Hello, this is my first post here, so don’t be too harsh on me 
I was just wondering if there is any difference between using nn.ReflectionPadding2d before Conv2d layer and just setting padding_mode of Conv2d to ‘reflect’?
It should yield the same results as seen here:
x = torch.randn(2, 3, 24, 24)
conv = nn.Conv2d(3, 6, 3)
pad = nn.ReflectionPad2d(1)
out = pad(x)
out = conv(out)
conv_pad = nn.Conv2d(3, 6, 3, 1, 1, padding_mode='reflect')
conv_pad.load_state_dict(conv.state_dict())
out_pad = conv_pad(x)
print((out - out_pad).abs().max())
> tensor(0., grad_fn=<MaxBackward1>)
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Hello, your posts are always so helpful! I’ve been using pytorch a lot over the past year and I find myself coming across your posts all the time. I totally want to thank you for all your helpful posts. Meta, give this man a raise! 
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