用于学习记录

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前言

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一、SEAM、MultiSEAM

1.1 models/common.py

class Residual(nn.Module):def __init__(self, fn):super(Residual, self).__init__()self.fn = fndef forward(self, x):return self.fn(x) + xclass SEAM(nn.Module):def __init__(self, c1, c2, n, reduction=16):super(SEAM, self).__init__()if c1 != c2:c2 = c1self.DCovN = nn.Sequential(# nn.Conv2d(c1, c2, kernel_size=3, stride=1, padding=1, groups=c1),# nn.GELU(),# nn.BatchNorm2d(c2),*[nn.Sequential(Residual(nn.Sequential(nn.Conv2d(in_channels=c2, out_channels=c2, kernel_size=3, stride=1, padding=1, groups=c2),nn.GELU(),nn.BatchNorm2d(c2))),nn.Conv2d(in_channels=c2, out_channels=c2, kernel_size=1, stride=1, padding=0, groups=1),nn.GELU(),nn.BatchNorm2d(c2)) for i in range(n)])self.avg_pool = torch.nn.AdaptiveAvgPool2d(1)self.fc = nn.Sequential(nn.Linear(c2, c2 // reduction, bias=False),nn.ReLU(inplace=True),nn.Linear(c2 // reduction, c2, bias=False),nn.Sigmoid())self._initialize_weights()# self.initialize_layer(self.avg_pool)self.initialize_layer(self.fc)def forward(self, x):b, c, _, _ = x.size()y = self.DCovN(x)y = self.avg_pool(y).view(b, c)y = self.fc(y).view(b, c, 1, 1)y = torch.exp(y)return x * y.expand_as(x)def _initialize_weights(self):for m in self.modules():if isinstance(m, nn.Conv2d):nn.init.xavier_uniform_(m.weight, gain=1)elif isinstance(m, nn.BatchNorm2d):nn.init.constant_(m.weight, 1)nn.init.constant_(m.bias, 0)def initialize_layer(self, layer):if isinstance(layer, (nn.Conv2d, nn.Linear)):torch.nn.init.normal_(layer.weight, mean=0., std=0.001)if layer.bias is not None:torch.nn.init.constant_(layer.bias, 0)def DcovN(c1, c2, depth, kernel_size=3, patch_size=3):dcovn = nn.Sequential(nn.Conv2d(c1, c2, kernel_size=patch_size, stride=patch_size),nn.SiLU(),nn.BatchNorm2d(c2),*[nn.Sequential(Residual(nn.Sequential(nn.Conv2d(in_channels=c2, out_channels=c2, kernel_size=kernel_size, stride=1, padding=1, groups=c2),nn.SiLU(),nn.BatchNorm2d(c2))),nn.Conv2d(in_channels=c2, out_channels=c2, kernel_size=1, stride=1, padding=0, groups=1),nn.SiLU(),nn.BatchNorm2d(c2)) for i in range(depth)])return dcovnclass MultiSEAM(nn.Module):def __init__(self, c1, c2, depth, kernel_size=3, patch_size=[3, 5, 7], reduction=16):super(MultiSEAM, self).__init__()if c1 != c2:c2 = c1self.DCovN0 = DcovN(c1, c2, depth, kernel_size