code: def tile(cls, op: "StatsModelsTrain"):
      if op.factor is not None:
          ctx = get_context()
          cluster_cpu_count = ctx.get_total_n_cpu()
          assert cluster_cpu_count > 0
          num_partitions = int(cluster_cpu_count * op.factor)
      else:
          num_partitions = op.num_partitions
  
      if has_unknown_shape(op.exog, op.endog):
          yield
  
      exog = op.exog
      if exog.ndim > 1 and exog.chunk_shape[1] > 1:
          exog = exog.rechunk({1: exog.shape[1]})
      exog = yield from recursive_tile(
          exog.rebalance(num_partitions=num_partitions)
      )
      endog = yield from recursive_tile(
          op.endog.rebalance(num_partitions=num_partitions)
      )
  
      assert len(exog.chunks) == len(endog.chunks)
  
      # generate map stage
      map_chunks = []
      for part_id, (exog_chunk, endog_chunk) in enumerate(
          zip(exog.chunks, endog.chunks)
      ):
          new_op = op.copy().reset_key()
          new_op._factor = None
          new_op._partition_id = part_id
          new_op._num_partitions = num_partitions
          new_op.stage = OperandStage.map
  
          map_chunks.append(
              new_op.new_chunk(
                  [exog_chunk, endog_chunk], index=exog_chunk.index
              )
          )
  
      # generate combine (join) stage
      new_op = op.copy().reset_key()
      new_op._factor = None
      new_op._num_partitions = num_partitions
      new_op.stage = OperandStage.combine
  
      combine_chunk = new_op.new_chunk(map_chunks, index=(0,))
  
      # generate tileable
      new_op = op.copy().reset_key()
      return new_op.new_tileables(op.inputs, chunks=[combine_chunk])
  
imports: import pickle
  import cloudpickle
  from ....None import opcodes
  from ....core import OutputType, recursive_tile
  from ....core.context import get_context
  from ....core.operand import OperandStage, MergeDictOperand
  from ....serialization.serializables import KeyField, BytesField, DictField, Int32Field, Float32Field, FunctionField
  from ....utils import has_unknown_shape
label_desc: Use image node_id 18 for calling the StatsModelsTrain obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op