code: def check_label_shapes(labels, preds, wrap=False, shape=False):
      
      if not shape:
          label_shape, pred_shape = len(labels), len(preds)
      else:
          label_shape, pred_shape = labels.shape, preds.shape
  
      if label_shape != pred_shape:
          raise ValueError("Shape of labels {} does not match shape of "
                           "predictions {}".format(label_shape, pred_shape))
  
      if wrap:
          if isinstance(labels, ndarray.ndarray.NDArray):
              labels = [labels]
          if isinstance(preds, ndarray.ndarray.NDArray):
              preds = [preds]
  
      return labels, preds
docs: Helper function for checking shape of label and prediction
  
      Parameters
      ----------
      labels : list of `NDArray`
          The labels of the data.
  
      preds : list of `NDArray`
          Predicted values.
  
      wrap : boolean
          If True, wrap labels/preds in a list if they are single NDArray
  
      shape : boolean
          If True, check the shape of labels and preds;
          Otherwise only check their length.