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 to_arrow(self) -> pa.Array:
      mask = None
      if self.nullable:
          mask = pa.py_buffer(
              self.mask_array_view(mode="read").copy_to_host()
          )
      data = pa.py_buffer(
          self.as_numerical_column("int64")
          .data_array_view(mode="read")
          .copy_to_host()
      )
      pa_dtype = np_to_pa_dtype(self.dtype)
      return pa.Array.from_buffers(
          type=pa_dtype,
          length=len(self),
          buffers=[mask, data],
          null_count=self.null_count,
      )
  
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 4 for calling the TimeDeltaColumn obj's underlying member method code with example usage: obj.to_arrow() and returns: pa