Merge branch 'develop' of https://github.com/deephealthproject/eddl i…

…nto develop
deephealthproject · Jan 26, 2021 · ba43ddc · ba43ddc
2 parents c933d30 + 74ffe85
commit ba43ddc
Showing 1 changed file with 9 additions and 8 deletions.
diff --git a/examples/nn/4_NLP/4_nlp_video_to_labels.cpp b/examples/nn/4_NLP/4_nlp_video_to_labels.cpp
@@ -30,14 +30,15 @@ int main(int argc, char **argv) {
     layer in  = Input({10, 3, size, size});
     layer l=in;
     l = Permute(l, {1, 0, 2, 3});  // Conv3D expects (B,C,dim1,dim2,dim3)
-    l=MaxPool3D(ReLu(Conv3D(l,4,{3, 3, 3},{1, 1, 1}, "same")),{2, 2, 2}, {2, 2, 2}, "same");
-    l=MaxPool3D(ReLu(Conv3D(l,8,{3, 3, 3},{1, 1, 1}, "same")),{2, 2, 2}, {2, 2, 2}, "same");
-    l=MaxPool3D(ReLu(Conv3D(l,16,{3, 3, 3},{1, 1, 1}, "same")),{2, 2, 2}, {2, 2, 2}, "same");
+    l=MaxPool3D(ReLu(Conv3D(l,4,{1, 3, 3},{1, 1, 1}, "same")),{1, 2, 2}, {1, 2, 2}, "same");
+    l=MaxPool3D(ReLu(Conv3D(l,8,{1, 3, 3},{1, 1, 1}, "same")),{1, 2, 2}, {1, 2, 2}, "same");
+    l=MaxPool3D(ReLu(Conv3D(l,16,{1, 3, 3},{1, 1, 1}, "same")),{1, 2, 2}, {1, 2, 2}, "same");
     l=GlobalMaxPool3D(l);
-    l = Reshape(l, {-1});
-    l = LSTM(l, 128);
-    l = Dense(l, 100);
-    l = ReLu(l);
+    l=Squeeze(l);
+//    l = Reshape(l, {10, -1});
+//    l = LSTM(l, 128);
+//    l = Dense(l, 100);
+//    l = ReLu(l);
     l = Dense(l, 2);
     layer out = ReLu(l);
     model deepVO = Model({in},{out});
@@ -54,7 +55,7 @@ int main(int argc, char **argv) {
 
     // 32 samples that are sequences of 10 RGB images of 256x256. Target 2 values per image, a sequence as well
     Tensor* seqImages = Tensor::randu({32, 10, 3, size, size});
-    Tensor* seqLabels = Tensor::randu({32, 10, 2});
+    Tensor* seqLabels = Tensor::randu({32, 2});
 
 
     fit(deepVO, {seqImages}, {seqLabels}, 4, 10);