improve dropout implementation by broadcasting from different dimensions

source/network/XBackwardMath.cpp

@@ -71,6 +71,8 @@ void XMathGrad::MakeGrad(XTensor * node, bool isEfficient)
         GradMultiply(node, isEfficient);
     else if(operID == MATH_MULTIPLYDIM)
         GradMultiplyDim(node, isEfficient);
+    else if (operID == MATH_MULTIPLYBROADCAST)
+        GradMultiplyBroadcast(node, isEfficient);
     else if(operID == MATH_NEGATE)
         GradNegate(node, isEfficient);
     else if(operID == MATH_NORMALIZE)

source/sample/transformer/T2TDecoder.cpp

@@ -82,7 +82,7 @@ XTensor AttDecoder::Make(XTensor &inputDec, XTensor &outputEnc, XTensor &mask, X
 
     /* dropout */
     if(isTraining && dropoutP > 0)
-        x = Dropout(x, dropoutP, 2);
+        x = Dropout(x, dropoutP, 0, 2);
 
     for(int i = 0; i < nlayer; i++){
         XTensor att;
@@ -97,7 +97,7 @@ XTensor AttDecoder::Make(XTensor &inputDec, XTensor &outputEnc, XTensor &mask, X
 
         /* dropout */
         if(isTraining && dropoutP > 0)
-            att = Dropout(att, dropoutP, 2);
+            att = Dropout(att, dropoutP, 0, 2);
 
         /* residual connection */
         res = Sum(att, x);
@@ -111,7 +111,7 @@ XTensor AttDecoder::Make(XTensor &inputDec, XTensor &outputEnc, XTensor &mask, X
 
         /* dropout */
         if(isTraining && dropoutP > 0)
-            ende = Dropout(ende, dropoutP, 2);
+            ende = Dropout(ende, dropoutP, 0, 2);
 
         /* residual connection */
         res = Sum(ende, x);
@@ -125,7 +125,7 @@ XTensor AttDecoder::Make(XTensor &inputDec, XTensor &outputEnc, XTensor &mask, X
 
         /* dropout */
         if(isTraining && dropoutP > 0)
-            fnn = Dropout(fnn, dropoutP, 2);
+            fnn = Dropout(fnn, dropoutP, 0, 2);
 
         /* residual connection */
         res = Sum(fnn, x);

source/sample/transformer/T2TEncoder.cpp

@@ -103,11 +103,9 @@ XTensor AttEncoder::Make(XTensor &input, XTensor &mask, XTensor &maskEncDec, boo
 
     x = embedder.Make(input);
 
-    //x.Dump(tmpFILE, "embedding: ");
-
     /* dropout */
     if(isTraining && dropoutP > 0)
-        x = Dropout(x, dropoutP, 2);
+        x = Dropout(x, dropoutP, 0, 2);
 
     for(int i = 0; i < nlayer; i++){
         XTensor att;
@@ -120,7 +118,7 @@ XTensor AttEncoder::Make(XTensor &input, XTensor &mask, XTensor &maskEncDec, boo
         
         /* dropout */
         if(isTraining && dropoutP > 0)
-            att = Dropout(att, dropoutP, 2);
+            att = Dropout(att, dropoutP, 0, 2);
 
         /* residual connection */
         res = Sum(att, x);
@@ -133,7 +131,7 @@ XTensor AttEncoder::Make(XTensor &input, XTensor &mask, XTensor &maskEncDec, boo
 
         /* dropout */
         if(isTraining && dropoutP > 0)
-            fnn = Dropout(fnn, dropoutP, 2);
+            fnn = Dropout(fnn, dropoutP, 0, 2);
 
         /* residual connection */
         res = Sum(fnn, x);

source/sample/transformer/Transformer.cpp

@@ -36,8 +36,6 @@ int TransformerMain(int argc, const char ** argv)
 {
     if(argc == 0)
         return 1;
-    
-    fprintf(stderr, "%e\n", log(1e-8F));
 
     char ** args = new char*[argc];
     for(int i = 0; i < argc; i++){