From b32355a06445396886f8326f437edddbf7873bc3 Mon Sep 17 00:00:00 2001 From: Vyas Ramasubramani Date: Tue, 19 Sep 2023 14:38:55 -0700 Subject: [PATCH] Revert "Add comment" This reverts commit bdfcd244ef806abb1bbf6d4c5d80e246554f0d2c. --- python/cudf/cudf/_lib/scalar.pyx | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/python/cudf/cudf/_lib/scalar.pyx b/python/cudf/cudf/_lib/scalar.pyx index 7a75d3a354e..d564281240b 100644 --- a/python/cudf/cudf/_lib/scalar.pyx +++ b/python/cudf/cudf/_lib/scalar.pyx @@ -338,17 +338,5 @@ def _create_proxy_nat_scalar(dtype): elif dtype.type == np.timedelta64: _set_timedelta64_from_np_scalar(result.c_value.c_obj, nat, dtype, True) return result - - # TODO: It should be able to reimplement the above with pylibcudf. - # Currently this doesn't quite seem to work, though, apparently because - # we need a way to create NaT _valid_ scalars but ingesting from - # pyarrow automatically sets them to invalid. Merely setting to valid - # after the fact is insufficient because the underlying memory appears - # to not be initialized. - # nat = pa.scalar(dtype.type('NaT').astype(dtype)) - # result.c_value = pylibcudf.Scalar.from_pyarrow_scalar(nat) - # result.c_value.c_obj.get().set_valid_async(True) - # result._dtype = dtype - # return result else: raise TypeError('NAT only valid for datetime and timedelta')