code: def to_ndarray(
      self, mode: "_modes.Mode", dtype: numpy.dtype
  ) -> ndarray:
      with self.device:
          if mode is _modes.REPLICA:
              data = _creation_basic.empty(self.shape, dtype)
          else:
              value = mode.identity_of(dtype)
              data = _creation_basic.full(self.shape, value, dtype)
  
          # We avoid 0D array because we expect data[idx] to return a view
          return _manipulation_dims.atleast_1d(data)
  
imports: import contextlib
  from itertools import chain
  from typing import Any, Iterator, Optional, Union
  import numpy
  from cupy._core.core import ndarray
  import cupy._creation.basic
  import cupy._manipulation.dims
  from cupy.cuda.device import Device
  from cupy.cuda.stream import Event
  from cupy.cuda.stream import Stream
  from cupy.cuda.stream import get_current_stream
  from cupyx.distributed.array import _modes
  from cupyx.distributed.array import _index_arith
  from cupyx.distributed.array import _data_transfer
  from cupyx.distributed.array._data_transfer import _Communicator
label_desc: Use image node_id 3 for calling the _ArrayPlaceholder obj's underlying member method code with example usage: obj.to_ndarray(mode, dtype) and returns: _manipulation_dims