upsample ok, route have problems

include/NetworkRT.h

@@ -45,6 +45,7 @@ public:
     nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input, Region *l);
     nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input, Shortcut *l);
     nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input, Yolo *l);
+    nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input, Upsample *l);
 
     bool serialize(const char *filename);
     bool deserialize(const char *filename);

src/NetworkRT.cpp

@@ -16,6 +16,7 @@ using namespace nvinfer1;
 #include "pluginsRT/RegionRT.cpp"
 #include "pluginsRT/ShortcutRT.cpp"
 #include "pluginsRT/YoloRT.cpp"
+#include "pluginsRT/UpsampleRT.cpp"
 #include "pluginsRT/Int8Calibrator.cpp"
 
 // Logger for info/warning/errors
@@ -173,6 +174,8 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Layer *l) {
         return convert_layer(input, (Shortcut*) l);
     if(type == LAYER_YOLO)
         return convert_layer(input, (Yolo*) l);
+    if(type == LAYER_UPSAMPLE)
+        return convert_layer(input, (Upsample*) l);
 
     FatalError("Layer not implemented in tensorRT");
     return NULL;
@@ -350,6 +353,15 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Yolo *l) {
     return lRT;
 }
 
+ILayer* NetworkRT::convert_layer(ITensor *input, Upsample *l) {
+    //std::cout<<"convert Upsample\n";
+
+    //std::cout<<"New plugin UPSAMPLE\n";
+    IPlugin *plugin = new UpsampleRT(l->stride);
+    IPluginLayer *lRT = networkRT->addPlugin(&input, 1, *plugin);
+    checkNULL(lRT);
+    return lRT;
+}
 
 bool NetworkRT::serialize(const char *filename) {
 
@@ -418,6 +430,14 @@ public:
             return r;
         } 
 
+        if(name.find("Upsample") == 0) {
+            UpsampleRT *r = new UpsampleRT(readBUF<int>(buf)); //stride
+        	r->c = readBUF<int>(buf);
+		    r->h = readBUF<int>(buf);
+		    r->w = readBUF<int>(buf);
+            return r;
+        } 
+
         FatalError("Cant deserialize Plugin");
         return NULL;
     }

src/pluginsRT/RegionRT.cpp

@@ -69,7 +69,7 @@ public:
 
 
 	virtual size_t getSerializationSize() override {
-		return 6*sizeof(int) + 1*sizeof(float);
+		return 6*sizeof(int);
 	}
 
 	virtual void serialize(void* buffer) override {

src/pluginsRT/UpsampleRT.cpp

@@ -0,0 +1,65 @@
+#include<cassert>
+#include "kernels.h"
+
+class UpsampleRT : public IPlugin {
+
+public:
+	UpsampleRT(int stride) {
+		this->stride = stride;
+	}
+
+	~UpsampleRT(){
+
+	}
+
+	int getNbOutputs() const override {
+		return 1;
+	}
+
+	Dims getOutputDimensions(int index, const Dims* inputs, int nbInputDims) override {
+		return DimsCHW(inputs[0].d[0], inputs[0].d[1]*stride, inputs[0].d[2]*stride);
+	}
+
+	void configure(const Dims* inputDims, int nbInputs, const Dims* outputDims, int nbOutputs, int maxBatchSize) override {
+		c = inputDims[0].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 *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);
+		return 0;
+	}
+
+
+	virtual size_t getSerializationSize() override {
+		return 4*sizeof(int);
+	}
+
+	virtual void serialize(void* buffer) override {
+		char *buf = reinterpret_cast<char*>(buffer);
+		tk::dnn::writeBUF(buf, stride);
+		tk::dnn::writeBUF(buf, c);
+		tk::dnn::writeBUF(buf, h);
+		tk::dnn::writeBUF(buf, w);
+	}
+
+	int c, h, w, stride;
+};

src/pluginsRT/YoloRT.cpp

@@ -57,12 +57,13 @@ public:
 			}
 		}
 
+		std::cout<<"YOLO END\n";
 		return 0;
 	}
 
 
 	virtual size_t getSerializationSize() override {
-		return 5*sizeof(int) + 1*sizeof(float);
+		return 5*sizeof(int);
 	}
 
 	virtual void serialize(void* buffer) override {

tests/yolo3_berkeley/yolo3_berkeley.cpp

@@ -77,7 +77,7 @@ const char *c102_bin  = "../tests/yolo3_berkeley/layers/c102.bin";
 const char *c103_bin  = "../tests/yolo3_berkeley/layers/c103.bin";
 const char *c104_bin  = "../tests/yolo3_berkeley/layers/c104.bin";
 const char *c105_bin  = "../tests/yolo3_berkeley/layers/c105.bin";
-const char *output_bin = "../tests/yolo3_berkeley/debug/layer82_out.bin";
+const char *output_bin = "../tests/yolo3_berkeley/debug/layer93_out.bin";
 
 int main() {
 
@@ -231,19 +231,21 @@ int main() {
     tk::dnn::Activation a78  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c79  (&net, 512, 1, 1, 1, 1, 0, 0, c79_bin, true);
     tk::dnn::Activation a79  (&net, tk::dnn::ACTIVATION_LEAKY);
+/*
     tk::dnn::Conv2d     c80  (&net,1024, 3, 3, 1, 1, 1, 1, c80_bin, true);
     tk::dnn::Activation a80  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c81  (&net,  45, 1, 1, 1, 1, 0, 0, c81_bin, false);
-    tk::dnn::Yolo       g82  (&net,  10, 3);
+    tk::dnn::Yolo       y82  (&net,  10, 3);
-/*
+
     tk::dnn::Layer *m83_layers[1] = { &a79 };
     tk::dnn::Route      m83  (&net, m83_layers, 1);
+*/
     tk::dnn::Conv2d     c84  (&net, 256, 1, 1, 1, 1, 0, 0, c84_bin, true);
     tk::dnn::Activation a84  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Upsample   u85  (&net, 2);
-    
+
-    tk::dnn::Layer *m86_layers[2] = { &u85, &s61 };
+//    tk::dnn::Layer *m86_layers[2] = { &u85, &s61 };
-    tk::dnn::Route      m86  (&net, m86_layers, 2);
+//    tk::dnn::Route      m86  (&net, m86_layers, 2);
     tk::dnn::Conv2d     c87  (&net, 256, 1, 1, 1, 1, 0, 0, c87_bin, true);
     tk::dnn::Activation a87  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c88  (&net, 512, 3, 3, 1, 1, 1, 1, c88_bin, true);
@@ -254,19 +256,21 @@ int main() {
     tk::dnn::Activation a90  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c91  (&net, 256, 1, 1, 1, 1, 0, 0, c91_bin, true);
     tk::dnn::Activation a91  (&net, tk::dnn::ACTIVATION_LEAKY);
+/*
     tk::dnn::Conv2d     c92  (&net, 512, 3, 3, 1, 1, 1, 1, c92_bin, true);
     tk::dnn::Activation a92  (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c93  (&net,  45, 1, 1, 1, 1, 0, 0, c93_bin, false);
-    tk::dnn::Yolo       g94  (&net,  10, 3);
+    tk::dnn::Yolo       y94  (&net,  10, 3);
 
     tk::dnn::Layer *m95_layers[1] = { &a91 };
     tk::dnn::Route      m95  (&net, m95_layers, 1);
+*/
     tk::dnn::Conv2d     c96  (&net, 128, 1, 1, 1, 1, 0, 0, c96_bin, true);
     tk::dnn::Activation a96  (&net, tk::dnn::ACTIVATION_LEAKY);
 
     tk::dnn::Upsample   u97  (&net, 2);
-    tk::dnn::Layer *m98_layers[2] = { &u97, &s36 };
+//    tk::dnn::Layer *m98_layers[2] = { &u97, &s36 };
-    tk::dnn::Route      m98  (&net, m98_layers, 2);
+//    tk::dnn::Route      m98  (&net, m98_layers, 2);
 
     tk::dnn::Conv2d     c99  (&net, 128, 1, 1, 1, 1, 0, 0, c99_bin, true);
     tk::dnn::Activation a99  (&net, tk::dnn::ACTIVATION_LEAKY);
@@ -282,8 +286,13 @@ int main() {
     tk::dnn::Conv2d     c104 (&net, 256, 3, 3, 1, 1, 1, 1, c104_bin, true);
     tk::dnn::Activation a104 (&net, tk::dnn::ACTIVATION_LEAKY);
     tk::dnn::Conv2d     c105 (&net,  45, 1, 1, 1, 1, 0, 0, c105_bin, false);
-    tk::dnn::Yolo       g106 (&net,  10, 3);
+    tk::dnn::Yolo       y106 (&net,  10, 3);
-*/
+
+    // merge all yolos
+//    tk::dnn::Layer *m107_layers[2] = { &y82, &y94, &y106 };
+//    tk::dnn::Route      m107 (&net, m107_layers, 3);
+
+
     // Load input
     dnnType *data;
     dnnType *input_h;
@@ -318,9 +327,9 @@ int main() {
     printCenteredTitle(" CHECK RESULTS ", '=', 30);
     dnnType *out, *out_h;
     int out_dim = net.getOutputDim().tot();
-    readBinaryFile(output_bin, out_dim, &out_h, &out);
+    //readBinaryFile(output_bin, out_dim, &out_h, &out);
-    std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
+    //std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
-    std::cout<<"TRT   vs correct"; checkResult(out_dim, out_data2, out);
+    //std::cout<<"TRT   vs correct"; checkResult(out_dim, out_data2, out);
     std::cout<<"CUDNN vs TRT    "; checkResult(out_dim, out_data, out_data2);
     return 0;
 }