def index_duplicated(index, keep="first"):
    """
    Indicate duplicate index values.

    Duplicated values are indicated as ``True`` values in the resulting
    array. Either all duplicates, all except the first, or all except the
    last occurrence of duplicates can be indicated.

    Parameters
    ----------
    keep : {'first', 'last', False}, default 'first'
        The value or values in a set of duplicates to mark as missing.
        - 'first' : Mark duplicates as ``True`` except for the first
          occurrence.
        - 'last' : Mark duplicates as ``True`` except for the last
          occurrence.
        - ``False`` : Mark all duplicates as ``True``.

    Returns
    -------
    Tensor

    See Also
    --------
    Series.duplicated : Equivalent method on pandas.Series.
    DataFrame.duplicated : Equivalent method on pandas.DataFrame.
    Index.drop_duplicates : Remove duplicate values from Index.

    Examples
    --------
    By default, for each set of duplicated values, the first occurrence is
    set to False and all others to True:

    >>> import mars.dataframe as md

    >>> idx = md.Index(['lama', 'cow', 'lama', 'beetle', 'lama'])
    >>> idx.duplicated().execute()
    array([False, False,  True, False,  True])

    which is equivalent to

    >>> idx.duplicated(keep='first').execute()
    array([False, False,  True, False,  True])

    By using 'last', the last occurrence of each set of duplicated values
    is set on False and all others on True:

    >>> idx.duplicated(keep='last').execute()
    array([ True, False,  True, False, False])

    By setting keep on ``False``, all duplicates are True:

    >>> idx.duplicated(keep=False).execute()
    array([ True, False,  True, False,  True])
    """
    return index.to_series().duplicated(keep=keep).to_tensor()