code: def to_numpy_multilabel(y):
      # reshapes input array to (N x ..., C)
      y = y.transpose(1, 0).cpu().numpy()
      num_classes = y.shape[0]
      y = y.reshape((num_classes, -1)).transpose(1, 0)
      return y
  
imports: import warnings
  import pytest
  import torch
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.metrics import precision_score
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import Precision
label_desc: Use image node_id 9 for calling a global function with example usage: to_numpy_multilabel(y) and returns: y