code: def tile(cls, op):
      ctx = get_context()
  
      workers = pick_workers(ctx.get_worker_addresses(), op.world_size)
      data, input_chunks = cls._get_chunk_data(op)
  
      out_chunks = []
      for i in range(op.world_size):
          chunk_op = op.copy().reset_key()
          chunk_op._data = data
          chunk_op.expect_worker = workers[i]
          if op.init_method is None:
              chunk_op._master_port = op.master_port
              chunk_op._master_addr = workers[0].split(":", 1)[0]
          chunk_op._rank = i
          chunk_op._init_method = op.init_method
          out_chunks.append(
              chunk_op.new_chunk(input_chunks, index=(i,))
          )
  
      new_op = op.copy()
      return new_op.new_tileables(
          op.inputs,
          chunks=out_chunks,
          nsplits=(tuple(np.nan for _ in range(len(out_chunks))),),
      )
  
imports: import os
  from typing import Any, BinaryIO, Dict, List, Optional, TextIO, Union
  import numpy
  from ....None import opcodes
  from ....core.context import get_context
  from ....remote.run_script import RunScript, _extract_inputs
  from ....serialization.serializables import Int32Field, StringField
  from ....typing import SessionType, TileableType
  from ....utils import to_binary
  from ..utils import pick_workers
label_desc: Use image node_id 5 for calling the RunPyTorch obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op