yolo3 ok

src/pluginsRT/RouteRT.cpp

@@ -0,0 +1,82 @@
+#include<cassert>
+#include "kernels.h"
+
+class RouteRT : public IPlugin {
+
+public:
+	RouteRT() {
+	}
+
+	~RouteRT(){
+
+	}
+
+	int getNbOutputs() const override {
+		return 1;
+	}
+
+	Dims getOutputDimensions(int index, const Dims* inputs, int nbInputDims) override {
+		int out_c = 0;
+		for(int i=0; i<nbInputDims; i++) out_c += inputs[i].d[0];
+		return DimsCHW{out_c, inputs[0].d[1], inputs[0].d[2]};
+	}
+
+	void configure(const Dims* inputDims, int nbInputs, const Dims* outputDims, int nbOutputs, int maxBatchSize) override {
+		in = nbInputs;
+		c = 0;
+		for(int i=0; i<nbInputs; i++) {
+			c_in[i] = inputDims[i].d[0]; 
+			c += inputDims[i].d[0];
+		}
+		h = inputDims[0].d[1];
+		w = inputDims[0].d[2];
+	}
+
+	int initialize() override {
+
+		return 0;
+	}
+
+	virtual void terminate() override {
+	}
+
+	virtual size_t getWorkspaceSize(int maxBatchSize) const override {
+		return 0;
+	}
+
+	virtual int enqueue(int batchSize, const void*const * inputs, void** outputs, void* workspace, cudaStream_t stream) override {
+
+		dnnType *dstData = reinterpret_cast<dnnType*>(outputs[0]);
+
+		int offset = 0;
+		for(int i=0; i<in; i++) {
+			dnnType *input = (dnnType*)reinterpret_cast<const dnnType*>(inputs[i]);
+			int in_dim = c_in[i]*h*w;
+			checkCuda( cudaMemcpyAsync(dstData + offset, input, in_dim*sizeof(dnnType), cudaMemcpyDeviceToDevice, stream) );
+			offset += in_dim;
+		}
+
+		return 0;
+	}
+
+
+	virtual size_t getSerializationSize() override {
+		return (4+MAX_INPUTS)*sizeof(int);
+	}
+
+	virtual void serialize(void* buffer) override {
+		char *buf = reinterpret_cast<char*>(buffer);
+		tk::dnn::writeBUF(buf, in);
+		for(int i=0; i<MAX_INPUTS; i++)
+			tk::dnn::writeBUF(buf, c_in[i]);
+
+		tk::dnn::writeBUF(buf, c);
+		tk::dnn::writeBUF(buf, h);
+		tk::dnn::writeBUF(buf, w);
+	}
+
+	static const int MAX_INPUTS = 4;
+	int in;
+	int c_in[MAX_INPUTS];
+	int c, h, w;
+};

src/pluginsRT/ShortcutRT.cpp

@@ -44,7 +44,7 @@ public:
 		dnnType *dstData = reinterpret_cast<dnnType*>(outputs[0]);
 
 		checkCuda( cudaMemcpyAsync(dstData, srcData, batchSize*c*h*w*sizeof(dnnType), cudaMemcpyDeviceToDevice, stream));
-		shortcutForward(srcDataBack, dstData, batchSize, c, h, w, 1, batchSize, c, h, w, 1);
+		shortcutForward(srcDataBack, dstData, batchSize, c, h, w, 1, batchSize, c, h, w, 1, stream);
 
 		return 0;
 	}

src/pluginsRT/UpsampleRT.cpp

@@ -43,8 +43,8 @@ public:
 		dnnType *srcData = (dnnType*)reinterpret_cast<const dnnType*>(inputs[0]);
 		dnnType *dstData = reinterpret_cast<dnnType*>(outputs[0]);
 	    
-		fill(dstData, batchSize*c*h*w, 0.0);
-    	upsampleForward(srcData, dstData, batchSize, c, h, w, stride, 1, 1);
+		fill(dstData, batchSize*c*h*w*stride*stride, 0.0, stream);
+    	upsampleForward(srcData, dstData, batchSize, c, h, w, stride, 1, 1, stream);
 		return 0;
 	}
 

src/pluginsRT/YoloRT.cpp

@@ -57,7 +57,7 @@ public:
 			}
 		}
 
-		std::cout<<"YOLO END\n";
+		//std::cout<<"YOLO END\n";
 		return 0;
 	}