# Training criterion = nn.MSELoss() optimizer = optim.Adam(model.parameters(), lr=0.001)
# Assume we have a dataset of engine numbers and corresponding labels/features class EngineDataset(Dataset): def __init__(self, engine_numbers, labels): self.engine_numbers = engine_numbers self.labels = labels tecdoc motornummer
def __len__(self): return len(self.engine_numbers) # Training criterion = nn
def __getitem__(self, idx): engine_number = self.engine_numbers[idx] label = self.labels[idx] return {"engine_number": engine_number, "label": label} tecdoc motornummer