* @since 22.0
   */
  public long approximateElementCount() {
    long bitSize = bits.bitSize();
    long bitCount = bits.bitCount();

    /*
     * Each insertion is expected to reduce the # of clear bits by a factor of
     * `numHashFunctions/bitSize`. So, after n insertions, expected bitCount is `bitSize * (1 - (1 -
     * numHashFunctions/bitSize)^n)`. Solving that for n, and approximating `ln x` as `x - 1` when x

In Python 3.10 there's also a **new syntax** where you can put the possible types separated by a <abbr title='also called "bitwise or operator", but that meaning is not relevant here'>vertical bar (`|`)</abbr>.

//// tab | Python 3.10+

```Python hl_lines="1"
{!> ../../docs_src/python_types/tutorial008b_py310.py!}
```

////

            return 0;
        }
        exists();
        return attributes & ATTR_GET_MASK;
    }

    /**
     * Set the attributes of this file. Attributes are composed into a
     * bitset by bitwise ORing the {@code ATTR_*} constants. Setting the
     * value returned by {@code getAttributes} will result in both files
     * having the same attributes.
     * @param attrs the attributes to set

*   Adds `tf.sparse.map_values` to apply a function to the `.value`s of
    `SparseTensor` arguments.
*   The Python bitwise operators for `Tensor` (`__and__`, `__or__`, `__xor__`
    and `__invert__` now support non-`bool` arguments and apply the
    corresponding bitwise ops. `bool` arguments continue to be supported and
    dispatch to logical ops. This brings them more in line with Python and NumPy
    behavior.