rename SetTMP

ad3fc86f · xiaotong · 22df3e17 · ad3fc86f · ad3fc86f · ad3fc86f
Commit ad3fc86f authored Sep 18, 2018 by xiaotong
--- a/source/tensor/XTensor.cpp
+++ b/source/tensor/XTensor.cpp
@@ -202,7 +202,7 @@ XTensor::~XTensor()
        dims[0] = -dims[0];
        XTensor * newTensor = new XTensor(order, dims, dataType, denseRatio, devID, mem);
-        newTensor->SetTMP();
+        newTensor->SetTMPFlag();
        newTensor->data = data;
        data = NULL;
@@ -244,6 +244,7 @@ void XTensor::Init()
    isInit = false;
    isTmp =  false;
    isGrad = false;
+    isVar  = false;
    visitMark = 0;
    grad = NULL;
 }
@@ -297,7 +298,7 @@ XTensor& XTensor::operator= (const XTensor& tensor)
        dims[0] = -dims[0];
        XTensor * newTensor = new XTensor(order, dims, dataType, denseRatio, devID, mem);
-        newTensor->SetTMP();
+        newTensor->SetTMPFlag();
        newTensor->data = data;
        newTensor->dataHost = dataHost;
        newTensor->signature = tensor.signature;
@@ -1125,7 +1126,7 @@ int XTensor::GetNonzeroSize()
 set the tensor as "temporary" 
 >> myIsTMP - the flag
 */
-void XTensor::SetTMP(bool myIsTmp)
+void XTensor::SetTMPFlag(bool myIsTmp)
 {
    isTmp = myIsTmp;
 }
@@ -1134,12 +1135,23 @@ void XTensor::SetTMP(bool myIsTmp)
 set the tensor as "keep-gradient" 
 >> myIsGrad - the flag
 */
-void XTensor::SetGrad(bool myIsGrad)
+void XTensor::SetGradFlag(bool myIsGrad)
 {
    isGrad = myIsGrad;
 }
 /* 
+set the tensor as "variable" 
+>> myIsVar - the flag
+*/
+void XTensor::SetVarFlag(bool myIsVar)
+{
+    isVar = myIsVar;
+    if(isVar)
+        SetGradFlag(true);
+}
+/* 
 resize a tensor with a specified tensor size
 >> myOrder - order of the tensor
 >> myDimSize - the size of each dimension

--- a/source/tensor/XTensor.h
+++ b/source/tensor/XTensor.h
@@ -145,6 +145,9 @@ public:
    /* indicates whether the tensor keeps the gradient when used as model parameters */
    bool isGrad;
+    /* indicates whether the tensor is used as paramters (or variables) */
+    bool isVar;
    /* mark for traversing the gragh */
    unsigned int visitMark;
@@ -319,10 +322,13 @@ public:
    int GetNonzeroSize();
    /* set the tensor as "temporary" */
-    void SetTMP(bool myIsTmp = true);
+    void SetTMPFlag(bool myIsTmp = true);
    /* set the tensor as "keep-gradient" */
-    void SetGrad(bool myIsGrad = true);
+    void SetGradFlag(bool myIsGrad = true);
+    /* set the tensor as "variable" */
+    void SetVarFlag(bool myIsVar = true);
    /* resize a matrix with a specified matrix size */
    bool Resize(const int myOrder, const int * myDimSize,

--- a/source/tensor/core/arithmetic/Div.cpp
+++ b/source/tensor/core/arithmetic/Div.cpp
@@ -181,7 +181,7 @@ where i is the index of the item
 XTensor Div(const XTensor &a, const XTensor &b, DTYPE alpha, int leadingDim)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    int n = GetDivDimIndex(a, b);

--- a/source/tensor/core/arithmetic/DivDim.cpp
+++ b/source/tensor/core/arithmetic/DivDim.cpp
@@ -150,7 +150,7 @@ i.e., a is divided with b by broadcasting
 XTensor DivDim(const XTensor &a, const XTensor &b, int n, DTYPE alpha)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _Div function */
    _DivDim(&a, &b, &c, n, alpha);

--- a/source/tensor/core/arithmetic/MatrixMul.cpp
+++ b/source/tensor/core/arithmetic/MatrixMul.cpp
@@ -249,7 +249,7 @@ XTensor MatrixMul(const XTensor &a, MATRIX_TRANS_TYPE transposedA,
    float dr = (!a.isSparse || !b.isSparse) ? 1.0F : MAX(a.denseRatio, b.denseRatio);
    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _MatrixMul function */
    _MatrixMul(&a, transposedA, &b, transposedB, &c, alpha, 0, parallelRunner);
@@ -299,7 +299,7 @@ XTensor MatrixMul(const XTensor &a, const XTensor &b,
    float dr = (!a.isSparse || !b.isSparse) ? 1.0F : MAX(a.denseRatio, b.denseRatio);
    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _MatrixMul function */
    _MatrixMul(&a, X_NOTRANS, &b, X_NOTRANS, &c, alpha, 0, parallelRunner);

--- a/source/tensor/core/arithmetic/MatrixMulBatched.cpp
+++ b/source/tensor/core/arithmetic/MatrixMulBatched.cpp
@@ -314,7 +314,7 @@ XTensor MatrixMulBatched(const XTensor &a, MATRIX_TRANS_TYPE transposedA, const 
    float dr = (!a.isSparse || !b.isSparse) ? 1.0F : MAX(a.denseRatio, b.denseRatio);
    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    c.SetTMP();
+    c.SetTMPFlag();
    /*call _MatrixMulBatched function */
    _MatrixMulBatched(&a, transposedA, &b, transposedB, &c, alpha, 0, parallelRunner);
@@ -370,7 +370,7 @@ XTensor MatrixMulBatched(const XTensor &a, const XTensor &b,
    float dr = (!a.isSparse || !b.isSparse) ? 1.0F : MAX(a.denseRatio, b.denseRatio);
    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    c.SetTMP();
+    c.SetTMPFlag();
    /*call _MatrixMulBatched function */
    _MatrixMulBatched(&a, X_NOTRANS, &b, X_NOTRANS, &c, alpha, 0, parallelRunner);

--- a/source/tensor/core/arithmetic/Multiply.cpp
+++ b/source/tensor/core/arithmetic/Multiply.cpp
@@ -182,7 +182,7 @@ XTensor Multiply(const XTensor &a, const XTensor &b, DTYPE alpha, int leadingDim
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    int n = GetMultiplyDimIndex(a, b);

--- a/source/tensor/core/arithmetic/MultiplyDim.cpp
+++ b/source/tensor/core/arithmetic/MultiplyDim.cpp
@@ -148,7 +148,7 @@ i.e., a is multiplied with b by broadcasting
 XTensor MultiplyDim(const XTensor &a, const XTensor &b, int n, DTYPE alpha)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _Multiply function */
    _MultiplyDim(&a, &b, &c, n, alpha);

--- a/source/tensor/core/arithmetic/Negate.cpp
+++ b/source/tensor/core/arithmetic/Negate.cpp
@@ -68,7 +68,7 @@ make a new tensor to keep the result and return it
 XTensor Negate(const XTensor & a)
 {
    XTensor b(&a);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _Negate function */
    _Negate(&a, &b);

--- a/source/tensor/core/arithmetic/Sign.cpp
+++ b/source/tensor/core/arithmetic/Sign.cpp
@@ -74,7 +74,7 @@ make a new tensor to keep the result and return it
 XTensor Sign(const XTensor & a)
 {
    XTensor b(&a);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _Sign function */
    _Sign(&a, &b);

--- a/source/tensor/core/arithmetic/Sub.cpp
+++ b/source/tensor/core/arithmetic/Sub.cpp
@@ -164,7 +164,7 @@ make a new tensor c to keep the result and return it
 XTensor Sub(const XTensor &a, const XTensor &b, DTYPE beta)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    int n = GetSubDimIndex(a, b);

--- a/source/tensor/core/arithmetic/SubDim.cpp
+++ b/source/tensor/core/arithmetic/SubDim.cpp
@@ -150,7 +150,7 @@ i.e., a is subtracted with b by broadcasting
 XTensor SubDim(const XTensor &a, const XTensor &b, int n, DTYPE beta)
 {
 	XTensor c(&a);
-	c.SetTMP();
+	c.SetTMPFlag();
 	/* call _Sub function */
 	_SubDim(&a, &b, &c, n, beta);

--- a/source/tensor/core/arithmetic/Sum.cpp
+++ b/source/tensor/core/arithmetic/Sum.cpp
@@ -169,7 +169,7 @@ make a new tensor c to keep the result and return it
 XTensor Sum(const XTensor &a, const XTensor &b, DTYPE beta)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    int n = GetSumDimIndex(a, b);

--- a/source/tensor/core/arithmetic/SumDim.cpp
+++ b/source/tensor/core/arithmetic/SumDim.cpp
@@ -150,7 +150,7 @@ i.e., a is summed with b by broadcasting
 XTensor SumDim(const XTensor &a, const XTensor &b, int n, DTYPE beta)
 {
    XTensor c(&a);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _Sum function */
    _SumDim(&a, &b, &c, n, beta);

--- a/source/tensor/core/getandset/Select.cpp
+++ b/source/tensor/core/getandset/Select.cpp
@@ -111,7 +111,7 @@ XTensor SelectRange(const XTensor &a, int dim, int low, int high)
    float dr = (!a.isSparse) ? 1.0F : a.denseRatio;
    XTensor c(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    c.SetTMP();
+    c.SetTMPFlag();
    /* call _SelectRange function */
    _SelectRange(&a, &c, dim, low, high);

--- a/source/tensor/core/math/Clip.cpp
+++ b/source/tensor/core/math/Clip.cpp
@@ -81,7 +81,7 @@ make a new tensor to keep the result and return it
 XTensor Clip(const XTensor & a, DTYPE lower, DTYPE upper)
 {
 	XTensor b(&a);
-	b.SetTMP();
+	b.SetTMPFlag();
 	/* call _Clip function */
 	_Clip(&a, &b, lower, upper);

--- a/source/tensor/core/math/Normalize.cpp
+++ b/source/tensor/core/math/Normalize.cpp
@@ -132,7 +132,7 @@ where a and b are the scalar and bias respectively, and \epsilon is the adjustme
 XTensor Normalize(const XTensor &input, int dim, const XTensor &mean, const XTensor &var, const XTensor &a, const XTensor &b, DTYPE epsilon)
 {
    XTensor output(&input);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _Normalize function */
    _Normalize(&input, &output, dim, &mean, &var, &a, &b, epsilon);

--- a/source/tensor/core/math/Power.cpp
+++ b/source/tensor/core/math/Power.cpp
@@ -90,7 +90,7 @@ make a new tensor to keep the result and return it
 XTensor Power(const XTensor & a, DTYPE p)
 {
    XTensor b(&a);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _Power function */
    _Power(&a, &b, p);

--- a/source/tensor/core/math/ScaleAndShift.cpp
+++ b/source/tensor/core/math/ScaleAndShift.cpp
@@ -105,7 +105,7 @@ b = a * scale + shift
 XTensor ScaleAndShift(const XTensor &a, DTYPE scale, DTYPE shift)
 {
    XTensor b(&a);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _ScaleAndShift function */
    _ScaleAndShift(&a, &b, scale, shift);

--- a/source/tensor/core/math/Unary.cpp
+++ b/source/tensor/core/math/Unary.cpp
@@ -65,7 +65,7 @@ void _funcNameMe(XTensor * a)                                               \
 XTensor funcName(const XTensor &a)                                          \
 {                                                                           \
    XTensor b(&a);                                                          \
-    b.SetTMP();                                                             \
+    b.SetTMPFlag();                                                             \
    _funcName(&a, &b);                                                      \
    XLink::MakeLink(&a, NULL, &b, operationId);                             \
    return b;                                                               \
@@ -140,7 +140,7 @@ void _funcNameMe(XTensor * a)                                               \
 XTensor funcName(const XTensor &a)                                          \
 {                                                                           \
    XTensor b(&a);                                                          \
-    b.SetTMP();                                                             \
+    b.SetTMPFlag();                                                             \
    _funcName(&a, &b);                                                      \
    XLink::MakeLink(&a, NULL, &b, operationId);                             \
    return b;                                                               \

--- a/source/tensor/core/movement/CopyIndexed.cpp
+++ b/source/tensor/core/movement/CopyIndexed.cpp
@@ -130,7 +130,7 @@ XTensor CopyIndexed(const XTensor &s, int dim, int * srcIndex, int indexSize, in
    float dr = (!s.isSparse) ? 1.0F : s.denseRatio;
    XTensor t(order, dimSize, s.dataType, dr, s.devID, s.mem);
-    t.SetTMP();
+    t.SetTMPFlag();
    /* call _CopyIndexed function */
    _CopyIndexed(&s, &t, dim, srcIndex, indexSize, tgtIndex, copyNum);

--- a/source/tensor/core/movement/CopyValues.cpp
+++ b/source/tensor/core/movement/CopyValues.cpp
@@ -108,7 +108,7 @@ make a new tensor to keep the result and return it
 XTensor CopyValues(const XTensor &s, XStream * stream)
 {
    XTensor t(&s);
-    t.SetTMP();
+    t.SetTMPFlag();
    /* call _CopyValues function */
    _CopyValues(&s, &t, stream);

--- a/source/tensor/core/reduce/ReduceMax.cpp
+++ b/source/tensor/core/reduce/ReduceMax.cpp
@@ -114,7 +114,7 @@ XTensor ReduceMax(const XTensor &input, int dim)
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceMax function */
    _ReduceMax(&input, &output, dim);

--- a/source/tensor/core/reduce/ReduceMean.cpp
+++ b/source/tensor/core/reduce/ReduceMean.cpp
@@ -71,7 +71,7 @@ XTensor ReduceMean(const XTensor &input, int dim)
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceMean function */
    _ReduceMean(&input, &output, dim);

--- a/source/tensor/core/reduce/ReduceSum.cpp
+++ b/source/tensor/core/reduce/ReduceSum.cpp
@@ -225,7 +225,7 @@ XTensor ReduceSum(const XTensor &input, int dim, const XTensor &shift, DTYPE pow
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceSum function */
    _ReduceSum(&input, &output, dim, &shift, power, isExp);
@@ -271,7 +271,7 @@ XTensor ReduceSum(const XTensor &input, int dim, DTYPE power, bool isExp)
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceSum function */
    _ReduceSum(&input, &output, dim, NULL, power, isExp);

--- a/source/tensor/core/reduce/ReduceSumSquared.cpp
+++ b/source/tensor/core/reduce/ReduceSumSquared.cpp
@@ -67,7 +67,7 @@ XTensor ReduceSumSquared(const XTensor &input, int dim, const XTensor &shift)
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceSumSquared function */
    _ReduceSumSquared(&input, &output, dim, &shift);

--- a/source/tensor/core/reduce/ReduceVariance.cpp
+++ b/source/tensor/core/reduce/ReduceVariance.cpp
@@ -70,7 +70,7 @@ XTensor ReduceVariance(const XTensor &input, int dim, const XTensor &mean)
    float dr = (!input.isSparse) ? 1.0F : input.denseRatio;
    XTensor output(order, dimSize, input.dataType, dr, input.devID, input.mem);
-    output.SetTMP();
+    output.SetTMPFlag();
    /* call _ReduceVariance function */
    _ReduceVariance(&input, &output, dim, &mean);

--- a/source/tensor/core/shape/Concatenate.cpp
+++ b/source/tensor/core/shape/Concatenate.cpp
@@ -93,7 +93,7 @@ XTensor Concatenate(const XList &smalls, int dim)
        float dr = (!tensor->isSparse) ? 1.0F : tensor->denseRatio;
        XTensor big(order, dimSize, tensor->dataType, dr, tensor->devID, tensor->mem);
-        big.SetTMP();
+        big.SetTMPFlag();
        /* call _Merge function */
        _Merge(&smalls, &big, dim);
@@ -121,7 +121,7 @@ XTensor Concatenate(const XList &smalls, int dim)
        float dr = (!tensor->isSparse) ? 1.0F : tensor->denseRatio;
        XTensor big(order, dimSize, tensor->dataType, dr, tensor->devID, tensor->mem);
-        big.SetTMP();
+        big.SetTMPFlag();
        /* call _ConcatenateSolely function */
        _ConcatenateSolely(&smalls, &big, dim);
@@ -194,7 +194,7 @@ XTensor Concatenate(const XTensor &smallA, const XTensor &smallB, int dim)
        float dr = (!tensor->isSparse) ? 1.0F : tensor->denseRatio;
        XTensor big(order, dimSize, tensor->dataType, dr, tensor->devID, tensor->mem);
-        big.SetTMP();
+        big.SetTMPFlag();
        /* call _Merge function */
        _Merge(&smalls, &big, dim);
@@ -222,7 +222,7 @@ XTensor Concatenate(const XTensor &smallA, const XTensor &smallB, int dim)
        float dr = (!tensor->isSparse) ? 1.0F : tensor->denseRatio;
        XTensor big(order, dimSize, tensor->dataType, dr, tensor->devID, tensor->mem);
-        big.SetTMP();
+        big.SetTMPFlag();
        /* call _ConcatenateSolely function */
        _ConcatenateSolely(&smalls, &big, dim);

--- a/source/tensor/core/shape/Merge.cpp
+++ b/source/tensor/core/shape/Merge.cpp
@@ -183,7 +183,7 @@ XTensor Merge(const XTensor &s, int whereToMerge, int leadingDim)
    float dr = (!s.isSparse) ? 1.0F : s.denseRatio;
    XTensor t(order, dimSize, s.dataType, dr, s.devID, s.mem);
-    t.SetTMP();
+    t.SetTMPFlag();
    /* call _Merge function */
    _Merge(&s, &t, whereToMerge, leadingDim);
@@ -334,7 +334,7 @@ XTensor Merge(const XList &smalls, int whereToMerge)
    float dr = (!tensor->isSparse) ? 1.0F : tensor->denseRatio;
    XTensor big(order, dimSize, tensor->dataType, dr, tensor->devID, tensor->mem);
-    big.SetTMP();
+    big.SetTMPFlag();
    /* call _Merge function */
    _Merge(&smalls, &big, whereToMerge);
@@ -371,7 +371,7 @@ XTensor Merge(const XTensor &smallA, const XTensor &smallB, int whereToMerge)
    float dr = (!smallA.isSparse) ? 1.0F : smallA.denseRatio;
    XTensor big(order, dimSize, smallA.dataType, dr, smallA.devID, smallA.mem);
-    big.SetTMP();
+    big.SetTMPFlag();
    XList smalls(2);
    smalls.Add(&smallA);

--- a/source/tensor/core/shape/Split.cpp
+++ b/source/tensor/core/shape/Split.cpp
@@ -184,7 +184,7 @@ XTensor Split(const XTensor &s, int whereToSplit, int splitNum)
    float dr = (!s.isSparse) ? 1.0F : s.denseRatio;
    XTensor t(order, dimSize, s.dataType, dr, s.devID, s.mem);
-    t.SetTMP();
+    t.SetTMPFlag();
    /* call _Split function */
    _Split(&s, &t, whereToSplit, splitNum);

--- a/source/tensor/core/shape/Transpose.cpp
+++ b/source/tensor/core/shape/Transpose.cpp
@@ -138,7 +138,7 @@ XTensor Transpose(const XTensor &a, const int i, const int j)
    float dr = (!a.isSparse) ? 1.0F : a.denseRatio;
    XTensor b(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _Transpose function */
    _Transpose(&a, &b, i, j);

--- a/source/tensor/core/shape/Unsqueeze.cpp
+++ b/source/tensor/core/shape/Unsqueeze.cpp
@@ -122,7 +122,7 @@ XTensor Unsqueeze(const XTensor &a, int dim, int dSize)
    float dr = (!a.isSparse) ? 1.0F : a.denseRatio;
    XTensor b(order, dimSize, a.dataType, dr, a.devID, a.mem);
-    b.SetTMP();
+    b.SetTMPFlag();
    /* call _Unsqueeze function */
    _Unsqueeze(&a, &b, dim, dSize);

--- a/source/tensor/function/HardTanH.cpp
+++ b/source/tensor/function/HardTanH.cpp
@@ -72,7 +72,7 @@ y =  1    if x > 1
 XTensor HardTanH(const XTensor &x)
 {
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _HardTanH function */
    _HardTanH(&x, &y);

--- a/source/tensor/function/Identity.cpp
+++ b/source/tensor/function/Identity.cpp
@@ -46,7 +46,7 @@ make a new tensor to keep the result and return it
 XTensor Identity(const XTensor &x)
 {
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _Identity function */
    _Identity(&x, &y);

--- a/source/tensor/function/LogSoftmax.cpp
+++ b/source/tensor/function/LogSoftmax.cpp
@@ -181,7 +181,7 @@ XTensor LogSoftmax(const XTensor &x, int leadDim)
        ld = x.order - 1;
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _LogSoftmax function */
    _LogSoftmax(&x, &y, ld);

--- a/source/tensor/function/Rectify.cpp
+++ b/source/tensor/function/Rectify.cpp
@@ -65,7 +65,7 @@ make a new tensor to keep the result and return it
 XTensor Rectify(const XTensor &x)
 {
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _Rectify function */
    _Rectify(&x, &y);

--- a/source/tensor/function/Sigmoid.cpp
+++ b/source/tensor/function/Sigmoid.cpp
@@ -63,7 +63,7 @@ make a new tensor to keep the result and return it
 XTensor Sigmoid(const XTensor &x)
 {
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _Sigmoid function */
    _Sigmoid(&x, &y);

--- a/source/tensor/function/Softmax.cpp
+++ b/source/tensor/function/Softmax.cpp
@@ -136,7 +136,7 @@ XTensor Softmax(const XTensor &x, int leadDim)
        ld = x.order - 1;
    XTensor y(&x);
-    y.SetTMP();
+    y.SetTMPFlag();
    /* call _Softmax function */
    _Softmax(&x, &y, ld);