updates

source/sample/transformer/Model.h

@@ -24,17 +24,18 @@
 
 
 #include "Encoder.h"
 #include "Encoder.h"
 #include "Decoder.h"
 #include "Decoder.h"
+#include "Utility.h"
 #include "submodel/FNN.h"
 #include "submodel/FNN.h"
 #include "submodel/Output.h"
 #include "submodel/Output.h"
-#include "Utility.h"
 #include "submodel/Attention.h"
 #include "submodel/Attention.h"
+#include "../../train/XModel.h"
 
 
 namespace nmt
 namespace nmt
 {
 {
 
 
-/* a nmt model that keeps parameters of the encoder,
+/* an nmt model that keeps parameters of the encoder,
    the decoder and the output layer (softmax). */
    the decoder and the output layer (softmax). */
-class Model
+class Model : public XModel
 {
 {
 public:
 public:
     /* device id */
     /* device id */
@@ -85,26 +86,26 @@ public:
 
 
     /* make the encoding network */
     /* make the encoding network */
     XTensor MakeDecoder(XTensor& inputEnc, XTensor& inputDec, XTensor* mask,
     XTensor MakeDecoder(XTensor& inputEnc, XTensor& inputDec, XTensor* mask,
-        XTensor& MaskEncDec, bool isTraining);
+                        XTensor& MaskEncDec, bool isTraining);
 
 
     /* make the network for language modeling (with the output softmax layer) */
     /* make the network for language modeling (with the output softmax layer) */
     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,
     void MakeMT(XTensor& inputEnc, XTensor& inputDec, XTensor& output,
-        XTensor& paddingEnc, XTensor& paddingDec, bool isTraining);
+                XTensor& paddingEnc, XTensor& paddingDec, bool isTraining);
 
 
     /* make the mask for training MT models */
     /* make the mask for training MT models */
     void MakeMTMask(XTensor& inputEnc, XTensor& inputDec,
     void MakeMTMask(XTensor& inputEnc, XTensor& inputDec,
-        XTensor& paddingEnc, XTensor& paddingDec,
-        XTensor& maskEnc, XTensor& maskDec, XTensor& maskEncDec);
+                    XTensor& paddingEnc, XTensor& paddingDec,
+                    XTensor& maskEnc, XTensor& maskDec, XTensor& maskEncDec);
 
 
     /* make the mask of the encoder */
     /* make the mask of the encoder */
     void MakeMTMaskEnc(XTensor& paddingEnc, XTensor& maskEnc);
     void MakeMTMaskEnc(XTensor& paddingEnc, XTensor& maskEnc);
 
 
     /* make the mask of the decoder */
     /* make the mask of the decoder */
     void MakeMTMaskDec(XTensor& paddingEnc, XTensor& paddingDec,
     void MakeMTMaskDec(XTensor& paddingEnc, XTensor& paddingDec,
-        XTensor& maskDec, XTensor& maskEncDec);
+                       XTensor& maskDec, XTensor& maskEncDec);
 
 
     /* get parameter matrices */
     /* get parameter matrices */
     void GetParams(TensorList& list);
     void GetParams(TensorList& list);
@@ -114,6 +115,13 @@ public:
 
 
     /* read the parameters */
     /* read the parameters */
     void Read(FILE* file);
     void Read(FILE* file);
+
+public:
+    /* clone the model (overloaded method of XModel) */
+    XModel * Clone(int devID);
+
+    /* run the neural network (overloaded method of XModel) */
+    bool RunSimple(XList * inputs, XList * outputs, XList * golds, XList * losses);
 };
 };
 
 
 }
 }

source/sample/transformer/train/TrainDataSet.h

@@ -29,6 +29,7 @@
 #include "../../../tensor/XList.h"
 #include "../../../tensor/XList.h"
 #include "../../../tensor/XTensor.h"
 #include "../../../tensor/XTensor.h"
 #include "../../../tensor/XGlobal.h"
 #include "../../../tensor/XGlobal.h"
+#include "../../../train/XBaseTemplate.h"
 
 
 #define MAX_WORD_NUM 120
 #define MAX_WORD_NUM 120
 
 
@@ -56,7 +57,8 @@ struct TrainExample {
 };
 };
 
 
 /* A `TrainDataSet` is associated with a file which contains training data. */
 /* A `TrainDataSet` is associated with a file which contains training data. */
-struct TrainDataSet {
+struct TrainDataSet : public DataDistributeBase
+{
 public:
 public:
     /* the data buffer */
     /* the data buffer */
     TrainBufferType buffer;
     TrainBufferType buffer;
@@ -98,21 +100,6 @@ public:
                          XTensor* batchDec, XTensor* paddingDec, XTensor* label,
                          XTensor* batchDec, XTensor* paddingDec, XTensor* label,
                          size_t minSentBatch, size_t batchSize, int devID);
                          size_t minSentBatch, size_t batchSize, int devID);
 
 
-    /* load the samples into the buffer (a list) */
-    bool LoadBatchToBuf(XList * buf);
-
-    /* load the samples into tensors from the buffer */
-    static
-    bool LoadBatch(XList * buf,
-                   XTensor* batchEnc, XTensor* paddingEnc,
-                   XTensor* batchDec, XTensor* paddingDec, XTensor* label,
-                   size_t minSentBatch, size_t batchSize, int devID,
-                   int &wc, int &sc);
-
-    /* release the samples in a buffer */
-    static
-    void ClearSamples(XList * buf);
-
     /* initialization function */
     /* initialization function */
     void Init(const char* dataFile, int bucketSize, bool training);
     void Init(const char* dataFile, int bucketSize, bool training);