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import torch.nn as nn
import torch.nn.functional as F
class DUC(nn.Module):
'''
INPUT: inplanes, planes, upscale_factor
OUTPUT: (planes // 4)* ht * wd
'''
def __init__(self, inplanes, planes, upscale_factor=2):
super(DUC, self).__init__()
self.conv = nn.Conv2d(inplanes, planes, kernel_size=3, padding=1, bias=False)
self.bn = nn.BatchNorm2d(planes)
self.relu = nn.ReLU()
self.pixel_shuffle = nn.PixelShuffle(upscale_factor)
def forward(self, x):
x = self.conv(x)
x = self.bn(x)
x = self.relu(x)
x = self.pixel_shuffle(x)
return x
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