code: def test_round_int64(self, timestamp, freq):
      # check that all rounding modes are accurate to int64 precision
      # see GH#22591
      dt = Timestamp(timestamp).as_unit("ns")
      unit = to_offset(freq).nanos
  
      # test floor
      result = dt.floor(freq)
      assert result._value % unit == 0, f"floor not a {freq} multiple"
      assert 0 <= dt._value - result._value < unit, "floor error"
  
      # test ceil
      result = dt.ceil(freq)
      assert result._value % unit == 0, f"ceil not a {freq} multiple"
      assert 0 <= result._value - dt._value < unit, "ceil error"
  
      # test round
      result = dt.round(freq)
      assert result._value % unit == 0, f"round not a {freq} multiple"
      assert abs(result._value - dt._value) <= unit // 2, "round error"
      if unit % 2 == 0 and abs(result._value - dt._value) == unit // 2:
          # round half to even
          assert (
              result._value // unit % 2 == 0
          ), "round half to even error"
  
imports: from hypothesis import given, strategies
  import numpy
  import pytest
  import pytz
  from pandas._libs import lib
  from pandas._libs.tslibs import NaT, OutOfBoundsDatetime, Timedelta, Timestamp, iNaT, to_offset
  from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
  from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG
  import pandas._testing
label_desc: Use image node_id 14 for calling the TestTimestampRound obj's underlying member method code with example usage: obj.test_round_int64(timestamp, freq) without return types