code: def forward(self, predictions: np.ndarray, labels: np.ndarray) -> float:  # type: ignore
      pred_dim = len(predictions.shape)
      diff = insert_intermediate_dims(labels, predictions) - predictions
      q = self.q.reshape((-1,) + (1,) * (pred_dim - 2))
      error = np.maximum(q * diff, (q - 1.0) * diff)
      return error.mean(0).sum().item()
  
imports: import numpy
  from typing import Any
  from typing import Tuple
  from typing import Optional
  from cftool.misc import print_warning
  from cftool.array import iou
  from cftool.array import corr
  from cftool.array import softmax
  from cftool.array import get_full_logits
  from cftool.array import get_label_predictions
  from cftool.types import np_dict_type
  from .schema import IMetric
  from .schema import IDataLoader
  from .constants import LABEL_KEY
  from .constants import PREDICTIONS_KEY
  from .misc.toolkit import insert_intermediate_dims
label_desc: Use image node_id 3 for calling the Quantile obj's underlying member method code with example usage: obj.forward(predictions, labels) and returns: error