24 lines
776 B
Python
24 lines
776 B
Python
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import torch.nn as nn
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import torch.nn.functional as F
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class CNNModel(nn.Module): #model of the CNN type
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def __init__(self):
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super(CNNModel, self).__init__()
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self.conv1 = nn.Conv2d(3, 32, 5)
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self.conv2 = nn.Conv2d(32, 64, 5)
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self.conv3 = nn.Conv2d(64, 128, 3)
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self.conv4 = nn.Conv2d(128, 256, 5)
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self.fc1 = nn.Linear(256, 50)
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self.pool = nn.MaxPool2d(2, 2)
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def forward(self, x):
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x = self.pool(F.relu(self.conv1(x)))
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x = self.pool(F.relu(self.conv2(x)))
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x = self.pool(F.relu(self.conv3(x)))
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x = self.pool(F.relu(self.conv4(x)))
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bs, _, _, _ = x.shape
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x = F.adaptive_avg_pool2d(x, 1).reshape(bs, -1)
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x = self.fc1(x)
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return x
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