Mise à jour de 'code/resnet18/resnet18.py'

code/resnet18/resnet18.py

         self.merge = Add()
 
         if self.__down_sample:
-            # perform down sampling using stride of 2, according to [1].
-            self.res_conv = Conv2D(
+
+          self.res_conv = Conv2D(
                 self.__channels, strides=2, kernel_size=(1, 1), kernel_initializer=INIT_SCHEME, padding="same")
             self.res_bn = BatchNormalization()
 
             res = self.res_conv(res)
             res = self.res_bn(res)
 
-        # if not perform down sample, then add a shortcut directly
+        
         x = self.merge([x, res])
         out = x + tf.sin(x)**2 #tf.nn.relu(x)
         return out