code: def evaluate_model(model, loss, data_iter):
      model.eval()
      l_sum, n = 0.0, 0
      with torch.no_grad():
          for x, y in data_iter:
              y_pred = model(x).view(len(x), -1)
              l = loss(y_pred, y)
              l_sum += l.item() * y.shape[0]
              n += y.shape[0]
          return l_sum / n
  
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate_model(model, loss, data_iter) and returns: unknown