File size: 951 Bytes
e3814d7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | # Code was taken from https://github.com/wangjuan001/hicplus
import torch.nn as nn
import torch.nn.functional as F
conv2d1_filters_numbers = 8
conv2d1_filters_size = 9
conv2d2_filters_numbers = 8
conv2d2_filters_size = 1
conv2d3_filters_numbers = 1
conv2d3_filters_size = 5
class Generator(nn.Module):
def __init__(self):
super(Generator, self).__init__()
# 1 input image channel, 6 output channels, 5x5 square convolution
# kernel
self.conv1 = nn.Conv2d(1, conv2d1_filters_numbers, conv2d1_filters_size)
self.conv2 = nn.Conv2d(conv2d1_filters_numbers, conv2d2_filters_numbers, conv2d2_filters_size)
self.conv3 = nn.Conv2d(conv2d2_filters_numbers, 1, conv2d3_filters_size)
def forward(self, x):
#print("start forwardingf")
x = self.conv1(x)
x = F.relu(x)
x = self.conv2(x)
x = F.relu(x)
x = self.conv3(x)
x = F.relu(x)
return x
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