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NiuTrans.Tensor
Commit ece0dc78 by 张裕浩
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测试softmax优化方法

parent dd6646ed
正在显示 包含 138 行增加 和 12 行删除
source/network/Main.cpp
...@@ -24,6 +24,7 @@ ...@@ -24,6 +24,7 @@
#include "../tensor/function/FHeader.h" #include "../tensor/function/FHeader.h"
#include "../tensor/core/CHeader.h" #include "../tensor/core/CHeader.h"
#include "../sample/fnnlm/FNNLM.h" #include "../sample/fnnlm/FNNLM.h"
#include "../tensor/test/Test.h"
//#define CRTDBG_MAP_ALLOC //#define CRTDBG_MAP_ALLOC
//#include <stdlib.h> //#include <stdlib.h>
...@@ -36,9 +37,9 @@ using namespace samplefnnlm; ...@@ -36,9 +37,9 @@ using namespace samplefnnlm;
int main( int argc, const char ** argv ) int main( int argc, const char ** argv )
{ {
if(argc > 1 && !strcmp(argv[1], "-test")) //if(argc > 1 && !strcmp(argv[1], "-test"))
1;//Test(); Test();
else if(argc > 1 && !strcmp(argv[1], "-fnnlm")) /*else if(argc > 1 && !strcmp(argv[1], "-fnnlm"))
FNNLMMain(argc - 1, argv + 1); FNNLMMain(argc - 1, argv + 1);
else{ else{
fprintf(stderr, "Thanks for using NiuTrans.Network! This is a library for building\n"); fprintf(stderr, "Thanks for using NiuTrans.Network! This is a library for building\n");
...@@ -76,7 +77,7 @@ int main( int argc, const char ** argv ) ...@@ -76,7 +77,7 @@ int main( int argc, const char ** argv )
net.Dump(stderr); net.Dump(stderr);
//_CrtDumpMemoryLeaks(); //_CrtDumpMemoryLeaks();*/
return 0; return 0;
} }
source/tensor/function/Softmax.cu
...@@ -155,6 +155,46 @@ void KernelSoftmaxComputeTensor(__half * x, __half * max, __half * sum, __half * ...@@ -155,6 +155,46 @@ void KernelSoftmaxComputeTensor(__half * x, __half * max, __half * sum, __half *
} }
} }
__device__ __forceinline__ float broadCast(float input)
{
float output;
asm(
"{"
"shfl.idx.b32 %0,%1,0x0,0x1f;"
"}"
:"=f"(output) : "f"(input)
);
return output;
}
__global__
void KernelSoftmaxComputeTensorUseBroadcast(DTYPE * input, DTYPE * max, DTYPE * sum, DTYPE * output, int stride, int strideNum, int blockNum)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
int j = blockDim.y * blockIdx.y + threadIdx.y;
int i2 = j % stride;
int blockSize = stride * strideNum;
if (j < stride * blockNum)
{
DTYPE sumData, maxData;
if (i % 32 == 0)
{
sumData = sum[j];
maxData = max[j];
}
//sumData = __shfl_sync(0xffffffff,sumData, 0);
//maxData = __shfl_sync(0xffffffff,maxData, 0);
sumData = broadCast(sumData);
maxData = broadCast(maxData);
if (i < strideNum)
{
int offset = int(j / stride) * blockSize + i * stride + i2;
output[offset] = exp(input[offset] - maxData) / sumData;
}
}
}
/* /*
softmax y = e^x / \sum_{i} e^{x_i} (Cuda version) softmax y = e^x / \sum_{i} e^{x_i} (Cuda version)
>> x - x vector >> x - x vector
...@@ -183,15 +223,24 @@ void _CudaSoftmaxSumMax(const XTensor * x, XTensor * y, int leadDim, XTensor * s ...@@ -183,15 +223,24 @@ void _CudaSoftmaxSumMax(const XTensor * x, XTensor * y, int leadDim, XTensor * s
int cudaGridSize[3]; int cudaGridSize[3];
int cudaBlockSize[3]; int cudaBlockSize[3];
GDevs.GetCudaThread2D(x->devID, stride * blockNum, dimensionSize, MAX_INT, cudaGridSize, cudaBlockSize); //GDevs.GetCudaThread2D(x->devID, stride * blockNum, dimensionSize, MAX_INT, cudaGridSize, cudaBlockSize);
GDevs.GetCudaThread2D(x->devID, dimensionSize, stride * blockNum, MAX_INT, cudaGridSize, cudaBlockSize);
if (cudaBlockSize[0] % 32 != 0)
cudaBlockSize[0] += (32 - cudaBlockSize[0] % 32);
/**/
int devIDBackup; int devIDBackup;
ProtectCudaDev(x->devID, devIDBackup); ProtectCudaDev(x->devID, devIDBackup);
if(x->dataType == DEFAULT_DTYPE && y->dataType == DEFAULT_DTYPE){ if(x->dataType == DEFAULT_DTYPE && y->dataType == DEFAULT_DTYPE){
KernelSoftmaxComputeTensor<<<dim3(cudaGridSize[0], cudaGridSize[1]), dim3(cudaBlockSize[0], cudaBlockSize[1])>>> printf("run here\n");
/*KernelSoftmaxComputeTensor<<<dim3(cudaGridSize[0], cudaGridSize[1]), dim3(cudaBlockSize[0], cudaBlockSize[1])>>>
((DTYPE*)x->data, (DTYPE*)max->data, (DTYPE*)sum->data, (DTYPE*)y->data,
stride, dimensionSize, stride * dimensionSize, blockNum, stride * blockNum);*/
KernelSoftmaxComputeTensorUseBroadcast << <dim3(cudaGridSize[0], cudaGridSize[1]), dim3(cudaBlockSize[0], cudaBlockSize[1]) >> >
((DTYPE*)x->data, (DTYPE*)max->data, (DTYPE*)sum->data, (DTYPE*)y->data, ((DTYPE*)x->data, (DTYPE*)max->data, (DTYPE*)sum->data, (DTYPE*)y->data,
stride, dimensionSize, stride * dimensionSize, blockNum, stride * blockNum); stride, dimensionSize, blockNum);
//printf("%d %d %d %d %d %d\n", stride, dimensionSize, stride * dimensionSize, blockNum, stride * blockNum);
} }
else if(x->dataType == X_FLOAT16 && y->dataType == X_FLOAT16){ else if(x->dataType == X_FLOAT16 && y->dataType == X_FLOAT16){
KernelSoftmaxComputeTensor<<<dim3(cudaGridSize[0], cudaGridSize[1]), dim3(cudaBlockSize[0], cudaBlockSize[1])>>> KernelSoftmaxComputeTensor<<<dim3(cudaGridSize[0], cudaGridSize[1]), dim3(cudaBlockSize[0], cudaBlockSize[1])>>>
......
source/tensor/test/TSoftmax.cpp
...@@ -68,7 +68,6 @@ bool TestSoftmax1() ...@@ -68,7 +68,6 @@ bool TestSoftmax1()
#ifdef USE_CUDA #ifdef USE_CUDA
/* GPU test */ /* GPU test */
bool gpuTest = true; bool gpuTest = true;
/* create tensors */ /* create tensors */
XTensor * xGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0); XTensor * xGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0);
XTensor * yGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0); XTensor * yGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0);
...@@ -81,7 +80,6 @@ bool TestSoftmax1() ...@@ -81,7 +80,6 @@ bool TestSoftmax1()
/* call Softmax function */ /* call Softmax function */
_Softmax(xGPU, yGPU, 1); _Softmax(xGPU, yGPU, 1);
yUserGPU = Softmax(*xGPU, 1); yUserGPU = Softmax(*xGPU, 1);
/* check result */ /* check result */
gpuTest = yGPU->CheckData(answer, unitNum, 1e-4F) && yUserGPU.CheckData(answer, unitNum, 1e-4F); gpuTest = yGPU->CheckData(answer, unitNum, 1e-4F) && yUserGPU.CheckData(answer, unitNum, 1e-4F);
...@@ -208,6 +206,77 @@ bool TestSoftmax2() ...@@ -208,6 +206,77 @@ bool TestSoftmax2()
} }
/* other cases */ /* other cases */
bool TestSoftmax3Gpu()
{
#ifdef USE_CUDA
/* GPU test */
bool gpuTest = true;
int order = 2;
int * dimSize = new int[order];
dimSize[0] = 32;
dimSize[1] = 1000;
int unitNum = 1;
for (int i = 0; i < order; i++)
unitNum *= dimSize[i];
/* create tensors */
XTensor * xGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0);
XTensor * yGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0);
/* initialize variables */
FILE *dataFile;
char dataString[32];
const int dataSize = 32 * 1000;
DTYPE xData[dataSize];
if ((dataFile = fopen("D:\\Work\\TensorFlowLearn\\testdata.in", "r")) == NULL)
{
printf("file open fail");
exit(1);
}
for (int i = 0; i < dataSize; ++i)
{
if (fscanf(dataFile, "%s", dataString) != EOF)
{
//printf("%s", dataString);
xData[i] = atof(dataString);
//srcTensorData[i] = i;
}
else
{
printf("read wrong");
break;
}
}
xGPU->SetData(xData, unitNum);
yGPU->SetZeroAll();
/* call Softmax function */
_Softmax(xGPU, yGPU, 0);
/* check result */
//gpuTest = yGPU->CheckData(yAnswer, unitNum, 1e-4F)
DTYPE check = 0;
DTYPE TensorData[dataSize];
cudaMemcpy(TensorData, yGPU->data, sizeof(DTYPE)* unitNum, cudaMemcpyDeviceToHost);
//float check = 0;
for (int i = 0; i < 32; ++i)
{
check += TensorData[i];
printf("%f ", TensorData[i]);
}
printf("\n%f \n", check);
/* destroy variables */
delete xGPU;
delete yGPU;
delete[] dimSize;
return gpuTest;
#endif
}
/* /*
TODO!! TODO!!
*/ */
...@@ -239,6 +308,13 @@ bool TestSoftmax() ...@@ -239,6 +308,13 @@ bool TestSoftmax()
XPRINT(0, stdout, ">> case 2 passed!\n"); XPRINT(0, stdout, ">> case 2 passed!\n");
/* other cases test */ /* other cases test */
caseFlag = TestSoftmax3Gpu();
if (!caseFlag) {
returnFlag = false;
XPRINT(0, stdout, ">> case 3 failed!\n");
}
else
XPRINT(0, stdout, ">> case 3 passed!\n");
/* /*
TODO!! TODO!!
*/ */
......
source/tensor/test/Test.cpp
...@@ -29,7 +29,7 @@ bool Test() ...@@ -29,7 +29,7 @@ bool Test()
bool wrong = false; bool wrong = false;
XPRINT(0, stdout, "Testing the XTensor utilites ... \n\n"); XPRINT(0, stdout, "Testing the XTensor utilites ... \n\n");
wrong = !TestAbsolute() || wrong; /*wrong = !TestAbsolute() || wrong;
wrong = !TestConcatenate() || wrong; wrong = !TestConcatenate() || wrong;
wrong = !TestConcatenateSolely() || wrong; wrong = !TestConcatenateSolely() || wrong;
wrong = !TestConvertDataType() || wrong; wrong = !TestConvertDataType() || wrong;
...@@ -70,7 +70,7 @@ bool Test() ...@@ -70,7 +70,7 @@ bool Test()
wrong = !TestLogSoftmax() || wrong; wrong = !TestLogSoftmax() || wrong;
wrong = !TestLoss() || wrong; wrong = !TestLoss() || wrong;
wrong = !TestRectify() || wrong; wrong = !TestRectify() || wrong;
wrong = !TestSigmoid() || wrong; wrong = !TestSigmoid() || wrong;*/
wrong = !TestSoftmax() || wrong; wrong = !TestSoftmax() || wrong;
/* other test */ /* other test */
......
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