improve the code of masking

source/sample/transformer/T2TModel.cpp

@@ -203,16 +203,30 @@ void T2TModel::MakeMT(XTensor &inputEnc, XTensor &inputDec, XTensor &output, XTe
     XTensor maskEnc;
     XTensor maskEnc;
     XTensor maskDec;
     XTensor maskDec;
     XTensor maskEncDec;
     XTensor maskEncDec;
-    
-    /* generate mask to see "previous" words on the decoder side */
-    //int len = inputDec.GetDim(inputDec.order - 2);
-    //int * dims = new int[inputDec.order + 1];
-    //for(int i = 0; i < inputDec.order; i++)
-    //    dims[i + 1] = inputDec.GetDim(i);
-    //dims[0] = nhead;
-    //dims[inputDec.order] = len;
-    //InitTensor(&maskDec, inputDec.order + 1, dims, X_FLOAT, 1.0F, inputDec.devID, inputDec.mem);
 
 
+    MakeMTMask(inputEnc, inputDec, paddingEnc, paddingDec, maskEnc, maskDec, maskEncDec);
+
+    encoding = MakeEncoder(inputEnc, maskEnc, isTraining);
+
+    decoding = MakeDecoder(inputDec, encoding, maskDec, maskEncDec, isTraining);
+
+    outputLayer->Make(decoding, output);
+}
+
+/* 
+make the mask for training MT models 
+>> inputEnc - input of the encoder
+>> inputDec - input of the decoder
+>> paddingEnc - padding of the encoder input
+>> paddingDec - padding of the decoder input
+>> maskEnc - mask of the encoder self-attention
+>> maksDec - mask of the decoder self-attention
+>> maksEncDec - mask of the decoder enc-dec attention
+*/
+void T2TModel::MakeMTMask(XTensor &inputEnc,   XTensor &inputDec, 
+                          XTensor &paddingEnc, XTensor &paddingDec, 
+                          XTensor &maskEnc,    XTensor &maskDec,    XTensor &maskEncDec)
+{
     int len = inputDec.GetDim(inputDec.order - 1);
     int len = inputDec.GetDim(inputDec.order - 1);
     int * dims = new int[inputDec.order + 2];
     int * dims = new int[inputDec.order + 2];
     for(int i = 0; i < inputDec.order; i++)
     for(int i = 0; i < inputDec.order; i++)
@@ -236,8 +250,6 @@ void T2TModel::MakeMT(XTensor &inputEnc, XTensor &inputDec, XTensor &output, XTe
     XTensor * maskEncDecTMPDec = NewTensorBuf(maskEncDecTMPEnc, paddingEnc.devID, paddingEnc.mem);
     XTensor * maskEncDecTMPDec = NewTensorBuf(maskEncDecTMPEnc, paddingEnc.devID, paddingEnc.mem);
 
 
     _Unsqueeze(&paddingEnc, maskEncDecTMPEnc, paddingEnc.order - 1, paddingDec.GetDim(-1));
     _Unsqueeze(&paddingEnc, maskEncDecTMPEnc, paddingEnc.order - 1, paddingDec.GetDim(-1));
-    //_Unsqueeze(&paddingDec, maskEncDecTMPDec, paddingEnc.order, paddingEnc.GetDim(-1));
-    //_Multiply(maskEncDecTMPDec, maskEncDecTMPEnc, maskEncDecTMPDec);
     _ScaleAndShiftMe(maskEncDecTMPEnc, 1e9F, -1e9F);
     _ScaleAndShiftMe(maskEncDecTMPEnc, 1e9F, -1e9F);
     _Unsqueeze(maskEncDecTMPEnc, &maskEncDec, 0, dims[0]);
     _Unsqueeze(maskEncDecTMPEnc, &maskEncDec, 0, dims[0]);
 
 
@@ -273,12 +285,6 @@ void T2TModel::MakeMT(XTensor &inputEnc, XTensor &inputDec, XTensor &output, XTe
     /* generate the mask on the source language side (for padding) */
     /* generate the mask on the source language side (for padding) */
     _Sum(&maskEnc, padding3, &maskEnc);
     _Sum(&maskEnc, padding3, &maskEnc);
 
 
-    encoding = MakeEncoder(inputEnc, maskEnc, isTraining);
-
-    decoding = MakeDecoder(inputDec, encoding, maskDec, maskEncDec, isTraining);
-
-    outputLayer->Make(decoding, output);
-
     delete[] dims;
     delete[] dims;
     delete[] dimsPadding;
     delete[] dimsPadding;
 
 

source/sample/transformer/T2TModel.h

@@ -81,7 +81,13 @@ public:
     void MakeLM(XTensor &input, XTensor &output, XTensor &padding, bool isTraining);
     void MakeLM(XTensor &input, XTensor &output, XTensor &padding, bool isTraining);
 
 
     /* make the network for machine translation (with the output softmax layer) */
     /* make the network for machine translation (with the output softmax layer) */
-    void MakeMT(XTensor &inputEnc, XTensor &inputDec, XTensor &output, XTensor &paddingEnc, XTensor &paddingDec, bool isTraining);
+    void MakeMT(XTensor &inputEnc, XTensor &inputDec, XTensor &output, 
+                XTensor &paddingEnc, XTensor &paddingDec, bool isTraining);
+
+    /* make the mask for training MT models */
+    void MakeMTMask(XTensor &inputEnc, XTensor &inputDec, 
+                    XTensor &paddingEnc, XTensor &paddingDec, 
+                    XTensor &maskEnc, XTensor &maskDec, XTensor &maskEncDec);
 
 
     /* get parameter matrics */
     /* get parameter matrics */
     void GetParams(XList &list);
     void GetParams(XList &list);