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I've tried to print the binarized weights , but it seems that the weights are still unbinarized.
Here is the related code:
optimizer.zero_grad() outputs = cnn(images) print cnn.state_dict()['layer1.0.weight'] loss = criterion(outputs, labels) loss.backward() optimizer.step()
And here is the results: (95,1 ,.,.) = 1.00000e-02 * -3.3969 2.1018 -3.1642 3.2847 0.9943 0.6272 0.4166 0.3461 -1.0757
(95,2 ,.,.) = 1.00000e-02 * -0.1648 -3.8358 0.9648 0.0416 -1.2637 -0.7090 3.0703 -2.1837 -1.9243 .....
Could you help me check this problem? THX:)
The text was updated successfully, but these errors were encountered:
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I've tried to print the binarized weights , but it seems that the weights are still unbinarized.
Here is the related code:
Forward + Backward + Optimize
And here is the results:
(95,1 ,.,.) =
1.00000e-02 *
-3.3969 2.1018 -3.1642
3.2847 0.9943 0.6272
0.4166 0.3461 -1.0757
(95,2 ,.,.) =
1.00000e-02 *
-0.1648 -3.8358 0.9648
0.0416 -1.2637 -0.7090
3.0703 -2.1837 -1.9243
.....
Could you help me check this problem? THX:)
The text was updated successfully, but these errors were encountered: