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network model mobilenetplus #15

@hanhande

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@hanhande

I don't know what that means. Can you elaborate on the specific function of this piece? Why use the 3x3 convolution kernel?

self.score = nn.Sequential(OrderedDict([("norm.1", norm_act(out_sec + in_stag2_up_chs)),
("conv.1", nn.Conv2d(out_sec + in_stag2_up_chs,
out_sec + in_stag2_up_chs,
kernel_size=3, stride=1, padding=2,
dilation=2, bias=False)),
("norm.2", norm_act(out_sec + in_stag2_up_chs)),
("conv.2", nn.Conv2d(out_sec + in_stag2_up_chs, self.n_class,
kernel_size=1, stride=1, padding=0,
bias=True)),
("up1", nn.Upsample(size=in_size, mode='bilinear'))]))

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