Remove rigid network

1 files changed, 3 insertions, 29 deletions

diff --git a/src/classification.py b/src/classification.py
index 110a8d9..7a93e7f 100644
--- a/src/classification.py
+++ b/src/classification.py
@@ -25,33 +25,7 @@ def count_correct(output, target):
             correct += 1
     return correct
 
-class Net(nn.Module):
-    def __init__(self):
-        super(Net, self).__init__()
-        self.conv1 = nn.Conv2d(1, 6, 3, padding=1)
-        self.conv2 = nn.Conv2d(6, 16, 3, padding=1)
-        self.conv3 = nn.Conv2d(16, 32, 3, padding=1)
-        self.fc1 = nn.Linear(288, 120)
-        self.fc2 = nn.Linear(120, 84)
-        self.fc3 = nn.Linear(84, 6)
+def finalizer(x):
+    return torch.sigmoid(x)
 
-    def forward(self, x):
-        x = x.unsqueeze(1)
-        x = self.conv1(x)
-        x = F.relu(x)
-        x = F.max_pool2d(x, (2, 2))
-        x = F.max_pool2d(F.relu(self.conv2(x)), 2)
-        x = F.max_pool2d(F.relu(self.conv3(x)), 2)
-        x = x.view(-1, self.num_flat_features(x))
-        x = F.relu(self.fc1(x))
-        x = F.relu(self.fc2(x))
-        x = self.fc3(x)
-        x = torch.sigmoid(x)
-        return x
-
-    def num_flat_features(self, x):
-        size = x.size()[1:]  # all dimensions except the batch dimension
-        num_features = 1
-        for s in size:
-            num_features *= s
-        return num_features
+outputs = 6