code: def _ensure_gpu_buffer(
      buf, data_type, allow_copy: bool
  ) -> _CuDFBuffer:
      # if `buf` is a (protocol) buffer that lives on the GPU already,
      # return it as is.  Otherwise, copy it to the device and return
      # the resulting buffer.
      if buf.__dlpack_device__()[0] != _Device.CUDA:
          if allow_copy:
              dbuf = rmm.DeviceBuffer(ptr=buf.ptr, size=buf.bufsize)
              return _CuDFBuffer(
                  as_buffer(dbuf, exposed=True),
                  protocol_dtype_to_cupy_dtype(data_type),
                  allow_copy,
              )
          else:
              raise TypeError(
                  "This operation must copy data from CPU to GPU. "
                  "Set `allow_copy=True` to allow it."
              )
      return buf
  
imports: import enum
  from collections import abc
  from typing import Any, Dict, Iterable, Mapping, Optional, Sequence, Tuple, cast
  import cupy
  import numpy
  from numba.cuda import as_cuda_array
  import rmm
  import cudf
  from cudf.core.buffer import Buffer, as_buffer
  from cudf.core.column import as_column, build_categorical_column, build_column
label_desc: Use image node_id 4 for calling a global function with example usage: _ensure_gpu_buffer(buf, data_type, allow_copy) and returns: buf, _CuDFBuffer