80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
from torch import nn
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class Conv(nn.Module):
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def __init__(self, inp_dim, out_dim, kernel_size=3, stride=1, bn=False, relu=True):
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super(Conv, self).__init__()
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self.inp_dim = inp_dim
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self.conv = nn.Conv2d(inp_dim, out_dim, kernel_size, stride, padding=(kernel_size - 1) // 2, bias=False)
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self.relu = None
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self.bn = None
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if relu:
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self.relu = nn.ReLU()
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if bn:
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self.bn = nn.BatchNorm2d(out_dim)
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def forward(self, x):
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assert x.size()[1] == self.inp_dim, "{} {}".format(x.size()[1], self.inp_dim)
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x = self.conv(x)
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if self.bn is not None:
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x = self.bn(x)
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if self.relu is not None:
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x = self.relu(x)
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return x
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class Deconv(nn.Module):
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def __init__(self, inp_dim, out_dim, kernel_size=3, stride=1, bn=False, relu=True):
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super(Deconv, self).__init__()
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self.inp_dim = inp_dim
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self.deconv = nn.ConvTranspose2d(inp_dim, out_dim, kernel_size=kernel_size, stride=stride, bias=False)
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self.relu = None
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self.bn = None
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if relu:
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self.relu = nn.ReLU()
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if bn:
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self.bn = nn.BatchNorm2d(out_dim)
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def forward(self, x):
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assert x.size()[1] == self.inp_dim, "{} {}".format(x.size()[1], self.inp_dim)
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x = self.deconv(x)
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if self.bn is not None:
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x = self.bn(x)
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if self.relu is not None:
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x = self.relu(x)
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return x
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class Residual(nn.Module):
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def __init__(self, inp_dim, out_dim, kernel=3):
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super(Residual, self).__init__()
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self.relu = nn.ReLU()
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self.bn1 = nn.BatchNorm2d(inp_dim)
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self.conv1 = Conv(inp_dim, int(out_dim / 2), 1, relu=False)
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self.bn2 = nn.BatchNorm2d(int(out_dim / 2))
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self.conv2 = Conv(int(out_dim / 2), int(out_dim / 2), kernel, relu=False)
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self.bn3 = nn.BatchNorm2d(int(out_dim / 2))
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self.conv3 = Conv(int(out_dim / 2), out_dim, 1, relu=False)
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self.skip_layer = Conv(inp_dim, out_dim, 1, relu=False)
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if inp_dim == out_dim:
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self.need_skip = False
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else:
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self.need_skip = True
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def forward(self, x):
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if self.need_skip:
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residual = self.skip_layer(x)
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else:
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residual = x
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out = self.bn1(x)
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out = self.relu(out)
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out = self.conv1(out)
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out = self.bn2(out)
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out = self.relu(out)
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out = self.conv2(out)
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out = self.bn3(out)
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out = self.relu(out)
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out = self.conv3(out)
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out += residual
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return out
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