mmr/tkDNN
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Merge remote-tracking branch 'origin/master' into cnet

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This commit is contained in:
Davide Sapienza
2021-07-22 17:03:23 +02:00
parent 2bb70859da f4e71a5a28
commit 0292e21c33
59 changed files with 7640 additions and 209 deletions
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include/tkDNN/pluginsRT/ActivationLeakyRT.h
+5 -5
View File
@@ -4,9 +4,8 @@
class ActivationLeakyRT : public IPlugin {
public:
ActivationLeakyRT() {
ActivationLeakyRT(float s) {
slope = s;
}
~ActivationLeakyRT(){
@@ -42,13 +41,13 @@ public:
virtual int enqueue(int batchSize, const void*const * inputs, void** outputs, void* workspace, cudaStream_t stream) override {
activationLEAKYForward((dnnType*)reinterpret_cast<const dnnType*>(inputs[0]),
reinterpret_cast<dnnType*>(outputs[0]), batchSize*size, stream);
reinterpret_cast<dnnType*>(outputs[0]), batchSize*size, slope, stream);
return 0;
}
virtual size_t getSerializationSize() override {
return 1*sizeof(int);
return 1*sizeof(int) + 1*sizeof(float);
}
virtual void serialize(void* buffer) override {
@@ -58,4 +57,5 @@ public:
}
int size;
float slope;
};
include/tkDNN/pluginsRT/ShortcutRT.h
+6 -4
View File
@@ -4,10 +4,11 @@
class ShortcutRT : public IPlugin {
public:
ShortcutRT(tk::dnn::dataDim_t bdim) {
ShortcutRT(tk::dnn::dataDim_t bdim, bool mul) {
this->bc = bdim.c;
this->bh = bdim.h;
this->bw = bdim.w;
this->mul = mul;
}
~ShortcutRT(){
@@ -47,15 +48,14 @@ public:
dnnType *dstData = reinterpret_cast<dnnType*>(outputs[0]);
checkCuda( cudaMemcpyAsync(dstData, srcData, batchSize*c*h*w*sizeof(dnnType), cudaMemcpyDeviceToDevice, stream));
for(int b=0; b < batchSize; ++b)
shortcutForward(srcDataBack + b*bc*bh*bw, dstData + b*c*h*w, 1, c, h, w, 1, 1, bc, bh, bw, 1, stream);
shortcutForward(srcDataBack, dstData, batchSize, c, h, w, 1, batchSize, bc, bh, bw, 1, mul, stream);
return 0;
}
virtual size_t getSerializationSize() override {
return 6*sizeof(int);
return 6*sizeof(int) + sizeof(bool);
}
virtual void serialize(void* buffer) override {
@@ -63,6 +63,7 @@ public:
tk::dnn::writeBUF(buf, bc);
tk::dnn::writeBUF(buf, bh);
tk::dnn::writeBUF(buf, bw);
tk::dnn::writeBUF(buf, mul);
tk::dnn::writeBUF(buf, c);
tk::dnn::writeBUF(buf, h);
tk::dnn::writeBUF(buf, w);
@@ -72,4 +73,5 @@ public:
int c, h, w;
int bc, bh, bw;
bool mul;
};
include/tkDNN/pluginsRT/YoloRT.h
+12 -12
View File
@@ -93,23 +93,23 @@ public:
virtual void serialize(void* buffer) override {
char *buf = reinterpret_cast<char*>(buffer),*a=buf;
tk::dnn::writeBUF(buf, classes); std::cout << "Classes :" << classes << std::endl;
tk::dnn::writeBUF(buf, num); std::cout << "Num : " << num << std::endl;
tk::dnn::writeBUF(buf, n_masks); std::cout << "N_Masks" << n_masks << std::endl;
tk::dnn::writeBUF(buf, scaleXY); std::cout << "ScaleXY :" << scaleXY << std::endl;
tk::dnn::writeBUF(buf, nms_thresh); std::cout << "nms_thresh :" << nms_thresh << std::endl;
tk::dnn::writeBUF(buf, nms_kind); std::cout << "nms_kind : " << nms_kind << std::endl;
tk::dnn::writeBUF(buf, new_coords); std::cout << "new_coords : " << new_coords << std::endl;
tk::dnn::writeBUF(buf, c); std::cout << "C : " << c << std::endl;
tk::dnn::writeBUF(buf, h); std::cout << "H : " << h << std::endl;
tk::dnn::writeBUF(buf, w); std::cout << "C : " << c << std::endl;
tk::dnn::writeBUF(buf, classes); //std::cout << "Classes :" << classes << std::endl;
tk::dnn::writeBUF(buf, num); //std::cout << "Num : " << num << std::endl;
tk::dnn::writeBUF(buf, n_masks); //std::cout << "N_Masks" << n_masks << std::endl;
tk::dnn::writeBUF(buf, scaleXY); //std::cout << "ScaleXY :" << scaleXY << std::endl;
tk::dnn::writeBUF(buf, nms_thresh); //std::cout << "nms_thresh :" << nms_thresh << std::endl;
tk::dnn::writeBUF(buf, nms_kind); //std::cout << "nms_kind : " << nms_kind << std::endl;
tk::dnn::writeBUF(buf, new_coords); //std::cout << "new_coords : " << new_coords << std::endl;
tk::dnn::writeBUF(buf, c); //std::cout << "C : " << c << std::endl;
tk::dnn::writeBUF(buf, h); //std::cout << "H : " << h << std::endl;
tk::dnn::writeBUF(buf, w); //std::cout << "C : " << c << std::endl;
for (int i = 0; i < n_masks; i++)
{
tk::dnn::writeBUF(buf, mask[i]); std::cout << "mask[i] : " << mask[i] << std::endl;
tk::dnn::writeBUF(buf, mask[i]); //std::cout << "mask[i] : " << mask[i] << std::endl;
}
for (int i = 0; i < n_masks * 2 * num; i++)
{
tk::dnn::writeBUF(buf, bias[i]); std::cout << "bias[i] : " << bias[i] << std::endl;
tk::dnn::writeBUF(buf, bias[i]); //std::cout << "bias[i] : " << bias[i] << std::endl;
}
// save classes names