code: def tile(cls, op: "DuplicateOperand"):
      inp = op.input
  
      if len(inp.chunks) == 1:
          # one chunk
          return cls._tile_one_chunk(op)
  
      if inp.ndim == 2 and inp.chunk_shape[1] > 1:
          if has_unknown_shape(inp):
              yield
          inp = yield from recursive_tile(
              inp.rechunk({1: inp.shape[1]})
          )
  
      default_tile = cls._tile_tree
  
      if op.method == "auto":
          # if method == 'auto', pick appropriate method
          if np.isnan(inp.shape[0]) or op.subset is None:
              # if any unknown shape exist,
              # choose merge method
              return default_tile(op, inp)
  
          # check subset data to see if it's small enough
          subset_dtypes = inp.dtypes[op.subset]
          memory_usage = 0.0
          for s_dtype in subset_dtypes:
              if s_dtype.kind == "O" or not hasattr(
                  s_dtype, "itemsize"
              ):
                  # object, just use default tile
                  return default_tile(op, inp)
              else:
                  memory_usage += s_dtype.itemsize * inp.shape[0]
          if memory_usage <= options.chunk_store_limit:
              # if subset is small enough, use method 'subset_tree'
              r = yield from cls._tile_subset_tree(op, inp)
              return r
          else:
              return default_tile(op, inp)
      elif op.method == "subset_tree":
          r = yield from cls._tile_subset_tree(op, inp)
          return r
      elif op.method == "tree":
          return cls._tile_tree(op, inp)
      else:
          assert op.method == "shuffle"
          ret = cls._tile_shuffle(op, inp)
          if inspect.isgenerator(ret):
              return (yield from ret)
          else:
              return ret
  
imports: import inspect
  import numpy
  import pandas
  from pandas.api.types import is_list_like
  from ...config import options
  from ...core import OutputType, recursive_tile
  from ...core.operand import OperandStage, MapReduceOperand
  from ...serialization.serializables import AnyField, Int32Field, StringField, KeyField
  from ...utils import ceildiv, has_unknown_shape, lazy_import
  from ..initializer import DataFrame
  from ..operands import DataFrameOperandMixin, DataFrameShuffleProxy
label_desc: Use image node_id 18 for calling the DuplicateOperand obj's underlying member method code with example usage: obj.tile(cls, op) and returns: cls, default_tile, r, default_tile, r, default_tile, cls, unknown, ret