neural_network #4

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s452622 merged 34 commits from neural_network into master 2021-06-08 23:47:22 +02:00
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@ -22,29 +22,28 @@ if __name__ == '__main__':
nn.Linear(input_dim, output_dim),
nn.LogSoftmax()
)
def train(model, n_iter):
criterion = nn.NLLLoss()
optimizer = optim.SGD(model.parameters(), lr=0.001)
for epoch in range(n_iter):
for image, label in zip(train_images, train_labels):
print(image.shape)
optimizer.zero_grad()
output = model(image)
loss = criterion(output.unsqueeze(0), label.unsqueeze(0))
loss.backward()
optimizer.step()
print(f'epoch: {epoch:03}')
train(model, 100)
# def accuracy(expected, predicted):
# return len([1 for e, p in zip(expected, predicted) if e == p]) / len(expected)
# return len([_ for e, p in zip(expected, predicted) if e == p]) / len(expected)
#
#
# predicted = [model(image).argmax() for image in train_images]