code: def meta_nonempty_cudf(x):
      idx = meta_nonempty(x.index)
      columns_with_dtype = dict()
      res = cudf.DataFrame(index=idx)
      for col in x._data.names:
          dtype = str(x._data[col].dtype)
          if dtype in ("list", "struct", "category"):
              # 1. Not possible to hash and store list & struct types
              #    as they can contain different levels of nesting or
              #    fields.
              # 2. Not possible to has `category` types as
              #    they often contain an underlying types to them.
              res._data[col] = _get_non_empty_data(x._data[col])
          else:
              if dtype not in columns_with_dtype:
                  columns_with_dtype[
                      dtype
                  ] = cudf.core.column.as_column(
                      _get_non_empty_data(x._data[col])
                  )
              res._data[col] = columns_with_dtype[dtype]
  
      return res
  
imports: import warnings
  from collections.abc import Iterator
  import cupy
  import numpy
  import pandas
  import pyarrow
  from pandas.api.types import is_scalar
  from pandas.core.tools.datetimes import is_datetime64tz_dtype
  import dask.dataframe
  from dask import config
  from dask.array.dispatch import percentile_lookup
  from dask.dataframe.backends import DataFrameBackendEntrypoint, PandasBackendEntrypoint
  from dask.dataframe.core import get_parallel_type, meta_nonempty
  from dask.dataframe.dispatch import categorical_dtype_dispatch, concat_dispatch, from_pyarrow_table_dispatch, group_split_dispatch, grouper_dispatch, hash_object_dispatch, is_categorical_dtype_dispatch, make_meta_dispatch, pyarrow_schema_dispatch, to_pyarrow_table_dispatch, tolist_dispatch, union_categoricals_dispatch
  from dask.dataframe.utils import UNKNOWN_CATEGORIES, _nonempty_scalar, _scalar_from_dtype, make_meta_obj
  from dask.sizeof import sizeof
  from dask.utils import Dispatch, is_arraylike
  import cudf
  from cudf.api.types import is_string_dtype
  from cudf.utils.nvtx_annotation import _dask_cudf_nvtx_annotate
  from .core import DataFrame, Index, Series
label_desc: Use image node_id 5 for calling a global function with example usage: meta_nonempty_cudf(x) and returns: res