Merge with HU Chi branch.

1. Offer global setting for enableGrad.
2. Update XList.
3. Minor error fixed.

source/tensor/XCall.h

@@ -26,6 +26,9 @@
 
 namespace nts { // namespace nts(NiuTrans.Tensor)
 
+/* default settings */
+#define X_ENABLE_GRAD false
+
 /*
 * we define the "new and delete" functions below
 */
@@ -38,13 +41,13 @@ void InitTensorV2(XTensor * tensor,
 /* initialize a dense XTensor */
 void InitTensor(XTensor * tensor,
                 const int myOrder, const int * myDimSize, const TENSOR_DATA_TYPE myDataType = X_FLOAT,
-                const int myDevID = -1, const bool isEnableGrad = true);
+                const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a scalar V2 */
 void InitTensor0DV2(XTensor * tensor, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, XMem * myMem = NULL);
 
 /* initialize a scalar */
-void InitTensor0D(XTensor * tensor, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+void InitTensor0D(XTensor * tensor, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a dense vector V2 */
 void InitTensor1DV2(XTensor * tensor, const int num, 
@@ -52,7 +55,7 @@ void InitTensor1DV2(XTensor * tensor, const int num,
 
 /* initialize a dense vector */
 void InitTensor1D(XTensor * tensor, const int num, 
-                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a dense matrix V2 */
 void InitTensor2DV2(XTensor * tensor, const int rowNum, const int colNum,
@@ -60,7 +63,7 @@ void InitTensor2DV2(XTensor * tensor, const int rowNum, const int colNum,
 
 /* initialize a dense matrix */
 void InitTensor2D(XTensor * tensor, const int rowNum, const int colNum,
-                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a dense 3d tensor V2 */
 void InitTensor3DV2(XTensor * tensor, const int d0, const int d1, const int d2,
@@ -68,7 +71,7 @@ void InitTensor3DV2(XTensor * tensor, const int d0, const int d1, const int d2,
 
 /* initialize a dense 3d tensor */
 void InitTensor3D(XTensor * tensor, const int d0, const int d1, const int d2,
-                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
     
 /* initialize a dense 4d tensor V2 */
 void InitTensor4DV2(XTensor * tensor, const int d0, const int d1, const int d2, const int d3,
@@ -76,7 +79,7 @@ void InitTensor4DV2(XTensor * tensor, const int d0, const int d1, const int d2,
 
 /* initialize a dense 4d tensor */
 void InitTensor4D(XTensor * tensor, const int d0, const int d1, const int d2, const int d3,
-                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a dense 5d tensor V2 */
 void InitTensor5DV2(XTensor * tensor, const int d0, const int d1, const int d2, const int d3, const int d4,
@@ -84,7 +87,7 @@ void InitTensor5DV2(XTensor * tensor, const int d0, const int d1, const int d2,
 
 /* initialize a dense 5d tensor */
 void InitTensor5D(XTensor * tensor, const int d0, const int d1, const int d2, const int d3, const int d4,
-                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                  const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* initialize a tensor with a reference tensor V2 */
 void InitTensorV2(XTensor * tensor, const XTensor * reference);
@@ -104,7 +107,7 @@ XTensor * NewTensorV2(const int myOrder, const int * myDimSize, const TENSOR_DAT
 
 /* generate a dense XTensor */
 XTensor * NewTensor(const int myOrder, const int * myDimSize, const TENSOR_DATA_TYPE myDataType = X_FLOAT,
-                    const int myDevID = -1, const bool isEnableGrad = true);
+                    const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a XTensor which allocates data on the buffer V2 */
 XTensor * NewTensorBufV2(const int myOrder, const int * myDimSize,
@@ -113,26 +116,26 @@ XTensor * NewTensorBufV2(const int myOrder, const int * myDimSize,
 
 /* generate a dense XTensor which allocates data on the buffer */
 XTensor * NewTensorBuf(const int myOrder, const int * myDimSize,
-                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a XTensor which allocates data on the buffer V2 */
 XTensor * NewTensorBufV2(const XTensor * reference, int devID, XMem * myMem);
 
 /* generate a XTensor which allocates data on the buffer */
-XTensor * NewTensorBuf(const XTensor * reference, int devID, const bool isEnableGrad = true);
+XTensor * NewTensorBuf(const XTensor * reference, int devID, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a scalar V2 */
 XTensor * NewTensor0DV2(const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, XMem * myMem = NULL);
 
 /* generate a scalar */
-XTensor * NewTensor0D(const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+XTensor * NewTensor0D(const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense vector V2 */
 XTensor * NewTensor1DV2(const int num, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, 
                         XMem * myMem = NULL);
 
 /* generate a dense vector */
-XTensor * NewTensor1D(const int num, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = true);
+XTensor * NewTensor1D(const int num, const TENSOR_DATA_TYPE myDataType = X_FLOAT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense matrix V2 */
 XTensor * NewTensor2DV2(const int rowNum, const int colNum, 
@@ -142,7 +145,7 @@ XTensor * NewTensor2DV2(const int rowNum, const int colNum,
 /* generate a dense matrix */
 XTensor * NewTensor2D(const int rowNum, const int colNum, 
                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, 
-                      const int myDevID = -1, const bool isEnableGrad = true);
+                      const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense 3d tensor V2 */
 XTensor * NewTensor3DV2(const int d0, const int d1, const int d2, 
@@ -152,7 +155,7 @@ XTensor * NewTensor3DV2(const int d0, const int d1, const int d2,
 /* generate a dense 3d tensor */
 XTensor * NewTensor3D(const int d0, const int d1, const int d2, 
                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, 
-                      const int myDevID = -1, const bool isEnableGrad = true);
+                      const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense 4d tensor V2 */
 XTensor * NewTensor4DV2(const int d0, const int d1, const int d2, const int d3,
@@ -162,7 +165,7 @@ XTensor * NewTensor4DV2(const int d0, const int d1, const int d2, const int d3,
 /* generate a dense 4d tensor */
 XTensor * NewTensor4D(const int d0, const int d1, const int d2, const int d3,
                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, 
-                      const int myDevID = -1, const bool isEnableGrad = true);
+                      const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense 5d tensor V2 */
 XTensor * NewTensor5DV2(const int d0, const int d1, const int d2, const int d3, const int d4,
@@ -172,10 +175,10 @@ XTensor * NewTensor5DV2(const int d0, const int d1, const int d2, const int d3,
 /* generate a dense 5d tensor */
 XTensor * NewTensor5D(const int d0, const int d1, const int d2, const int d3, const int d4,
                       const TENSOR_DATA_TYPE myDataType = X_FLOAT, 
-                      const int myDevID = -1, const bool isEnableGrad = true);
+                      const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a dense vector by range */
-XTensor * NewTensorRange(int lower, int upper, int step, const TENSOR_DATA_TYPE myDataType = X_INT, const int myDevID = -1, const bool isEnableGrad = true);
+XTensor * NewTensorRange(int lower, int upper, int step, const TENSOR_DATA_TYPE myDataType = X_INT, const int myDevID = -1, const bool isEnableGrad = X_ENABLE_GRAD);
 
 /* generate a copy of XTensor (with a reference to a given tensor) */
 XTensor * NewTensor(const XTensor * a, bool isFilledData = true);

source/tensor/XList.cpp

@@ -249,26 +249,6 @@ inline int TensorListBase<T>::FindFirst(const T& item)
     return -1;
 }
 
-template <>
-inline int TensorListBase<Example>::FindFirst(const Example& item)
-{
-    for (int i = 0; i < count; i++) {
-        if (item.id == items[i].id)
-            return i;
-    }
-    return -1;
-}
-
-template <>
-inline int TensorListBase<Result>::FindFirst(const Result& item)
-{
-    for (int i = 0; i < count; i++) {
-        if (item.id == items[i].id)
-            return i;
-    }
-    return -1;
-}
-
 /* clear the data array */
 template <typename T>
 void TensorListBase<T>::Clear()
@@ -383,8 +363,7 @@ template struct TensorListBase<long>;
 template struct TensorListBase<float>;
 template struct TensorListBase<short>;
 template struct TensorListBase<XTensor*>;
-template struct TensorListBase<Result>;
-template struct TensorListBase<Example>;
+template struct TensorListBase<uint64_t>;
 template struct TensorListBase<void*>;
 
 } /* end of the nts (NiuTrans.Tensor) namespace */
\ No newline at end of file

source/tensor/XList.h

@@ -26,6 +26,8 @@
 #include "XMem.h"
 #include "XGlobal.h"
 
+#include <cstdint>
+
 #ifndef __TensorList_H__
 #define __TensorList_H__
 
@@ -118,7 +120,14 @@ public:
     void Shuffle(int nround = 10, int beg = -1, int len = 0);
 
     /* short */
-    T& operator[] (int i) { return GetItem(i); };
+    T& operator[] (int i) { 
+        CheckNTErrors(i >= -count && i < count, "Index of a list item is out of scope!");
+        CheckNTErrors(count > 0, "Cannt index the item in an empty list!");
+        if (i < 0)
+            return items[count + i];
+        else
+            return items[i];
+    };
     T& Get(int i) { return GetItem(i); };
     void Set(int i, T item) { SetItem(i, item); };
 };
@@ -132,19 +141,7 @@ typedef TensorListBase<char*> StrList;
 typedef TensorListBase<long> LongList;
 typedef TensorListBase<float> FloatList;
 typedef TensorListBase<short> ShortList;
-
-struct Example {
-    int id;
-    IntList data;
-};
-
-struct Result {
-    int id;
-    IntList data;
-};
-
-typedef TensorListBase<Result> ResultList;
-typedef TensorListBase<Example> ExampleList;
+typedef TensorListBase<uint64_t> UInt64List;
 typedef TensorListBase<XTensor*> TensorList;
 
 } /* end of the nts (NiuTrans.Tensor) namespace */