def __len__(self): return len(self.engine_numbers)

model = EngineModel(num_embeddings=1000, embedding_dim=128)

# Initialize dataset, model, and data loader # For demonstration, assume we have 1000 unique engine numbers and labels engine_numbers = torch.randint(0, 1000, (100,)) labels = torch.randn(100) dataset = EngineDataset(engine_numbers, labels) data_loader = DataLoader(dataset, batch_size=32)