提交 69b44f2f 编写于 作者: T tensor-tang

unify MKL macro definition

上级 74ead9dc
......@@ -17,7 +17,7 @@ if(WITH_MKLML AND MKLML_INC_DIR AND MKLML_LIB)
set(CBLAS_INC_DIR ${MKLML_INC_DIR})
set(CBLAS_LIBRARIES ${MKLML_LIB})
add_definitions(-DPADDLE_USE_MKLML)
add_definitions(-DPADDLE_WITH_MKLML)
add_definitions(-DLAPACK_FOUND)
message(STATUS "Found cblas and lapack in MKLML "
......
......@@ -67,5 +67,5 @@ ADD_LIBRARY(mkldnn SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET mkldnn PROPERTY IMPORTED_LOCATION ${MKLDNN_LIB})
ADD_DEPENDENCIES(mkldnn ${MKLDNN_PROJECT})
MESSAGE(STATUS "MKLDNN library: ${MKLDNN_LIB}")
add_definitions(-DPADDLE_USE_MKLDNN)
add_definitions(-DPADDLE_WITH_MKLDNN)
LIST(APPEND external_project_dependencies mkldnn)
......@@ -24,7 +24,7 @@ limitations under the License. */
#include "paddle/utils/ClassRegistrar.h"
#include "paddle/utils/Logging.h"
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
#include "MKLDNNActivation.h"
#endif
......@@ -490,7 +490,7 @@ Error __must_check backward(Argument& act) {
END_DEFINE_ACTIVATION(log)
ActivationFunction* ActivationFunction::create(const std::string& type) {
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
if (!type.empty() && type.compare(0, 7, "mkldnn_") == 0) {
return MKLDNNActivation::create(type);
}
......
......@@ -20,7 +20,7 @@ limitations under the License. */
#include "paddle/utils/Logging.h"
#include "paddle/utils/Stat.h"
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/gserver/layers/MKLDNNLayer.h"
#endif
......@@ -307,7 +307,7 @@ void NeuralNetwork::backward(const UpdateCallback& callback) {
}
void NeuralNetwork::finish() {
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
FOR_EACH_R(layer, layers_) {
MKLDNNLayerPtr dnnLayer = std::dynamic_pointer_cast<MKLDNNLayer>(*layer);
if (dnnLayer) {
......
......@@ -48,7 +48,7 @@ public:
*/
virtual void* alloc(size_t size) {
void* ptr;
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
// refer to https://github.com/01org/mkl-dnn/blob/master/include/mkldnn.hpp
// memory alignment
CHECK_EQ(posix_memalign(&ptr, 4096ul, size), 0);
......
......@@ -206,7 +206,7 @@ double dotProduct<double>(const int n, const double* x, const double* y) {
}
#endif
#if defined(PADDLE_USE_MKLML)
#if defined(PADDLE_WITH_MKLML)
template <>
void vExp<float>(const int n, const float* a, float* r) {
......
......@@ -15,7 +15,7 @@ limitations under the License. */
#ifndef MATHFUNCTIONS_H_
#define MATHFUNCTIONS_H_
#ifdef PADDLE_USE_MKLML
#ifdef PADDLE_WITH_MKLML
#include <mkl_cblas.h>
#include <mkl_lapacke.h>
#include <mkl_vml_functions.h>
......
......@@ -43,7 +43,7 @@ void* CPUAllocator::Alloc(size_t& index, size_t size) {
void* p;
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
// refer to https://github.com/01org/mkl-dnn/blob/master/include/mkldnn.hpp
// memory alignment
PADDLE_ENFORCE_EQ(posix_memalign(&p, 4096ul, size), 0);
......
......@@ -132,7 +132,7 @@ void matmul<platform::CPUPlace, double>(
matrix_b.data<double>(), beta, matrix_out->data<double>());
}
#ifdef PADDLE_USE_MKLML
#ifdef PADDLE_WITH_MKLML
// Use cblas_{s,d}gemm_batched if available: Run with 1 group of size batchSize.
template <>
void batched_gemm<platform::CPUPlace, float>(
......
......@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#ifdef PADDLE_USE_MKLML
#ifdef PADDLE_WITH_MKLML
#include <mkl_cblas.h>
#include <mkl_lapacke.h>
#include <mkl_vml_functions.h>
......
......@@ -38,7 +38,7 @@ public:
real torch_learningRate = optConfig_.learning_method() == "torch_momentum"
? 1.0 - paraConfig.momentum()
: 1.0;
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
sgdUpdate(learningRate_ * paraConfig.learning_rate() *
(firstTime_ ? 1.0 : torch_learningRate),
paraConfig.momentum(),
......
......@@ -30,7 +30,7 @@ void sgdUpdateCpu(real learningRate,
const real* grad,
real* momentumVec) {
decayRate *= learningRate;
#ifdef PADDLE_USE_MKLML
#ifdef PADDLE_WITH_MKLML
#pragma omp parallel for
#endif
for (size_t i = 0; i < size; ++i) {
......
......@@ -20,7 +20,7 @@ DEFINE_bool(use_gpu, false, "Only support CPU training");
DEFINE_bool(use_gpu, true, "Whether to use GPU for training");
#endif
#ifdef PADDLE_USE_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
// TODO(TJ): change to true when MKLDNN layers support multi-inputs
DEFINE_bool(use_mkldnn, false, "Default still keep use CPU training");
#else
......
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