yolo TensorRT almost DONE

src/NetworkRT.cpp

@@ -1,10 +1,12 @@
 #include <iostream>
+#include <map>
 #include "NvInfer.h"
 
 #include "NetworkRT.h"
 
 using namespace nvinfer1;
 #include "pluginsRT/ActivationLeakyRT.cpp"
+#include "pluginsRT/ReorgRT.cpp"
 
 // Logger for info/warning/errors
 class Logger : public ILogger			
@@ -17,6 +19,8 @@ class Logger : public ILogger
 
 namespace tkDNN {
 
+std::map<Layer*, nvinfer1::ITensor*>tensors; 
+
 NetworkRT::NetworkRT(Network *net) {
 
     builderRT = createInferBuilder(loggerRT);
@@ -33,6 +37,7 @@ NetworkRT::NetworkRT(Network *net) {
     for(int i=0; i<net->num_layers; i++) {
         Layer *l = net->layers[i];
         input = convert_layer(input, l);
+        tensors[l] = input;
     }
     if(input == NULL)
         FatalError("conversion failed");
@@ -102,6 +107,10 @@ ITensor* NetworkRT::convert_layer(ITensor *input, Layer *l) {
         return convert_layer(input, (Activation*) l);
     if(type == LAYER_SOFTMAX)
         return convert_layer(input, (Softmax*) l);
+    if(type == LAYER_ROUTE)
+        return convert_layer(input, (Route*) l);
+    if(type == LAYER_REORG)
+        return convert_layer(input, (Reorg*) l);
 
     FatalError("Layer not implemented in tensorRT");
     return NULL;
@@ -206,4 +215,26 @@ ITensor* NetworkRT::convert_layer(ITensor *input, Softmax *l) {
     return lRT->getOutput(0);
 }
 
+ITensor* NetworkRT::convert_layer(ITensor *input, Route *l) {
+    std::cout<<"convert route\n";
+
+    ITensor *tens[256];
+    for(int i=0; i<l->layers_n; i++)
+        tens[i] = tensors[l->layers[i]];
+    IConcatenationLayer *lRT = networkRT->addConcatenation(tens, l->layers_n);
+    checkNULL(lRT);
+
+    return lRT->getOutput(0);
+}
+
+ITensor* NetworkRT::convert_layer(ITensor *input, Reorg *l) {
+    std::cout<<"convert Reorg\n";
+
+    std::cout<<"New plugin REORG\n";
+    IPlugin *plugin = new ReorgRT(l->stride);
+    IPluginLayer *lRT = networkRT->addPlugin(&input, 1, *plugin);
+    checkNULL(lRT);
+    return lRT->getOutput(0);
+}
+
 }

src/pluginsRT/ReorgRT.cpp

@@ -0,0 +1,58 @@
+#include<cassert>
+#include "kernels.h"
+
+class ReorgRT : public IPlugin {
+
+public:
+	ReorgRT(int stride) {
+		this->stride = stride;
+	}
+
+	~ReorgRT(){
+
+	}
+
+	int getNbOutputs() const override {
+		return 1;
+	}
+
+	Dims getOutputDimensions(int index, const Dims* inputs, int nbInputDims) override {
+		return DimsCHW{inputs[0].d[0]*stride*stride, 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 {
+
+		reorgForward((value_type*)reinterpret_cast<const value_type*>(inputs[0]), 
+					  reinterpret_cast<value_type*>(outputs[0]), 
+					  batchSize, c, h, w, stride);
+		return 0;
+	}
+
+
+	virtual size_t getSerializationSize() override {
+		return 0;
+	}
+
+	virtual void serialize(void* buffer) override {
+	}
+
+	int c, h, w, stride;
+};

src/utils.cpp

@@ -70,7 +70,7 @@ int checkResult(int size, value_type *data_d, value_type *correct_d, bool device
         if(fabs(data_h[i] - correct_h[i]) > 0.0001) {
             diffs += 1;
             if(diffs < 10)
-                printf("%f %f\n", data_h[i], correct_h[i]);
+                printf("%d: %f %f\n", i, data_h[i], correct_h[i]);
         }
     }