code: def unreduce_array(array, shape, axis, keepdims):
    
    # NumPy uses a special default value for keepdims, which is equivalent to
    # False.
    if axis is not None and (not keepdims or keepdims is numpy._NoValue):  # pylint: disable=protected-access
      if isinstance(axis, int):
        axis = axis,
      for ax in sorted(axis):
        array = numpy.expand_dims(array, ax)
    return numpy.broadcast_to(array, shape)
docs: Reverse summing over a dimension, NumPy implementation.
  
    Args:
      array: The array that was reduced.
      shape: The original shape of the array before reduction.
      axis: The axis or axes that were summed.
      keepdims: Whether these axes were kept as singleton axes.
  
    Returns:
      An array with axes broadcast to match the shape of the original array.