code: def tile(cls, op):
      clean_up_func(op)
      in_groupby = op.inputs[0]
      out_df = op.outputs[0]
  
      chunks = []
      for c in in_groupby.chunks:
          inp_chunks = [c]
  
          new_op = op.copy().reset_key()
          new_op.tileable_op_key = op.key
          if op.output_types[0] == OutputType.df_or_series:
              chunks.append(
                  new_op.new_chunk(
                      inp_chunks, index=c.index, collapse_axis=1
                  )
              )
          elif op.output_types[0] == OutputType.dataframe:
              chunks.append(
                  new_op.new_chunk(
                      inp_chunks,
                      index=c.index,
                      shape=(np.nan, len(out_df.dtypes)),
                      dtypes=out_df.dtypes,
                      columns_value=out_df.columns_value,
                      index_value=out_df.index_value,
                  )
              )
          else:
              chunks.append(
                  new_op.new_chunk(
                      inp_chunks,
                      name=out_df.name,
                      index=(c.index[0],),
                      shape=(np.nan,),
                      dtype=out_df.dtype,
                      index_value=out_df.index_value,
                  )
              )
  
      new_op = op.copy()
      kw = out_df.params.copy()
      kw["chunks"] = chunks
      if op.output_types[0] == OutputType.dataframe:
          kw["nsplits"] = ((np.nan,) * len(chunks), (out_df.shape[1],))
      else:
          kw["nsplits"] = ((np.nan,) * len(chunks),)
      ret = new_op.new_tileable([in_groupby], **kw)
      if not op.maybe_agg:
          return [ret]
      else:
          # auto merge small chunks if df.groupby().apply(func)
          # may be an aggregation operation
          yield ret.chunks  # trigger execution for chunks
          return [auto_merge_chunks(get_context(), ret)]
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import OutputType
  from ...core.context import get_context
  from ...core.custom_log import redirect_custom_log
  from ...serialization.serializables import AnyField, BoolField, TupleField, DictField, FunctionField, StringField
  from ...core.operand import OperatorLogicKeyGeneratorMixin
  from ...utils import enter_current_session, quiet_stdio, get_func_token, tokenize
  from ..operands import DataFrameOperandMixin, DataFrameOperand
  from ..utils import auto_merge_chunks, build_empty_df, build_empty_series, parse_index, validate_output_types, make_dtypes, make_dtype, clean_up_func, restore_func
label_desc: Use image node_id 4 for calling the GroupByApply obj's underlying member method code with example usage: obj.tile(cls, op) and returns: list, list