diff --git a/matrix/generic/mmatrix.c b/matrix/generic/mmatrix.c
index 3a9ae79..4b722f3 100644
--- a/matrix/generic/mmatrix.c
+++ b/matrix/generic/mmatrix.c
@@ -11,6 +11,7 @@
#define NERV_GENERIC_MATRIX
#include "../../common.h"
#include "../../io/chunk_file.h"
+#include "string.h"
static void host_matrix_(alloc)(lua_State *L,
MATRIX_ELEM **dptr, size_t *stride,
@@ -96,10 +97,27 @@ int nerv_matrix_(save)(lua_State *L) {
return 0;
}
-
+static int nerv_matrix_(copy_from)(lua_State *L) {
+ Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+ 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;
+ if (!(0 <= b_begin && b_begin < b_end && b_end <= b->nrow &&
+ a_begin + b_end - b_begin <= a->nrow))
+ nerv_error(L, "invalid copy interval");
+ if (a->ncol != b->ncol)
+ nerv_error(L, "matrices should be of the same dimension");
+ memmove(MATRIX_ROW_PTR(a, a_begin),
+ MATRIX_ROW_PTR(b, b_begin),
+ sizeof(MATRIX_ELEM) * b->ncol * (b_end - b_begin));
+ return 0;
+}
static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"load", nerv_matrix_(load)},
{"save", nerv_matrix_(save)},
+ {"copy_from", nerv_matrix_(copy_from)},
{NULL, NULL}
};
diff --git a/matrix/init.lua b/matrix/init.lua
index f309f81..9637391 100644
--- a/matrix/init.lua
+++ b/matrix/init.lua
@@ -22,7 +22,8 @@ function nerv.Matrix:__tostring__()
table.insert(strt, "\n")
end
end
- table.insert(strt, string.format("[Matrix %d x %d]", nrow, ncol))
+ table.insert(strt, string.format(
+ "[%s %d x %d]", self.__typename, nrow, ncol))
return table.concat(strt)
end
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