Merge pull request #10934 from tensor-tang/mklml_funcs

speedup vInvSqrt vLogqp vTanh with mklml

Author: luotao1

paddle/math/MathFunctions.cpp

@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "MathFunctions.h"
+#include "paddle/math/MathFunctions.h"
 #include "hl_matrix_apply.cuh"
 #include "hl_matrix_ops.cuh"
 #include "paddle/utils/DynamicLoader.h"
@@ -240,6 +240,36 @@ template <>
 void vAdd<double>(const int n, const double* a, const double* b, double* r) {
   vdAdd(n, a, b, r);
 }
+
+template <>
+void vTanh<float>(const int n, const float* a, float* r) {
+  vsTanh(n, a, r);
+}
+
+template <>
+void vTanh<double>(const int n, const double* a, double* r) {
+  vdTanh(n, a, r);
+}
+
+template <>
+void vInvSqrt<float>(const int n, const float* a, float* r) {
+  vsInvSqrt(n, a, r);
+}
+
+template <>
+void vInvSqrt<double>(const int n, const double* a, double* r) {
+  vdInvSqrt(n, a, r);
+}
+
+template <>
+void vLog1p<float>(const int n, const float* a, float* r) {
+  vsLog1p(n, a, r);
+}
+
+template <>
+void vLog1p<double>(const int n, const double* a, double* r) {
+  vdLog1p(n, a, r);
+}
 #else
 
 DEFINE_MATRIX_BINARY_OP(vExp, b = std::exp(a));
@@ -277,17 +307,6 @@ void vAdd(const int n, const T* a, const T* b, T* r) {
                                                      n);
 }
 
-template void vExp(const int n, const float* a, float* r);
-template void vExp(const int n, const double* a, double* r);
-template void vLog(const int n, const float* a, float* r);
-template void vLog(const int n, const double* a, double* r);
-template void vPow(const int n, const float* a, const float b, float* r);
-template void vPow(const int n, const double* a, const double b, double* r);
-template void vAdd(const int n, const float* a, const float* b, float* r);
-template void vAdd(const int n, const double* a, const double* b, double* r);
-
-#endif
-
 DEFINE_MATRIX_BINARY_OP(vInvSqrt, b = 1.0f / std::sqrt(a));
 template <class T>
 void vInvSqrt(const int n, const T* a, T* r) {
@@ -311,11 +330,19 @@ void vTanh(const int n, const T* a, T* r) {
       binary::vTanh<T>(), const_cast<T*>(a), r, 1, n, n, n);
 }
 
+template void vExp(const int n, const float* a, float* r);
+template void vExp(const int n, const double* a, double* r);
+template void vLog(const int n, const float* a, float* r);
+template void vLog(const int n, const double* a, double* r);
+template void vPow(const int n, const float* a, const float b, float* r);
+template void vPow(const int n, const double* a, const double b, double* r);
+template void vAdd(const int n, const float* a, const float* b, float* r);
+template void vAdd(const int n, const double* a, const double* b, double* r);
 template void vInvSqrt(const int n, const double* a, double* r);
 template void vInvSqrt(const int n, const float* a, float* r);
 template void vLog1p(const int n, const float* a, float* r);
 template void vLog1p(const int n, const double* a, double* r);
 template void vTanh(const int n, const float* a, float* r);
 template void vTanh(const int n, const double* a, double* r);
-
+#endif
 }  // namespace paddle