init

components/ResBlock.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+#############################################################
+# File: ResBlock.py
+# Created Date: Monday July 5th 2021
+# Author: Chen Xuanhong
+# Email: chenxuanhongzju@outlook.com
+# Last Modified:  Monday, 5th July 2021 12:18:18 am
+# Modified By: Chen Xuanhong
+# Copyright (c) 2021 Shanghai Jiao Tong University
+#############################################################
+
+from torch import nn
+
+class ResBlock(nn.Module):
+    def __init__(self, in_channel, k_size = 3, stride=1):
+        super().__init__()
+        padding_size = int((k_size -1)/2)
+        self.block = nn.Sequential(
+                nn.ReflectionPad2d(padding_size),
+                nn.Conv2d(in_channels = in_channel , out_channels = in_channel , kernel_size= k_size, stride=stride, bias= False),
+                nn.InstanceNorm2d(in_channel, affine=True, momentum=0),
+                nn.ReflectionPad2d(padding_size),
+                nn.Conv2d(in_channels = in_channel , out_channels = in_channel , kernel_size= k_size, stride=stride, bias= False),
+                nn.InstanceNorm2d(in_channel, affine=True, momentum=0)
+            )
+        self.__weights_init__()
+
+    def __weights_init__(self):
+        for m in self.modules():
+            if isinstance(m,nn.Conv2d):
+                nn.init.xavier_uniform_(m.weight)
+
+    def forward(self, input):
+        res = input
+        h   = self.block(input)
+        out = h + res
+        return out