da in examples

deephealthproject · Nov 29, 2019 · b72e902 · b72e902
1 parent 7619a2e
commit b72e902
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Showing 4 changed files with 12 additions and 15 deletions.
diff --git a/examples/NN/2_CIFAR10/2_cifar_conv_da.cpp b/examples/NN/2_CIFAR10/2_cifar_conv_da.cpp
@@ -38,13 +38,8 @@ int main(int argc, char **argv){
     layer l=in;
 
     // Data augmentation
-//    l = ShiftRandom(l, {-0.2f, +0.2f}, {-0.2f, +0.2f});
-//    l = RotateRandom(l, {-30.0f, +30.0f});
-//    l = ScaleRandom(l, {0.85f, 2.0f});
-//    l = FlipRandom(l, 1);
-//    l = CropRandom(l, {28, 28});
-//    l = CropScaleRandom(l, {0.f, 1.0f});
-//    l = CutoutRandom(l, {0.0f, 0.3f}, {0.0f, 0.3f});
+    l = CropScaleRandom(l, {0.8f, 1.0f});
+    l = Flip(l,1);
 
     l=MaxPool(ReLu(Conv(l,32,{3,3},{1,1})),{2,2});
     l=MaxPool(ReLu(Conv(l,64,{3,3},{1,1})),{2,2});

diff --git a/examples/NN/2_CIFAR10/4_cifar_vgg16_bn.cpp b/examples/NN/2_CIFAR10/4_cifar_vgg16_bn.cpp
@@ -27,7 +27,7 @@ layer Block1(layer l,int filters) {
 }
 layer Block3_2(layer l,int filters) {
   l=ReLu(BatchNormalization(Conv(l,filters,{3,3},{1,1})));
-  l=BatchNormalization(ReLu(Conv(l,filters,{3,3},{1,1})));
+  l=ReLu(BatchNormalization(Conv(l,filters,{3,3},{1,1})));
   return l;
 }
 
@@ -46,6 +46,10 @@ int main(int argc, char **argv){
   layer in=Input({3,32,32});
   layer l=in;
 
+  // Data augmentation
+  l = CropScaleRandom(l, {0.8f, 1.0f});
+  l = Flip(l,1);
+
   l=MaxPool(Block3_2(l,64));
   l=MaxPool(Block3_2(l,128));
   l=MaxPool(Block1(Block3_2(l,256),256));
@@ -71,7 +75,7 @@ int main(int argc, char **argv){
   );
 
   // plot the model
-  plot(net,"model.pdf");
+  plot(net,"model.pdf","TB");  //Top Bottom plot
 
   // get some info from the network
   summary(net);

diff --git a/examples/NN/2_CIFAR10/6_cifar_resnet_da_bn.cpp b/examples/NN/2_CIFAR10/6_cifar_resnet_da_bn.cpp
@@ -61,9 +61,8 @@ int main(int argc, char **argv){
   layer l=in;
 
   // Data augmentation
-  l = FlipRandom(l, 1);
-  l = ShiftRandom(l, {-0.2f, +0.2f}, {-0.2f, +0.2f});
-  l = ScaleRandom(l, {0.9f, 1.1f});
+  l = CropScaleRandom(l, {0.8f, 1.0f});
+  l = Flip(l,1);
 
   // Resnet-18
   l=ReLu(BG(Conv(l,64,{3,3},{1,1})));

diff --git a/examples/NN/2_CIFAR10/7_cifar_resnet50_da_bn.cpp b/examples/NN/2_CIFAR10/7_cifar_resnet50_da_bn.cpp
@@ -61,9 +61,8 @@ int main(int argc, char **argv){
   layer l=in;
 
   // Data augmentation
-  l = FlipRandom(l, 1);
-  l = ShiftRandom(l, {-0.1f, +0.1f}, {-0.1f, +0.1f});
-  l = ScaleRandom(l, {0.9f, 1.1f});
+  l = CropScaleRandom(l, {0.8f, 1.0f});
+  l = Flip(l,1);
 
   // Resnet-50
   l=ReLu(BG(Conv(l,64,{3,3},{1,1})));