path: root/include/caffe/layers/euclidean_loss_layer.hpp
diff options
Diffstat (limited to 'include/caffe/layers/euclidean_loss_layer.hpp')
1 files changed, 1 insertions, 1 deletions
diff --git a/include/caffe/layers/euclidean_loss_layer.hpp b/include/caffe/layers/euclidean_loss_layer.hpp
index f564569..24568c5 100644
--- a/include/caffe/layers/euclidean_loss_layer.hpp
+++ b/include/caffe/layers/euclidean_loss_layer.hpp
@@ -30,7 +30,7 @@ namespace caffe {
* This can be used for least-squares regression tasks. An InnerProductLayer
* input to a EuclideanLossLayer exactly formulates a linear least squares
* regression problem. With non-zero weight decay the problem becomes one of
- * ridge regression -- see src/caffe/test/test_sgd_solver.cpp for a concrete
+ * ridge regression -- see src/caffe/test/test_gradient_based_solver.cpp for a concrete
* example wherein we check that the gradients computed for a Net with exactly
* this structure match hand-computed gradient formulas for ridge regression.