completed padding migrations from github

include/tkDNN/Layer.h

@@ -31,7 +31,8 @@ enum layerType_t {
     LAYER_SHORTCUT,
     LAYER_UPSAMPLE,
     LAYER_REGION,
-    LAYER_YOLO
+    LAYER_YOLO,
+    LAYER_PADDING
 };
 
 #define TKDNN_BN_MIN_EPSILON 1e-5
@@ -87,6 +88,7 @@ public:
             case LAYER_UPSAMPLE:            return "Upsample";
             case LAYER_REGION:              return "Region";
             case LAYER_YOLO:                return "Yolo";
+            case LAYER_PADDING:             return "Padding";
             default:                        return "unknown";
         }
     }
@@ -520,9 +522,32 @@ protected:
     bool poolOn3d;
 };
 
+/**
+ * Padding Layers
+ * tkDNN supports reflection,constant and zero padding
+ */
+
+typedef enum {
+    PADDING_MODE_CONSTANT = 0,
+    PADDING_MODE_ZERO = 1,
+    PADDING_MODE_REFLECTION = 2
+} tkdnnPaddingMode_t;
+
+class Padding : public Layer {
+public:
+    Padding(Network *net,int32_t pad_h,int32_t pad_w,tkdnnPaddingMode_t padding_mode);
+    virtual ~Padding();
+    virtual layerType_t getLayerType(){return LAYER_PADDING ;};
+    virtual dnnType* infer(dataDim_t& dim,dnnType* srcData);
+    int32_t paddingH,paddingW;
+    tkdnnPaddingMode_t padding_mode;
+
+};
+
 /**
     Softmax layer
 */
+
 class Softmax : public Layer {
 
 public:

include/tkDNN/NetworkRT.h

@@ -95,6 +95,7 @@ public:
     nvinfer1::IPluginV2Layer* convert_layer(nvinfer1::ITensor *input, Yolo *l);
     nvinfer1::IResizeLayer* convert_layer(nvinfer1::ITensor *input, Upsample *l);
     nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input, DeformConv2d *l);
+    nvinfer1::ILayer* convert_layer(nvinfer1::ITensor *input,Padding *l);
 
 #if NV_TENSORRT_MAJOR > 5 && NV_TENSORRT_MAJOR < 8
     bool serialize(const char *filename);

include/tkDNN/kernels.h

@@ -49,7 +49,6 @@ void dcnV2CudaForward(cublasStatus_t stat, cublasHandle_t handle,
 
 void scalAdd(dnnType* dstData, int size, float alpha, float beta, int inc, cudaStream_t stream = cudaStream_t(0));
 
-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 = cudaStream_t(0));
-
+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 = cudaStream_t(0));
 
 #endif //KERNELS_H