tensorflow/models · error · ValueError

k must be a positive integer.

Error message

k must be a positive integer.

What it means

Error "k must be a positive integer." thrown in tensorflow/models.

Source

Thrown at official/projects/yt8m/eval_utils/eval_util.py:123

      are 'batch' x 'num_classes'.
    labels: A numpy matrix containing the ground truth labels. Dimensions are
      'batch' x 'num_classes'.
    k: the top k non-zero entries to preserve in each prediction.

  Returns:
    A tuple (predictions,labels, true_positives). 'predictions' and 'labels'
    are lists of lists of floats. 'true_positives' is a list of scalars. The
    length of the lists are equal to the number of classes. The entries in the
    predictions variable are probability predictions, and
    the corresponding entries in the labels variable are the ground truth for
    those predictions. The entries in 'true_positives' are the number of true
    positives for each class in the ground truth.

  Raises:
    ValueError: An error occurred when the k is not a positive integer.
  """
  if k <= 0:
    raise ValueError("k must be a positive integer.")
  k = min(k, predictions.shape[1])
  num_classes = predictions.shape[1]
  prediction_triplets = []
  for video_index in range(predictions.shape[0]):
    prediction_triplets.extend(
        top_k_triplets(predictions[video_index], labels[video_index], k))
  out_predictions = [[] for _ in range(num_classes)]
  out_labels = [[] for _ in range(num_classes)]
  for triplet in prediction_triplets:
    out_predictions[triplet[0]].append(triplet[1])
    out_labels[triplet[0]].append(triplet[2])
  out_true_positives = [np.sum(labels[:, i]) for i in range(num_classes)]

  return out_predictions, out_labels, out_true_positives


def top_k_triplets(predictions, labels, k=20):
  """Get the top_k for a 1-d numpy array.

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/yt8m/eval_utils/eval_util.py:123 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/f27c294c78ef6423. Report an issue: GitHub.