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code for saving the model is added

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yunjey
2017-03-11 14:54:46 +09:00
parent 278c13513f
commit 86a0872430
17 changed files with 630 additions and 37 deletions
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13
tutorials/04 - Convolutional Neural Network/main-gpu.py
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@ -11,12 +11,12 @@ batch_size = 100
learning_rate = 0.001
# MNIST Dataset
train_dataset = dsets.MNIST(root='./data/',
train_dataset = dsets.MNIST(root='../data/',
train=True,
transform=transforms.ToTensor(),
download=True)
test_dataset = dsets.MNIST(root='./data/',
test_dataset = dsets.MNIST(root='../data/',
train=False,
transform=transforms.ToTensor())
@ -77,7 +77,7 @@ for epoch in range(num_epochs):
%(epoch+1, num_epochs, i+1, len(train_dataset)//batch_size, loss.data[0]))
# Test the Model
cnn.eval()
cnn.eval() # Change model to 'eval' mode (BN uses moving mean/var).
correct = 0
total = 0
for images, labels in test_loader:
@ -85,6 +85,9 @@ for images, labels in test_loader:
outputs = cnn(images)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels).sum()
correct += (predicted.cpu() == labels).sum()
print('Test Accuracy of the model on the 10000 test images: %d %%' % (100 * correct / total))
print('Test Accuracy of the model on the 10000 test images: %d %%' % (100 * correct / total))
# Save the Trained Model
torch.save(cnn, 'cnn.pkl')