In [6]: idx = cudf.date_range("2021-01-01", periods=3, freq="D")

In [7]: idx
Out[7]: DatetimeIndex(['2021-01-01', '2021-01-02', '2021-01-03'], dtype='datetime64[ns]', freq='D')

In [9]: idx._freq
Out[9]: <DateOffset: days=1>

In [10]: idx.repeat(2)
Out[10]: ---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/pandas/core/arrays/datetimelike.py:2124, in TimelikeOps._validate_frequency(cls, index, freq, **kwargs)
   2123     if not np.array_equal(index.asi8, on_freq.asi8):
-> 2124         raise ValueError
   2125 except ValueError as err:

ValueError: 

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/IPython/core/formatters.py:711, in PlainTextFormatter.__call__(self, obj)
    704 stream = StringIO()
    705 printer = pretty.RepresentationPrinter(stream, self.verbose,
    706     self.max_width, self.newline,
    707     max_seq_length=self.max_seq_length,
    708     singleton_pprinters=self.singleton_printers,
    709     type_pprinters=self.type_printers,
    710     deferred_pprinters=self.deferred_printers)
--> 711 printer.pretty(obj)
    712 printer.flush()
    713 return stream.getvalue()

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/IPython/lib/pretty.py:411, in RepresentationPrinter.pretty(self, obj)
    408                         return meth(obj, self, cycle)
    409                 if cls is not object \
    410                         and callable(cls.__dict__.get('__repr__')):
--> 411                     return _repr_pprint(obj, self, cycle)
    413     return _default_pprint(obj, self, cycle)
    414 finally:

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/IPython/lib/pretty.py:779, in _repr_pprint(obj, p, cycle)
    777 """A pprint that just redirects to the normal repr function."""
    778 # Find newlines and replace them with p.break_()
--> 779 output = repr(obj)
    780 lines = output.splitlines()
    781 with p.group():

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/nvtx/nvtx.py:116, in annotate.__call__.<locals>.inner(*args, **kwargs)
    113 @wraps(func)
    114 def inner(*args, **kwargs):
    115     libnvtx_push_range(self.attributes, self.domain.handle)
--> 116     result = func(*args, **kwargs)
    117     libnvtx_pop_range(self.domain.handle)
    118     return result

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/cudf/core/index.py:1393, in Index.__repr__(self)
   1391         output = output.replace("'", "")
   1392 else:
-> 1393     output = repr(preprocess.to_pandas())
   1395 # Fix and correct the class name of the output
   1396 # string by finding first occurrence of "(" in the output
   1397 index_class_split_index = output.find("(")

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/nvtx/nvtx.py:116, in annotate.__call__.<locals>.inner(*args, **kwargs)
    113 @wraps(func)
    114 def inner(*args, **kwargs):
    115     libnvtx_push_range(self.attributes, self.domain.handle)
--> 116     result = func(*args, **kwargs)
    117     libnvtx_pop_range(self.domain.handle)
    118     return result

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/cudf/core/index.py:2158, in DatetimeIndex.to_pandas(self, nullable, arrow_type)
   2152 else:
   2153     freq = (
   2154         self._freq._maybe_as_fast_pandas_offset()
   2155         if self._freq is not None
   2156         else None
   2157     )
-> 2158     return pd.DatetimeIndex(result, name=self.name, freq=freq)

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/pandas/core/indexes/datetimes.py:370, in DatetimeIndex.__new__(cls, data, freq, tz, normalize, closed, ambiguous, dayfirst, yearfirst, dtype, copy, name)
    367         data = data.copy()
    368     return cls._simple_new(data, name=name)
--> 370 dtarr = DatetimeArray._from_sequence_not_strict(
    371     data,
    372     dtype=dtype,
    373     copy=copy,
    374     tz=tz,
    375     freq=freq,
    376     dayfirst=dayfirst,
    377     yearfirst=yearfirst,
    378     ambiguous=ambiguous,
    379 )
    380 refs = None
    381 if not copy and isinstance(data, (Index, ABCSeries)):

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/pandas/core/arrays/datetimes.py:394, in DatetimeArray._from_sequence_not_strict(cls, data, dtype, copy, tz, freq, dayfirst, yearfirst, ambiguous)
    391     result = result.as_unit(unit)
    393 validate_kwds = {"ambiguous": ambiguous}
--> 394 result._maybe_pin_freq(freq, validate_kwds)
    395 return result

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/pandas/core/arrays/datetimelike.py:2088, in TimelikeOps._maybe_pin_freq(self, freq, validate_kwds)
   2084 elif self._freq is None:
   2085     # We cannot inherit a freq from the data, so we need to validate
   2086     #  the user-passed freq
   2087     freq = to_offset(freq)
-> 2088     type(self)._validate_frequency(self, freq, **validate_kwds)
   2089     self._freq = freq
   2090 else:
   2091     # Otherwise we just need to check that the user-passed freq
   2092     #  doesn't conflict with the one we already have.

File /nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/pandas/core/arrays/datetimelike.py:2135, in TimelikeOps._validate_frequency(cls, index, freq, **kwargs)
   2129     raise err
   2130 # GH#11587 the main way this is reached is if the `np.array_equal`
   2131 #  check above is False.  This can also be reached if index[0]
   2132 #  is `NaT`, in which case the call to `cls._generate_range` will
   2133 #  raise a ValueError, which we re-raise with a more targeted
   2134 #  message.
-> 2135 raise ValueError(
   2136     f"Inferred frequency {inferred} from passed values "
   2137     f"does not conform to passed frequency {freq.freqstr}"
   2138 ) from err

ValueError: Inferred frequency None from passed values does not conform to passed frequency D

In [11]: idx.to_pandas().repeat(2)
Out[11]: 
DatetimeIndex(['2021-01-01', '2021-01-01', '2021-01-02', '2021-01-02',
               '2021-01-03', '2021-01-03'],
              dtype='datetime64[ns]', freq=None)