code: def generate_input(self):
      if self._regression:
          (
              dtypes_meta,
              num_rows,
              num_cols,
              seed,
          ) = self.get_next_regression_params()
      else:
          dtypes_list = list(
              cudf.utils.dtypes.ALL_TYPES
              # TODO: Remove "bool" from below
              # list after following issue is fixed:
              # https://github.com/rapidsai/cudf/issues/6763
              - {"category", "bool"}
              # Following dtypes are not supported by orc
              # https://orc.apache.org/specification/ORCv0/
              - cudf.utils.dtypes.TIMEDELTA_TYPES
              - cudf.utils.dtypes.UNSIGNED_TYPES
              # TODO: Remove `DATETIME_TYPES` once
              # following bug is fixed:
              # https://github.com/rapidsai/cudf/issues/7355
              - cudf.utils.dtypes.DATETIME_TYPES
          )
  
          dtypes_meta, num_rows, num_cols = _generate_rand_meta(
              self, dtypes_list
          )
          self._current_params["dtypes_meta"] = dtypes_meta
          seed = random.randint(0, 2**32 - 1)
          self._current_params["seed"] = seed
          self._current_params["num_rows"] = num_rows
          self._current_params["num_cols"] = num_cols
      logging.info(
          f"Generating DataFrame with rows: {num_rows} "
          f"and columns: {num_cols}"
      )
      table = dg.rand_dataframe(dtypes_meta, num_rows, seed)
      df = pyarrow_to_pandas(table)
      logging.info(f"Shape of DataFrame generated: {table.shape}")
      self._df = df
      return df
  
imports: import copy
  import io
  import logging
  import random
  import numpy
  import pyarrow
  import cudf
  from cudf._fuzz_testing.io import IOFuzz
  from cudf._fuzz_testing.utils import ALL_POSSIBLE_VALUES, _generate_rand_meta, pyarrow_to_pandas
  from cudf.testing import dataset_generator
label_desc: Use image node_id 2 for calling the OrcWriter obj's underlying member method code with example usage: obj.generate_input() and returns: df