code: def _take_nd_object(arr, indexer, out, axis, fill_value, mask_info):
      if mask_info is not None:
          mask, needs_masking = mask_info
      else:
          mask = indexer == -1
          needs_masking = mask.any()
      if arr.dtype != out.dtype:
          arr = arr.astype(out.dtype)
      if arr.shape[axis] > 0:
          arr.take(ensure_platform_int(indexer), axis=axis, out=out)
      if needs_masking:
          outindexer = [slice(None)] * arr.ndim
          outindexer[axis] = mask
          out[tuple(outindexer)] = fill_value
  
imports: from __future__ import division
  from textwrap import dedent
  from warnings import catch_warnings, simplefilter, warn
  import numpy
  from pandas._libs import algos, hashtable, lib
  from pandas._libs.tslib import iNaT
  from pandas.util._decorators import Appender, Substitution, deprecate_kwarg
  from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike, maybe_promote
  from pandas.core.dtypes.common import ensure_float64, ensure_int64, ensure_object, ensure_platform_int, ensure_uint64, is_array_like, is_bool_dtype, is_categorical_dtype, is_complex_dtype, is_datetime64_any_dtype, is_datetime64tz_dtype, is_datetimelike, is_extension_array_dtype, is_float_dtype, is_integer_dtype, is_interval_dtype, is_list_like, is_numeric_dtype, is_object_dtype, is_period_dtype, is_scalar, is_signed_integer_dtype, is_sparse, is_timedelta64_dtype, is_unsigned_integer_dtype, needs_i8_conversion
  from pandas.core.dtypes.generic import ABCIndex, ABCIndexClass, ABCSeries
  from pandas.core.dtypes.missing import isna, na_value_for_dtype
  from pandas.core import common
label_desc: Use image node_id 21 for calling a global function with example usage: _take_nd_object(arr, indexer, out, axis, fill_value, mask_info) without return types