code: def tile(cls, op: "LGBMTrain"):
      ctx = get_context()
      data = op.data
      worker_to_args = defaultdict(dict)
  
      # Note: Mars worker is band address, and LGBMTrain worker is machine ip.
      ips, ip_to_worker = cls._get_data_chunks_workers(ctx, data)
  
      for arg in ["_data", "_label", "_sample_weight", "_init_score"]:
          if getattr(op, arg) is not None:
              for worker, chunk in cls._concat_chunks_by_worker(
                  getattr(op, arg).chunks, ips
              ).items():
                  worker_to_args[worker][arg] = chunk
  
      if op.eval_datas:
          eval_workers_list = [
              cls._get_data_chunks_workers(ctx, d)[0]
              for d in op.eval_datas
          ]
          extra_workers = reduce(
              operator.or_, (set(w) for w in eval_workers_list)
          ) - set(ips)
          worker_remap = dict(zip(extra_workers, itertools.cycle(ips)))
          if worker_remap:
              eval_workers_list = [
                  [worker_remap.get(w, w) for w in wl]
                  for wl in eval_workers_list
              ]
  
          for arg in [
              "_eval_datas",
              "_eval_labels",
              "_eval_sample_weights",
              "_eval_init_scores",
          ]:
              if getattr(op, arg):
                  for tileable, eval_workers in zip(
                      getattr(op, arg), eval_workers_list
                  ):
                      for worker, chunk in cls._concat_chunks_by_worker(
                          tileable.chunks, eval_workers
                      ).items():
                          if arg not in worker_to_args[worker]:
                              worker_to_args[worker][arg] = []
                          worker_to_args[worker][arg].append(chunk)
  
      out_chunks = []
      ips = list(set(ips))
      workers = list(ip_to_worker.values())
      for worker_id, worker in enumerate(ips):
          chunk_op = op.copy().reset_key()
          chunk_op.expect_worker = ip_to_worker[worker]
  
          input_chunks = []
          concat_args = worker_to_args.get(worker, {})
          for arg in [
              "_data",
              "_label",
              "_sample_weight",
              "_init_score",
              "_eval_datas",
              "_eval_labels",
              "_eval_sample_weights",
              "_eval_init_scores",
          ]:
              arg_val = getattr(op, arg)
              if arg_val:
                  arg_chunk = concat_args.get(arg)
                  setattr(chunk_op, arg, arg_chunk)
                  if isinstance(arg_chunk, list):
                      input_chunks.extend(arg_chunk)
                  else:
                      input_chunks.append(arg_chunk)
  
          worker_ports_chunk = (
              yield from recursive_tile(collect_ports(workers, op.data))
          ).chunks[0]
          input_chunks.append(worker_ports_chunk)
  
          chunk_op._workers = ips
          chunk_op._worker_ports = worker_ports_chunk
          chunk_op._worker_id = worker_id
  
          data_chunk = concat_args["_data"]
          out_chunk = chunk_op.new_chunk(
              input_chunks, shape=(np.nan,), index=data_chunk.index[:1]
          )
          out_chunks.append(out_chunk)
  
      new_op = op.copy()
      return new_op.new_tileables(
          op.inputs,
          chunks=out_chunks,
          nsplits=((np.nan for _ in out_chunks),),
      )
  
imports: import itertools
  import logging
  import operator
  import pickle
  from collections import defaultdict
  from functools import reduce
  import numpy
  from ....None import opcodes
  from ....core import ExecutableTuple, OutputType, recursive_tile
  from ....core.context import get_context
  from ....core.operand import MergeDictOperand
  from ....serialization.serializables import FieldTypes, DictField, Int32Field, KeyField, ListField, StringField
  from ...utils import concat_chunks, collect_ports
  from ._align import align_data_set
  from .core import LGBMModelType, get_model_cls_from_type
label_desc: Use image node_id 22 for calling the LGBMTrain obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op