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-rw-r--r--matrix/cukernel.h1
-rw-r--r--matrix/generic/cukernel.cu25
-rw-r--r--matrix/generic/cumatrix.c31
3 files changed, 49 insertions, 8 deletions
diff --git a/matrix/cukernel.h b/matrix/cukernel.h
index 3cad489..b2b6cb2 100644
--- a/matrix/cukernel.h
+++ b/matrix/cukernel.h
@@ -1,5 +1,6 @@
#ifdef NERV_GENERIC_CUKERNEL
void cudak_(cuda_sigmoid)(const Matrix *a, Matrix *b);
+void cudak_(cuda_sigmoid_grad)(const Matrix *output, const Matrix *err, Matrix *nerr);
void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b);
void cudak_(cuda_rowmax)(const Matrix *a, Matrix *b);
void cudak_(cuda_colsum)(const Matrix *a, Matrix *b);
diff --git a/matrix/generic/cukernel.cu b/matrix/generic/cukernel.cu
index 8b929e4..517393e 100644
--- a/matrix/generic/cukernel.cu
+++ b/matrix/generic/cukernel.cu
@@ -16,6 +16,18 @@ __global__ void cudak_(sigmoid)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
b[idx] = 1.0 / (1.0 + exp(-a[idx]));
}
+__global__ void cudak_(sigmoid_grad)(const MATRIX_ELEM *output,
+ const MATRIX_ELEM *err,
+ MATRIX_ELEM *nerr,
+ int nrow, int ncol, int stride) {
+ int j = blockIdx.x * blockDim.x + threadIdx.x;
+ int i = blockIdx.y * blockDim.y + threadIdx.y;
+ long idx;
+ if (i >= nrow || j >= ncol) return;
+ idx = j + i * stride;
+ nerr[idx] = output[idx] * (1.0 - output[idx]) * err[idx];
+}
+
__global__ void cudak_(softmax_final)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
const MATRIX_ELEM *max, const MATRIX_ELEM *deno,
int nrow, int ncol, int stride, int mstride) {
@@ -134,6 +146,19 @@ extern "C" {
b->stride / sizeof(MATRIX_ELEM));
}
+ void cudak_(cuda_sigmoid_grad)(const Matrix *output,
+ const Matrix *err, Matrix *nerr) {
+ dim3 threadsPerBlock(CUDA_THREADS_N,
+ CUDA_THREADS_N);
+ dim3 numBlocks(CEIL_DIV(nerr->ncol, threadsPerBlock.x),
+ CEIL_DIV(nerr->nrow, threadsPerBlock.y));
+ cudak_(sigmoid_grad)<<<numBlocks, threadsPerBlock>>> \
+ (MATRIX_ELEM_PTR(output), MATRIX_ELEM_PTR(err),
+ MATRIX_ELEM_PTR(nerr),
+ nerr->nrow, nerr->ncol,
+ nerr->stride / sizeof(MATRIX_ELEM));
+ }
+
void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b) {
dim3 block(CUDA_THREADS_NN, 1);
int ncol = a->ncol;
diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c
index 8de6c1b..2b3b9d4 100644
--- a/matrix/generic/cumatrix.c
+++ b/matrix/generic/cumatrix.c
@@ -18,6 +18,12 @@
#include "driver_types.h"
#include "cublas_v2.h"
+#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"); \
+ } while (0)
+
static cublasHandle_t cublas_handle;
Matrix *nerv_matrix_(new_)(long nrow, long ncol);
@@ -40,8 +46,7 @@ static int nerv_matrix_(add)(lua_State *L) {
Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname));
MATRIX_ELEM alpha = luaL_checknumber(L, 4); /* alpha */
MATRIX_ELEM beta = luaL_checknumber(L, 5); /* alpha */
- if (!(a->nrow == b->nrow && a->ncol == b->ncol))
- nerv_error(L, "Matrices should be of the same dimension");
+ CHECK_SAME_DIMENSION(a, b);
nerv_matrix_(add_)(a, b, c, alpha, beta);
return 0;
}
@@ -91,12 +96,23 @@ static int nerv_matrix_(create)(lua_State *L) {
static int nerv_matrix_(sigmoid)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
- Matrix *b = nerv_matrix_(new_)(a->nrow, a->ncol);
+ Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ CHECK_SAME_DIMENSION(a, b);
cudak_(cuda_sigmoid)(a, b);
luaT_pushudata(L, b, nerv_matrix_(tname));
return 1;
}
+static int nerv_matrix_(sigmoid_grad)(lua_State *L) {
+ 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));
+ CHECK_SAME_DIMENSION(nerr, err);
+ CHECK_SAME_DIMENSION(nerr, output);
+ cudak_(cuda_sigmoid_grad)(output, err, nerr);
+ return 0;
+}
+
static int nerv_matrix_(softmax)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *max = nerv_matrix_(new_)(a->nrow, 1);
@@ -158,8 +174,7 @@ extern const char *MATRIX_CUMATRIX_HOST_TNAME;
static int nerv_matrix_(copy_from)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- if (!(a->nrow == b->nrow && a->ncol == b->ncol))
- nerv_error(L, "Matrices should be of the same dimension");
+ CHECK_SAME_DIMENSION(a, b);
cudaMemcpy2D(MATRIX_ELEM_PTR(a), a->stride,
MATRIX_ELEM_PTR(b), b->stride,
sizeof(MATRIX_ELEM) * b->ncol, b->nrow,
@@ -170,8 +185,7 @@ static int nerv_matrix_(copy_from)(lua_State *L) {
static int nerv_matrix_(copy_to)(lua_State *L) {
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- if (!(a->nrow == b->nrow && a->ncol == b->ncol))
- nerv_error(L, "Matrices should be of the same dimension");
+ CHECK_SAME_DIMENSION(a, b);
cudaMemcpy2D(MATRIX_ELEM_PTR(b), b->stride,
MATRIX_ELEM_PTR(a), a->stride,
sizeof(MATRIX_ELEM) * a->ncol, a->nrow,
@@ -197,7 +211,6 @@ static int nerv_matrix_(trans)(lua_State *L) {
static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"create", nerv_matrix_(create)},
- {"sigmoid", nerv_matrix_(sigmoid)},
{"softmax", nerv_matrix_(softmax)},
{"colsum", nerv_matrix_(colsum)},
{"rowsum", nerv_matrix_(rowsum)},
@@ -210,6 +223,8 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"mul", nerv_matrix_(mul)},
{"add_row", nerv_matrix_(add_row)},
{"fill", nerv_matrix_(fill)},
+ {"sigmoid", nerv_matrix_(sigmoid)},
+ {"sigmoid_grad", nerv_matrix_(sigmoid_grad)},
{NULL, NULL}
};
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