Fix compilation error (#17860)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17860
att
Reviewed By: bddppq
Differential Revision: D14402751
fbshipit-source-id: 2d53b230dfd775372addeab1d3eaf0b9552fae9f
diff --git a/caffe2/operators/normalize_op.cc b/caffe2/operators/normalize_op.cc
index 5c7d3c7..ec0600c 100644
--- a/caffe2/operators/normalize_op.cc
+++ b/caffe2/operators/normalize_op.cc
@@ -1,34 +1,10 @@
#include "caffe2/operators/normalize_op.h"
#include "caffe2/core/tensor.h"
-#include "caffe2/utils/eigen_utils.h"
namespace caffe2 {
template <typename T, class Context>
-void NormalizeOp<T, Context>::DoNormalize(
- const T* xData,
- T* yData,
- const int m,
- const int n,
- const int sf) {
- using InnerStride = Eigen::InnerStride<Eigen::Dynamic>;
- using StridedVec =
- Eigen::Map<Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
- using ConstStridedVec =
- Eigen::Map<const Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
-
- for (int i = 0; i < n; ++i) {
- auto base = (i / sf) * sf * m + (i % sf);
- ConstStridedVec xVec(xData + base, 1, m, InnerStride(sf));
- auto norm = xVec.template lpNorm<2>();
- norm = std::max(norm, kEps_);
- StridedVec yVec(yData + base, 1, m, InnerStride(sf));
- yVec = xVec / norm;
- }
-};
-
-template <typename T, class Context>
void NormalizeGradientOp<T, Context>::DoNormalize(
const T* xData,
const T* gOutData,
diff --git a/caffe2/operators/normalize_op.h b/caffe2/operators/normalize_op.h
index 065484d..57c42e6 100644
--- a/caffe2/operators/normalize_op.h
+++ b/caffe2/operators/normalize_op.h
@@ -3,6 +3,7 @@
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
+#include "caffe2/utils/eigen_utils.h"
#include "caffe2/utils/math.h"
#define KEPS 1e-12f
@@ -35,8 +36,27 @@
private:
const T kEps_ = KEPS;
- void
- DoNormalize(const T* xData, T* yData, const int m, const int n, const int sf);
+ void DoNormalize(
+ const T* xData,
+ T* yData,
+ const int m,
+ const int n,
+ const int sf) {
+ using InnerStride = Eigen::InnerStride<Eigen::Dynamic>;
+ using StridedVec =
+ Eigen::Map<Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
+ using ConstStridedVec =
+ Eigen::Map<const Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
+
+ for (int i = 0; i < n; ++i) {
+ auto base = (i / sf) * sf * m + (i % sf);
+ ConstStridedVec xVec(xData + base, 1, m, InnerStride(sf));
+ auto norm = xVec.template lpNorm<2>();
+ norm = std::max(norm, kEps_);
+ StridedVec yVec(yData + base, 1, m, InnerStride(sf));
+ yVec = xVec / norm;
+ }
+ }
};
template <typename T, class Context>
