optimize the implementation of LoadBatchMT

source/network/Main.cpp

@@ -35,6 +35,8 @@
 void BackwardTest();
 void BackwardTest();
 void TransposeTest();
 void TransposeTest();
 void SumDimTest();
 void SumDimTest();
+void SplitBackwardTest();
+void MemTest();
 
 
 using namespace nts;
 using namespace nts;
 using namespace fnnlm;
 using namespace fnnlm;
@@ -42,6 +44,10 @@ using namespace transformer;
 
 
 int main( int argc, const char ** argv )
 int main( int argc, const char ** argv )
 {
 {
+    //MemTest();
+    //return 0;
+    //SplitBackwardTest();
+    //return 0;
     //_CrtSetBreakAlloc(896);
     //_CrtSetBreakAlloc(896);
     //BackwardTest();
     //BackwardTest();
     //return 0;
     //return 0;
@@ -209,3 +215,67 @@ void SumDimTest()
 
 
     delete[] data;
     delete[] data;
 }
 }
+
+void SplitBackwardTest()
+{
+    int * dimSize = new int[2];
+    dimSize[0] = 2;
+    dimSize[1] = 4;
+
+    XTensor t1;
+    InitTensor2D(&t1, 2, 4, X_FLOAT, 0, NULL);
+    XTensor t2;
+    InitTensor2D(&t2, 2, 4, X_FLOAT, 0, NULL);
+    XTensor tensor;
+    
+    //_SetDataFixedFloat(&t1, 1.0F);
+    //_SetDataFixedFloat(&t2, 2.0F);
+    t1.SetDataRand();
+    t2.SetDataRand();
+
+    tensor = t1 + t2;
+
+    XList smalls;
+
+    XTensor first;
+    XTensor second;
+    InitTensor2D(&first, 2, 2, X_FLOAT, 0, NULL);
+    InitTensor2D(&second, 2, 2, X_FLOAT, 0, NULL);
+    smalls.Add(&first);
+    smalls.Add(&second);
+
+    Split(tensor, smalls, 1, 2);
+
+    XTensor mul;
+    mul = Sum(first, second);
+
+    XNet net;
+    net.Backward(mul);
+    net.Dump(stderr);
+
+    printf("Done!");
+}
+
+void MemTest()
+{
+    XMem * mem;
+    mem = new XMem(0, FREE_ON_THE_FLY, (MTYPE)MILLION, 1024, MILLION);
+    
+    XTensor tensor;
+    InitTensor2D(&tensor, 2, 4, X_FLOAT, 0, mem);
+    
+    tensor.SetZeroAll();
+
+    tensor.Dump(stderr);
+
+    delete mem;
+
+    if (tensor.mem != NULL) {
+        printf("It isn't null!\n");
+        printf("%d\n", (int)tensor.mem->signature);
+    }
+    else {
+        printf("It's null\n");
+    }
+    tensor.Dump(stderr);
+}
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