diff --git a/unsuper/minist.py b/unsuper/minist.py
index 4421692..21abca5 100644
--- a/unsuper/minist.py
+++ b/unsuper/minist.py
@@ -108,7 +108,6 @@ epochs = 10
 model.conv1.weight.requires_grad = True
 model.conv2.weight.requires_grad = False
 model.fc1.weight.requires_grad = False
-optimizer_unsuper = torch.optim.SGD(model.parameters(), lr=0.1)
 n_total_steps = len(train_loader)
 for epoch in range(epochs):
     for i, (images, labels) in enumerate(train_loader):
@@ -121,9 +120,11 @@ for epoch in range(epochs):
         diff_ratio_mean = torch.mean(diff_ratio * diff_ratio, dim=1)
         label = diff_ratio_mean * 0.5
         loss = F.l1_loss(diff_ratio_mean, label)
-        optimizer_unsuper.zero_grad()
+        if model.conv1.weight.grad is None:
+            model.conv1.weight.grad = model.conv1.weight.data
+        model.conv1.weight.grad = model.conv1.weight.grad * 0.0
         loss.backward()
-        optimizer_unsuper.step()
+        model.conv1.weight.data = model.conv1.weight.data - model.conv1.weight.grad * 0.2
         if (i + 1) % 100 == 0:
             print(f"Epoch [{epoch+1}/{epochs}], Step [{i+1}/{n_total_steps}], Loss: {loss.item():.8f}")