tensorflow/models · error · ValueError

the shape of predictions and actuals does not match.

Error message

the shape of predictions and actuals does not match.

What it means

Error "the shape of predictions and actuals does not match." thrown in tensorflow/models.

Source

Thrown at official/projects/yt8m/eval_utils/average_precision_calculator.py:114

    After the function call, we may call peek_ap_at_n to actually calculate
    the average precision.
    Note predictions and actuals must have the same shape.

    Args:
      predictions: a list storing the prediction scores.
      actuals: a list storing the ground truth labels. Any value larger than 0
        will be treated as positives, otherwise as negatives. num_positives = If
        the 'predictions' and 'actuals' inputs aren't complete, then it's
        possible some true positives were missed in them. In that case, you can
        provide 'num_positives' in order to accurately track recall.
      num_positives: number of positive examples.

    Raises:
      ValueError: An error occurred when the format of the input is not the
      numpy 1-D array or the shape of predictions and actuals does not match.
    """
    if len(predictions) != len(actuals):
      raise ValueError("the shape of predictions and actuals does not match.")

    if num_positives is not None:
      if not isinstance(num_positives, numbers.Number) or num_positives < 0:  # pyrefly: ignore[unsupported-operation]
        raise ValueError(
            "'num_positives' was provided but it was a negative number.")

    if num_positives is not None:
      self._total_positives += num_positives
    else:
      self._total_positives += numpy.size(
          numpy.where(numpy.array(actuals) > 1e-5))
    topk = self._top_n
    heap = self._heap

    for i in range(numpy.size(predictions)):
      if topk is None or len(heap) < topk:
        heapq.heappush(heap, (predictions[i], actuals[i]))
      else:

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/yt8m/eval_utils/average_precision_calculator.py:114 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/607e6dab7a4fb58c. Report an issue: GitHub.