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import torch.optim as optim
#define optimizer and loss
optimizer = optim.Adam(model.parameters())
criterion = nn.BCELoss()
#define metric
def binary_accuracy(preds, y):
#round predictions to the closest integer
rounded_preds = torch.round(preds)
correct = (rounded_preds == y).float()
acc = correct.sum() / len(correct)
return acc
#push to cuda if available
model = model.to(device)
criterion = criterion.to(device)
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