model = EngineModel(num_embeddings=1000, embedding_dim=128)
# 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) model = EngineModel(num_embeddings=1000
def forward(self, engine_number): embedded = self.embedding(engine_number) out = torch.relu(self.fc(embedded)) out = self.output_layer(out) return out tecdoc motornummer