diff --git a/CNNDemo/ResNet50Weight.bin b/CNNDemo/ResNet50Weight.bin
index abcb6f6..f60947c 100644
Binary files a/CNNDemo/ResNet50Weight.bin and b/CNNDemo/ResNet50Weight.bin differ
diff --git a/CNNDemo/Resnet50.py b/CNNDemo/Resnet50.py
index 7cf7ef0..e44a955 100644
--- a/CNNDemo/Resnet50.py
+++ b/CNNDemo/Resnet50.py
@@ -15,12 +15,30 @@ import struct
 from struct import Struct
 
 
+# m = nn.BatchNorm2d(1)
+
+# m.weight.data = torch.ones(1)
+# m.bias.data = torch.ones(1)
+# m.running_mean.data = torch.ones(1)*2.0
+# m.running_var.data = torch.zeros(1)
+
+# # Without Learnable Parameters
+# # m = nn.BatchNorm2d(1, affine=False)
+# input = torch.ones(1, 1, 4, 4) * 2.0
+# output = m(input)
+# print(output)
+
+
 CurrentPath = os.path.split(os.path.realpath(__file__))[0]+"/"
 
-
 resnet50 = models.resnet50(pretrained=True)
+
+
 # torch.save(resnet50, CurrentPath+'params.pth')
 resnet50 = torch.load(CurrentPath+'params.pth')
+resnet50.eval()
+
+
 print("===========================")
 print("===========================")
 print("===========================")
@@ -282,8 +300,26 @@ for batch_idx, (data, target) in enumerate(val_loader):
     currentbyte,binaryfile,strg = genData("verify_input", data, currentbyte, binaryfile, strg)
     x = resnet50.conv1(data)
     currentbyte,binaryfile,strg = genData("verify_conv1", x, currentbyte, binaryfile, strg)
+    
+
+    print("bias")
+    print(resnet50.bn1.bias.data)
+    print("weight")
+    print(resnet50.bn1.weight.data)  
+    print("mean")
+    print(resnet50.bn1.running_mean.data)  
+    print("var")
+    print(resnet50.bn1.running_var.data)
+    print("input")
+    print(x)
+
     x = resnet50.bn1(x)
     currentbyte,binaryfile,strg = genData("verify_bn1", x, currentbyte, binaryfile, strg)
+    
+
+    print("output")
+    print(x)
+    
     x = resnet50.relu(x)
     currentbyte,binaryfile,strg = genData("verify_relu", x, currentbyte, binaryfile, strg)
     x = resnet50.maxpool(x)