class_docstr: Parameters
  ----------
  data : Buffer
      The Timedelta values
  dtype : np.dtype
      The data type
  size : int
      Size of memory allocation.
  mask : Buffer; optional
      The validity mask
  offset : int
      Data offset
  null_count : int, optional
      The number of null values.
      If None, it is calculated automatically.
code: def fillna(
      self,
      fill_value: Any = None,
      method: Optional[str] = None,
  ) -> Self:
      if fill_value is not None:
          if cudf.utils.utils._isnat(fill_value):
              return self.copy(deep=True)
          if is_scalar(fill_value):
              fill_value = cudf.Scalar(fill_value)
              dtype = determine_out_dtype(self.dtype, fill_value.dtype)
              fill_value = fill_value.astype(dtype)
              if self.dtype != dtype:
                  return cast(
                      Self,
                      self.astype(dtype).fillna(fill_value, method),
                  )
          else:
              fill_value = column.as_column(
                  fill_value, nan_as_null=False
              )
      return super().fillna(fill_value, method)
  
imports: from __future__ import annotations
  import datetime
  from typing import Any, Optional, Sequence, cast
  import numpy
  import pandas
  import pyarrow
  from typing_extensions import Self
  import cudf
  from cudf import _lib
  from cudf._typing import ColumnBinaryOperand, DatetimeLikeScalar, Dtype
  from cudf.api.types import is_scalar, is_timedelta64_dtype
  from cudf.core.buffer import Buffer, acquire_spill_lock
  from cudf.core.column import ColumnBase, column, string
  from cudf.utils.dtypes import np_to_pa_dtype
  from cudf.utils.utils import _all_bools_with_nulls
label_desc: Use image node_id 9 for calling the TimeDeltaColumn obj's underlying member method code with example usage: obj.fillna(fill_value, method) and returns: super, self, cast