code: def recall_at_k(
      y_true: List[int], y_pred: List[List[np.ndarray]], k: int
  ):
      """
      Calculates recall at k ranking metric.
  
      Args:
          y_true: Labels. Not used in the calculation of the metric.
          y_predicted: Predictions.
              Each prediction contains ranking score of all ranking candidates for the particular data sample.
              It is supposed that the ranking score for the true candidate goes first in the prediction.
  
      Returns:
          Recall at k
      """
      num_examples = float(len(y_pred))
      predictions = np.array(y_pred)
      predictions = np.flip(np.argsort(predictions, -1), -1)[:, :k]
      num_correct = 0
      for el in predictions:
          if 0 in el:
              num_correct += 1
      return float(num_correct) / num_examples
  
imports: from typing import List
  import numpy
  from deeppavlov.core.common.metrics_registry import register_metric
label_desc: Use image node_id 1 for calling a global function with example usage: recall_at_k(y_true, y_pred, k) and returns: unknown