Open hanhande opened 6 years ago
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'))]))
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'))]))