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NiuTrans.Tensor
Commit d3ec5df8 by linye
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1. implement SetData by template 2. update float16 datatype of SetData

parent 4b54d3d0
正在显示 包含 112 行增加 和 222 行删除
source/network/Main.cpp
......@@ -399,8 +399,8 @@ void xcTest()
InitTensor2D(&t2, 2, 4, X_FLOAT, 0, NULL);
XTensor tensor;
_SetDataFixedFloat(&t1, 1.0F);
_SetDataFixedFloat(&t2, 2.0F);
_SetDataFixed(&t1, 1.0F);
_SetDataFixed(&t2, 2.0F);
tensor = t1 + t2;
......
source/network/XBackwardLoss.cpp
......@@ -52,15 +52,7 @@ void XLossGrad::MakeGrad(XTensor * node, bool isEfficient)
XTensor * dedy = output->grad;
if (income.tailNum == 1) {
if(dedy->dataType == X_FLOAT)
_SetDataFixedFloat(dedy, 1.0F);
else if(dedy->dataType == X_DOUBLE)
_SetDataFixedDouble(dedy, 1.0);
else if(dedy->dataType == X_INT)
_SetDataFixedInt(dedy, 1);
else
ShowNTErrors("TODO");
_SetDataFixed(dedy, 1.0F);
return;
}
......@@ -144,15 +136,7 @@ void XLossGrad::Compute(XTensor * gold, XTensor * y,
LOSS_FUNCTION_NAME lossName)
{
if(gold == NULL){
if(dedy->dataType == X_FLOAT)
_SetDataFixedFloat(dedy, 1.0F);
else if(dedy->dataType == X_DOUBLE)
_SetDataFixedDouble(dedy, 1.0);
else if(dedy->dataType == X_INT)
_SetDataFixedInt(dedy, 1);
else{
ShowNTErrors("TODO");
}
_SetDataFixed(dedy, 1.0F);
return;
}
......
source/tensor/core/getandset/SetData.cpp
......@@ -25,6 +25,7 @@
#include "SetData.cuh"
#include "../../XUtility.h"
#include "../movement/CopyValues.h"
#include "ConvertDataType.h"
#if !defined( WIN32 ) && !defined( _WIN32 )
#include "sys/time.h"
......@@ -77,153 +78,78 @@ void _SetDataFanInOut(XTensor * tensor, DTYPE gain)
}
/*
generate data items with a fixed value p
generate data items with a fixed value
>> tensor - the tensor whose data array would be initialized
>> p - pointer to the number for initializing the tensor
>> value - pointer to the number for initializing the tensor
*/
void _SetDataFixed(XTensor * tensor, void * valuePointer)
template<class T>
void _SetDataFixed(XTensor * tensor, T value)
{
#ifdef USE_CUDA
if (tensor->devID >= 0) {
_CudaSetDataFixed(tensor, value);
return;
}
#endif
int num = tensor->unitNum;
if(tensor->dataType == X_INT){
int p = *(int*)valuePointer;
if(tensor->devID < 0){
int * d = (int*)tensor->data;
if(num % 4 == 0){
for(int i = 0; i < num; i += 4){
d[i] = p;
d[i + 1] = p;
d[i + 2] = p;
d[i + 3] = p;
}
}
else{
for(int i = 0; i < num; i++)
d[i] = p;
if (tensor->dataType == X_INT) {
int * d = (int*)tensor->data;
int v = (int)value;
if (num % 4 == 0) {
for (int i = 0; i < num; i += 4) {
d[i] = v;
d[i + 1] = v;
d[i + 2] = v;
d[i + 3] = v;
}
}
else{
#ifdef USE_CUDA
_CudaSetDataFixedInt(tensor, p);
#endif
else {
for (int i = 0; i < num; i++)
d[i] = v;
}
}
else if(tensor->dataType == X_FLOAT){
float p = *(float*)valuePointer;
if(tensor->devID < 0){
float * d = (float*)tensor->data;
if(num % 4 == 0){
for(int i = 0; i < num; i += 4){
d[i] = p;
d[i + 1] = p;
d[i + 2] = p;
d[i + 3] = p;
}
}
else{
for(int i = 0; i < num; i++)
d[i] = p;
else if (tensor->dataType == X_FLOAT) {
float * d = (float*)tensor->data;
float v = (float)value;
if (num % 4 == 0) {
for (int i = 0; i < num; i += 4) {
d[i] = v;
d[i + 1] = v;
d[i + 2] = v;
d[i + 3] = v;
}
}
else{
#ifdef USE_CUDA
_CudaSetDataFixedFloat(tensor, p);
#endif
else {
for (int i = 0; i < num; i++)
d[i] = v;
}
}
else if(tensor->dataType == X_DOUBLE){
double p = *(double*)valuePointer;
if(tensor->devID < 0){
double * d = (double*)tensor->data;
if(num % 4 == 0){
for(int i = 0; i < num; i += 4){
d[i] = p;
d[i + 1] = p;
d[i + 2] = p;
d[i + 3] = p;
}
}
else{
for(int i = 0; i < num; i++)
d[i] = p;
else if (tensor->dataType == X_DOUBLE) {
double * d = (double*)tensor->data;
double v = (double)value;
if (num % 4 == 0) {
for (int i = 0; i < num; i += 4) {
d[i] = v;
d[i + 1] = v;
d[i + 2] = v;
d[i + 3] = v;
}
}
else{
#ifdef USE_CUDA
_CudaSetDataFixedDouble(tensor, p);
#endif
else {
for (int i = 0; i < num; i++)
d[i] = v;
}
}
else{
ShowNTErrors("TODO");
}
}
/*
generate data items with a fixed value p (in default type)
>> tensor - the tensor whose data array would be initialized
>> p - number in default type
*/
void SetDataFixed(XTensor &tensor, DTYPE p)
{
_SetDataFixed(&tensor, &p);
}
/*
generate data items with a fixed value p (in integer)
>> tensor - the tensor whose data array would be initialized
>> p - an integer
*/
void SetDataFixedInt(XTensor &tensor, int p)
{
CheckNTErrors(tensor.dataType == X_INT, "An integer tensor is required!");
_SetDataFixed(&tensor, &p);
}
/*
generate data items with a fixed value p (in integer)
>> tensor - the tensor whose data array would be initialized
>> p - an int-valued number
*/
void _SetDataFixedInt(XTensor * tensor, int p)
{
CheckNTErrors(tensor->dataType == X_INT, "the tensor must be in X_INT!");
if(p == 0)
tensor->SetZeroAll();
else
_SetDataFixed(tensor, &p);
}
/*
generate data items with a fixed value p (in float)
>> tensor - the tensor whose data array would be initialized
>> p - a float-valued number
*/
void _SetDataFixedFloat(XTensor * tensor, float p)
{
CheckNTErrors(tensor->dataType == X_FLOAT, "the tensor must be in X_FLOAT!");
if(p == 0)
tensor->SetZeroAll();
else
_SetDataFixed(tensor, &p);
ShowNTErrors("TODO");
}
/*
generate data items with a fixed value p (in double)
>> tensor - the tensor whose data array would be initialized
>> p - a double-valued number
*/
void _SetDataFixedDouble(XTensor * tensor, double p)
{
CheckNTErrors(tensor->dataType == X_DOUBLE, "the tensor must be in X_DOUBLE!");
if(p == 0)
tensor->SetZeroAll();
else
_SetDataFixed(tensor, &p);
}
template void _SetDataFixed<int>(XTensor*, int);
template void _SetDataFixed<float>(XTensor*, float);
template void _SetDataFixed<double>(XTensor*, double);
/*
set data items along with a given dimension (and keep the remaining items unchanged)
......@@ -396,7 +322,7 @@ generate data items with a uniform distribution in [lower, upper]
>> lower - lower value of the range
>> upper - upper value of the range
*/
void _SetDataRand(const XTensor * tensor, DTYPE lower, DTYPE upper)
void _SetDataRand(XTensor * tensor, DTYPE lower, DTYPE upper)
{
CheckNTErrors(upper > lower, "the high value must be greater than low value!");
......@@ -433,10 +359,6 @@ void _SetDataRand(const XTensor * tensor, DTYPE lower, DTYPE upper)
#ifdef USE_CUDA
_CudaSetDataRand(tensor, lower, upper);
#endif
//XTensor * t2 = NewTensor(tensor->order, tensor->dimSize, tensor->dataType, tensor->denseRatio, -1);
//_SetDataRand(t2, low, high);
//_CopyValues(t2, tensor);
//delete t2;
}
}
......@@ -449,10 +371,8 @@ the item to a pre-defined value if the item >= p, set the item to 0 otherwise
>> p - the threshold
>> value - the value we intend to assign to the item
*/
void _SetDataRandP(const XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value)
void _SetDataRandP(XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value)
{
CheckNTErrors(tensor->dataType == DEFAULT_DTYPE, "TODO");
if (tensor->devID < 0) {
_SetDataRand(tensor, lower, upper);
......
source/tensor/core/getandset/SetData.cuh
......@@ -19,6 +19,7 @@
/*
* $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-07-18
* I'm surprised that I did not write this file till today.
* $Update by: Lin Ye (email: linye2015@outlook.com) 2019-07-22 float16 added
*/
#ifndef __SETDATA_CUH__
......@@ -28,14 +29,9 @@
namespace nts { // namespace nts(NiuTrans.Tensor)
/* generate data items with a fixed value p (in int) */
void _CudaSetDataFixedInt(XTensor * tensor, int p);
/* generate data items with a fixed value p (in float) */
void _CudaSetDataFixedFloat(XTensor * tensor, float p);
/* generate data items with a fixed value p (in double) */
void _CudaSetDataFixedDouble(XTensor * tensor, double p);
/* generate data items with a fixed value p (in int, float, float16, double) */
template<class T>
void _CudaSetDataFixed(XTensor * tensor, T p);
/* set data items along with a given dimension (and keep the remaining items unchanged) */
void _CudaSetDataDim(XTensor * tensor, int beg, int len, int dim, DTYPE p);
......@@ -47,11 +43,11 @@ void _CudaSetDataIndexed(XTensor * source, XTensor * modify, int dim, int index)
void _CudaSetDataLowTri(XTensor * tensor, DTYPE p, int shift);
/* generate data items with a uniform distribution in [lower, upper] */
void _CudaSetDataRand(const XTensor * tensor, DTYPE lower, DTYPE upper);
void _CudaSetDataRand(XTensor * tensor, DTYPE lower, DTYPE upper);
/* generate data items with a uniform distribution in [lower, upper] and set
the item to a pre-defined value if the item >= p, set the item to 0 otherwise */
void _CudaSetDataRandP(const XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value);
void _CudaSetDataRandP(XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value);
/* set the data with an array of offsets */
void _CudaSetDataWithOffset(XTensor * tensor, MTYPE * offsets, DTYPE value, MTYPE num);
......
source/tensor/core/getandset/SetData.h
......@@ -24,29 +24,19 @@
#define __SETDATA_H__
#include "../../XTensor.h"
#include "SetData.cuh"
namespace nts { // namespace nts(NiuTrans.Tensor)
/* generate data items with a xavier initialization */
void _SetDataFanInOut(XTensor * tensor, DTYPE gain = 1.0F);
/* generate data items with a fixed value p */
void _SetDataFixed(XTensor * tensor, void * valuePointer);
///* generate data items with a fixed value p */
//void _SetDataFixed(XTensor * tensor, void * valuePointer);
/* generate data items with a fixed value p (in default type) */
void SetDataFixed(XTensor &tensor, DTYPE p);
/* generate data items with a fixed value p (in integer) */
void SetDataFixedInt(XTensor &tensor, int p);
/* generate data items with a fixed value p (in int) */
void _SetDataFixedInt(XTensor * tensor, int p);
/* generate data items with a fixed value p (in float) */
void _SetDataFixedFloat(XTensor * tensor, float p);
/* generate data items with a fixed value p (in double) */
void _SetDataFixedDouble(XTensor * tensor, double p);
template<class T>
void _SetDataFixed(XTensor * tensor, T value);
/* set data items along with a given dimension (and keep the remaining items unchanged) */
void _SetDataDim(XTensor * tensor, int beg, int len, int dim, DTYPE p);
......@@ -58,11 +48,11 @@ void _SetDataIndexed(XTensor * source, XTensor * modify, int dim, int index);
void _SetDataLowTri(XTensor * tensor, DTYPE p, int shift);
/* generate data items with a uniform distribution in [lower, upper] */
void _SetDataRand(const XTensor * tensor, DTYPE lower, DTYPE upper);
void _SetDataRand(XTensor * tensor, DTYPE lower, DTYPE upper);
/* generate data items with a uniform distribution in [lower, upper] and set
the item to a pre-defined value if the item >= p, set the item to 0 otherwise */
void _SetDataRandP(const XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value);
void _SetDataRandP(XTensor * tensor, DTYPE lower, DTYPE upper, DTYPE p, DTYPE value);
/* generate data items with a normal distribution with specified mean and standard deviation */
void _SetDataRandN(XTensor * tensor, DTYPE mean = 0.0F, DTYPE standardDeviation = 1.0F);
......
source/tensor/function/DropoutWithIndex.cpp
......@@ -70,7 +70,7 @@ XTensor DropoutWithIndex(const XTensor &x, XTensor &maskIndex, DTYPE scale)
InitTensor1D(&c, x.unitNum, x.dataType, x.devID, x.mem);
_SetDataFixedFloat(&c, 1.0F);
_SetDataFixed(&c, 1.0F);
_DropoutWithIndex(&x, &maskIndex, &c);
......
source/tensor/function/Loss.cpp
......@@ -385,11 +385,11 @@ void _LossBackward(XTensor * dedy, XTensor * t, XTensor * y,
{
if(t == NULL){
if(dedy->dataType == X_FLOAT)
_SetDataFixedFloat(dedy, 1.0F);
_SetDataFixed(dedy, 1.0F);
else if(dedy->dataType == X_DOUBLE)
_SetDataFixedDouble(dedy, 1.0);
_SetDataFixed(dedy, 1.0);
else if(dedy->dataType == X_INT)
_SetDataFixedInt(dedy, 1);
_SetDataFixed(dedy, 1);
else{
ShowNTErrors("TODO");
}
......
source/tensor/test/TDropout.cpp
......@@ -50,7 +50,7 @@ bool TestDropout1()
XTensor yUser;
/* initialize variables */
_SetDataFixedFloat(x, 1.0F);
_SetDataFixed(x, 1.0F);
y->SetZeroAll();
/* call Dropout function */
......@@ -88,7 +88,7 @@ bool TestDropout1()
XTensor yUserGPU;
/* initialize variables */
_SetDataFixedFloat(xGPU, 1.0F);
_SetDataFixed(xGPU, 1.0F);
yGPU->SetZeroAll();
/* call Dropout function */
......@@ -157,10 +157,10 @@ bool TestDropout2()
XTensor * dedy = NewTensor(order, dimSize);
/* initialize variables */
_SetDataFixedFloat(x, 1.0F);
_SetDataFixed(x, 1.0F);
y->SetZeroAll();
dedx->SetZeroAll();
_SetDataFixedFloat(dedy, 1.5F);
_SetDataFixed(dedy, 1.5F);
/* call Dropout function */
float dropProb = 0.5F;
......@@ -183,10 +183,10 @@ bool TestDropout2()
XTensor * dedyGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0);
/* initialize variables */
_SetDataFixedFloat(xGPU, 1.0F);
_SetDataFixed(xGPU, 1.0F);
yGPU->SetZeroAll();
dedxGPU->SetZeroAll();
_SetDataFixedFloat(dedyGPU, 1.5F);
_SetDataFixed(dedyGPU, 1.5F);
/* call Dropout function */
_Dropout(xGPU, yGPU, seed, dropProb);
......
source/tensor/test/TReduceSum.cpp
......@@ -196,8 +196,8 @@ bool TestReduceSum2()
XTensor tUser;
/* initialize variables */
_SetDataFixedFloat(s, 1.0F);
_SetDataFixedFloat(answer, (float)s->GetDim(1));
_SetDataFixed(s, 1.0F);
_SetDataFixed(answer, (float)s->GetDim(1));
/* call ReduceSum function */
_ReduceSum(s, t, 1);
......@@ -216,7 +216,7 @@ bool TestReduceSum2()
XTensor tUserGPU;
/* initialize variables */
_SetDataFixedFloat(sGPU, 1.0F);
_SetDataFixed(sGPU, 1.0F);
/* call ReduceSum function */
_ReduceSum(sGPU, tGPU, 1);
......@@ -285,8 +285,8 @@ bool TestReduceSum3()
XTensor tUser;
/* initialize variables */
_SetDataFixedFloat(s, 1.0F);
_SetDataFixedFloat(answer, (float)s->GetDim(1));
_SetDataFixed(s, 1.0F);
_SetDataFixed(answer, (float)s->GetDim(1));
/* call ReduceSum function */
_ReduceSum(s, t, 1);
......@@ -305,7 +305,7 @@ bool TestReduceSum3()
XTensor tUserGPU;
/* initialize variables */
_SetDataFixedFloat(sGPU, 1.0F);
_SetDataFixed(sGPU, 1.0F);
/* call ReduceSum function */
_ReduceSum(sGPU, tGPU, 1);
......@@ -374,8 +374,8 @@ bool TestReduceSum4()
XTensor tUser;
/* initialize variables */
_SetDataFixedFloat(s, 1.0F);
_SetDataFixedFloat(answer, (float)s->GetDim(1));
_SetDataFixed(s, 1.0F);
_SetDataFixed(answer, (float)s->GetDim(1));
/* call ReduceSum function */
_ReduceSum(s, t, 1);
......@@ -394,7 +394,7 @@ bool TestReduceSum4()
XTensor tUserGPU;
/* initialize variables */
_SetDataFixedFloat(sGPU, 1.0F);
_SetDataFixed(sGPU, 1.0F);
/* call ReduceSum function */
_ReduceSum(sGPU, tGPU, 1);
......@@ -465,8 +465,8 @@ bool TestReduceSum5()
XTensor tUser;
/* initialize variables */
_SetDataFixedFloat(s, 1.0F);
_SetDataFixedFloat(answer, (float)s->GetDim(1));
_SetDataFixed(s, 1.0F);
_SetDataFixed(answer, (float)s->GetDim(1));
/* call ReduceSum function */
_ReduceSum(s, t, 1);
......@@ -485,7 +485,7 @@ bool TestReduceSum5()
XTensor tUserGPU;
/* initialize variables */
_SetDataFixedFloat(sGPU, 1.0F);
_SetDataFixed(sGPU, 1.0F);
/* call ReduceSum function */
_ReduceSum(sGPU, tGPU, 1);
......@@ -556,8 +556,8 @@ bool TestReduceSum6()
XTensor tUser;
/* initialize variables */
_SetDataFixedFloat(s, 1.0F);
_SetDataFixedFloat(answer, (float)s->GetDim(1));
_SetDataFixed(s, 1.0F);
_SetDataFixed(answer, (float)s->GetDim(1));
/* call ReduceSum function */
_ReduceSum(s, t, 1);
......@@ -576,7 +576,7 @@ bool TestReduceSum6()
XTensor tUserGPU;
/* initialize variables */
_SetDataFixedFloat(sGPU, 1.0F);
_SetDataFixed(sGPU, 1.0F);
/* call ReduceSum function */
_ReduceSum(sGPU, tGPU, 1);
......
source/tensor/test/TSpread.cpp
......@@ -90,7 +90,7 @@ bool TestSpread1()
XTensor * modify = NewTensor(dataOrder, dataDimSize);
/* Initialize variables */
_SetDataFixedFloat(s, 0.0F);
_SetDataFixed(s, 0.0F);
modify->SetData(data, dataUnitNum);
/* call _Spread function */
......@@ -108,7 +108,7 @@ bool TestSpread1()
XTensor * modifyGPU = NewTensor(dataOrder, dataDimSize, X_FLOAT, 1.0F, 0);
/* Initialize variables */
_SetDataFixedFloat(sGPU, 0.0F);
_SetDataFixed(sGPU, 0.0F);
modifyGPU->SetData(data, dataUnitNum);
/* call _Spread function */
......
source/tensor/test/TSumDim.cpp
......@@ -295,8 +295,8 @@ bool TestSumDim3()
/* initialize variables */
a->SetZeroAll();
cMe->SetZeroAll();
_SetDataFixedFloat(b, 1.0F);
_SetDataFixedFloat(answer, 1.0F);
_SetDataFixed(b, 1.0F);
_SetDataFixed(answer, 1.0F);
/* call SumDim function */
_SumDim(a, b, c, 1);
......@@ -322,7 +322,7 @@ bool TestSumDim3()
/* Initialize variables */
aGPU->SetZeroAll();
cMe->SetZeroAll();
_SetDataFixedFloat(bGPU, 1.0F);
_SetDataFixed(bGPU, 1.0F);
/* call sum function */
_SumDim(aGPU, bGPU, cGPU, 1);
......@@ -404,8 +404,8 @@ bool TestSumDim4()
/* initialize variables */
a->SetZeroAll();
cMe->SetZeroAll();
_SetDataFixedFloat(b, 1.0F);
_SetDataFixedFloat(answer, 1.0F);
_SetDataFixed(b, 1.0F);
_SetDataFixed(answer, 1.0F);
/* call SumDim function */
_SumDim(a, b, c, 1);
......@@ -431,7 +431,7 @@ bool TestSumDim4()
/* Initialize variables */
aGPU->SetZeroAll();
cMe->SetZeroAll();
_SetDataFixedFloat(bGPU, 1.0F);
_SetDataFixed(bGPU, 1.0F);
/* call sum function */
_SumDim(aGPU, bGPU, cGPU, 1);
......
source/tensor/test/Test.cpp
......@@ -30,7 +30,7 @@ bool Test()
XPRINT(0, stdout, "Testing the XTensor utilites ... \n\n");
//wrong = !TestAbsolute() || wrong;
wrong = !TestClip() || wrong;
//wrong = !TestClip() || wrong;
//wrong = !TestCompare() || wrong;
//wrong = !TestConcatenate() || wrong;
//wrong = !TestConcatenateSolely() || wrong;
......@@ -38,8 +38,8 @@ bool Test()
//wrong = !TestConvertDataType() || wrong;
//wrong = !TestCopyIndexed() || wrong;
//wrong = !TestCopyValues() || wrong;
wrong = !TestDiv() || wrong;
wrong = !TestDivDim() || wrong;
//wrong = !TestDiv() || wrong;
//wrong = !TestDivDim() || wrong;
//wrong = !TestExp() || wrong;
//wrong = !TestGather() || wrong;
//wrong = !TestLog() || wrong;
......@@ -49,7 +49,7 @@ bool Test()
//wrong = !TestMatrixMulBatched() || wrong;
//wrong = !TestMerge() || wrong;
//wrong = !TestMultiply() || wrong;
wrong = !TestMultiplyDim() || wrong;
//wrong = !TestMultiplyDim() || wrong;
//wrong = !TestNegate() || wrong;
//wrong = !TestNormalize() || wrong;
//wrong = !TestPower() || wrong;
......@@ -60,17 +60,17 @@ bool Test()
//wrong = !TestReduceSumSquared() || wrong;
//wrong = !TestReduceVariance() || wrong;
//wrong = !TestRound() || wrong;
wrong = !TestScaleAndShift() || wrong;
//wrong = !TestScaleAndShift() || wrong;
//wrong = !TestSelect() || wrong;
//wrong = !TestSetAscendingOrder() || wrong;
//wrong = !TestSetData() || wrong;
wrong = !TestSetData() || wrong;
//wrong = !TestSign() || wrong;
//wrong = !TestSin() || wrong;
//wrong = !TestSort() || wrong;
//wrong = !TestSplit() || wrong;
//wrong = !TestSpread() || wrong;
//wrong = !TestSub() || wrong;
wrong = !TestSum() || wrong;
//wrong = !TestSum() || wrong;
//wrong = !TestSumByColumnTV() || wrong;
//wrong = !TestSumByColumnVT() || wrong;
//wrong = !TestSumDim() || wrong;
......
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