code: def value_counts_fill_missing_classes(
      x, num_classes, *, multi_label=False
  ) -> np.ndarray:
      """Same as ``internal.util.value_counts`` but requires that num_classes is provided and
      always fills missing classes with zero counts.
  
      See ``internal.util.value_counts`` for parameter docstrings."""
  
      return value_counts(
          x, num_classes=num_classes, multi_label=multi_label
      )
  
imports: import warnings
  import numpy
  import pandas
  from typing import Union, Tuple
  from cleanlab.typing import DatasetLike, LabelLike
  from cleanlab.internal.validation import labels_to_array
  from cleanlab.internal.constants import FLOATING_POINT_COMPARISON, TINY_VALUE
label_desc: Use image node_id 5 for calling a global function with example usage: value_counts_fill_missing_classes(x, num_classes) and returns: value_counts