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-rw-r--r--nerv/lib/matrix/cukernel.h2
-rw-r--r--nerv/lib/matrix/generic/cukernel.cu45
-rw-r--r--nerv/lib/matrix/generic/cumatrix.c18
-rw-r--r--nerv/lib/matrix/generic/cumatrix.h3
-rw-r--r--nerv/matrix/generic/cumatrix.c21
5 files changed, 89 insertions, 0 deletions
diff --git a/nerv/lib/matrix/cukernel.h b/nerv/lib/matrix/cukernel.h
index fffe0bc..40f8e9f 100644
--- a/nerv/lib/matrix/cukernel.h
+++ b/nerv/lib/matrix/cukernel.h
@@ -3,6 +3,8 @@ void cudak_(cuda_mul_elem)(const Matrix *a, const Matrix *b, Matrix *c);
void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b);
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_tanh)(const Matrix *a, Matrix *b);
+void cudak_(cuda_tanh_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_rowmax_idx)(const Matrix *a, Matrix *b, Matrix *idx);
diff --git a/nerv/lib/matrix/generic/cukernel.cu b/nerv/lib/matrix/generic/cukernel.cu
index e58c488..c82041f 100644
--- a/nerv/lib/matrix/generic/cukernel.cu
+++ b/nerv/lib/matrix/generic/cukernel.cu
@@ -53,6 +53,28 @@ __global__ void cudak_(sigmoid_grad)(const MATRIX_ELEM *output,
nerr[idx] = output[idx] * (1.0 - output[idx]) * err[idx];
}
+__global__ void cudak_(tanh)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
+ 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;
+ b[idx] = (exp(a[idx]) - exp(-a[idx])) / (exp(a[idx]) + exp(-a[idx]));
+}
+
+__global__ void cudak_(tanh_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] = (1.0 - output[idx] * 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) {
@@ -353,6 +375,29 @@ extern "C" {
cudaStreamSynchronize(0);
}
+ void cudak_(cuda_tanh)(const Matrix *a, Matrix *b) {
+ dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N);
+ dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x),
+ CEIL_DIV(b->nrow, threadsPerBlock.y));
+ cudak_(tanh)<<<numBlocks, threadsPerBlock>>> \
+ (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), b->nrow, b->ncol,
+ b->stride / sizeof(MATRIX_ELEM));
+ cudaStreamSynchronize(0);
+ }
+
+ void cudak_(cuda_tanh_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_(tanh_grad)<<<numBlocks, threadsPerBlock>>> \
+ (MATRIX_ELEM_PTR(output), MATRIX_ELEM_PTR(err),
+ MATRIX_ELEM_PTR(nerr),
+ nerr->nrow, nerr->ncol,
+ nerr->stride / sizeof(MATRIX_ELEM));
+ cudaStreamSynchronize(0);
+ }
+
void cudak_(cuda_rowsum)(const Matrix *a, Matrix *b) {
dim3 block(CUDA_THREADS_NN, 1);
int ncol = a->ncol;
diff --git a/nerv/lib/matrix/generic/cumatrix.c b/nerv/lib/matrix/generic/cumatrix.c
index 00af895..77cb304 100644
--- a/nerv/lib/matrix/generic/cumatrix.c
+++ b/nerv/lib/matrix/generic/cumatrix.c
@@ -75,6 +75,24 @@ void nerv_matrix_(sigmoid_grad)(Matrix *nerr, const Matrix *err,
NERV_SET_STATUS(status, NERV_NORMAL, 0);
}
+void nerv_matrix_(tanh)(Matrix *a, const Matrix *b, Status *status) {
+ CHECK_SAME_DIMENSION(a, b, status);
+ PROFILE_START
+ cudak_(cuda_tanh)(b, a);
+ PROFILE_STOP
+ NERV_SET_STATUS(status, NERV_NORMAL, 0);
+}
+
+void nerv_matrix_(tanh_grad)(Matrix *nerr, const Matrix *err,
+ const Matrix *output, Status *status) {
+ CHECK_SAME_DIMENSION(nerr, err, status);
+ CHECK_SAME_DIMENSION(nerr, output, status);
+ PROFILE_START
+ cudak_(cuda_tanh_grad)(output, err, nerr);
+ PROFILE_STOP
+ NERV_SET_STATUS(status, NERV_NORMAL, 0);
+}
+
Matrix *nerv_matrix_(softmax)(Matrix *b, const Matrix *a, Status *status) {
Matrix *max, *max_idx;
Matrix *dno;
diff --git a/nerv/lib/matrix/generic/cumatrix.h b/nerv/lib/matrix/generic/cumatrix.h
index 21c29b7..aa8805a 100644
--- a/nerv/lib/matrix/generic/cumatrix.h
+++ b/nerv/lib/matrix/generic/cumatrix.h
@@ -9,6 +9,9 @@ void nerv_matrix_(mul)(Matrix *c, const Matrix *a, const Matrix *b,
void nerv_matrix_(sigmoid)(Matrix *a, const Matrix *b, Status *status);
void nerv_matrix_(sigmoid_grad)(Matrix *nerr, const Matrix *err,
const Matrix *output, Status *status);
+void nerv_matrix_(tanh)(Matrix *a, const Matrix *b, Status *status);
+void nerv_matrix_(tanh_grad)(Matrix *nerr, const Matrix *err,
+ const Matrix *output, Status *status);
Matrix *nerv_matrix_(softmax)(Matrix *b, const Matrix *a, Status *status);
Matrix *nerv_matrix_(rowsum)(Matrix *a, Status *status);
diff --git a/nerv/matrix/generic/cumatrix.c b/nerv/matrix/generic/cumatrix.c
index e1519b0..3d9e694 100644
--- a/nerv/matrix/generic/cumatrix.c
+++ b/nerv/matrix/generic/cumatrix.c
@@ -62,6 +62,25 @@ static int nerv_matrix_(lua_sigmoid_grad)(lua_State *L) {
return 0;
}
+static int nerv_matrix_(lua_tanh)(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_(tanh)(a, b, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
+ return 0;
+}
+
+static int nerv_matrix_(lua_tanh_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_(tanh_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));
@@ -328,6 +347,8 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"fill", nerv_matrix_(lua_fill)},
{"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)},
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