completed padding migrations from github

src/NetworkRT.cpp

@@ -275,6 +275,8 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Layer *l) {
         return convert_layer(input, (Upsample*) l);
     if(type == LAYER_DEFORMCONV2D)
         return convert_layer(input, (DeformConv2d*) l);
+    if(type == LAYER_PADDING)
+        return convert_layer(input, (Padding*) l);
 
     std::cout<<l->getLayerName()<<"\n";
     FatalError("Layer not implemented in tensorRT");
@@ -453,6 +455,15 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Pooling *l) {
     }
 }
 
+ILayer* NetworkRT::convert_layer(ITensor *input,Padding *l){
+    auto *lRT = networkRT->addSlice(*input,Dims3{0,0,0},Dims3{l->output_dim.c,l->output_dim.h,l->output_dim.w},Dims3{0,0,0});
+    if(l->padding_mode == PADDING_MODE_REFLECTION){
+        lRT->setMode(SliceMode::kREFLECT);
+    }
+    checkNULL(lRT);
+    return lRT;
+}
+
 ILayer* NetworkRT::convert_layer(ITensor *input, Activation *l) {
     //std::cout<<"convert Activation\n";
 

src/Padding.cpp

@@ -0,0 +1,35 @@
+//
+// Created by perseusdg on 03/01/22.
+//
+
+#include <iostream>
+#include "Layer.h"
+#include "kernels.h"
+
+namespace tk{ namespace dnn {
+    Padding::Padding(Network *net, int32_t pad_h, int32_t pad_w, tkdnnPaddingMode_t padding_mode) : Layer(net) {
+        this->paddingH = pad_h;
+        this->paddingW = pad_w;
+        this->padding_mode = padding_mode;
+        output_dim.c = input_dim.c;
+        output_dim.n = input_dim.n;
+        output_dim.h = input_dim.h + 2 * (this->paddingH);
+        output_dim.w = input_dim.w + 2 * (this->paddingW);
+        checkCuda(cudaMalloc(&dstData,output_dim.tot()*sizeof(dnnType)));
+    }
+
+    Padding::~Padding() {
+        checkCuda(cudaFree(dstData));
+    }
+    dnnType* Padding::infer(dataDim_t &dim, float *srcData) {
+        fill(dstData,output_dim.tot(),0.0);
+        if(padding_mode == tkdnnPaddingMode_t::PADDING_MODE_REFLECTION)
+        {
+            reflection_pad2d_out_forward(paddingH, paddingW, srcData, dstData, input_dim.h, input_dim.w, input_dim.c,
+                                         input_dim.n);
+        }
+        dim = output_dim;
+        return dstData;
+    }
+
+}}

src/kernels/padding.cu

@@ -44,11 +44,11 @@ int32_t ceilDiv(int32_t a,int32_t b){
 }
 
 
-void reflection_pad2d_out_forward(int32_t padding[4],float *srcData,float *dstData,int32_t input_h,int32_t input_w,int32_t plane_dim,int32_t n_batch,cudaStream_t cudaStream){
-    int32_t pad_l = padding[0];
-    int32_t pad_r = padding[1];
-    int32_t pad_t = padding[2];
-    int32_t pad_b = padding[3];
+void reflection_pad2d_out_forward(int32_t pad_h,int32_t pad_w,float *srcData,float *dstData,int32_t input_h,int32_t input_w,int32_t plane_dim,int32_t n_batch,cudaStream_t cudaStream){
+    int32_t pad_l = pad_w;
+    int32_t pad_r = pad_w;
+    int32_t pad_t = pad_h;
+    int32_t pad_b = pad_w;
     int32_t output_h = input_h + pad_t + pad_b;
     int32_t output_w = input_w + pad_l + pad_r;
     int32_t size_y = plane_dim;