code: def _tile_as_shuffle(op):
      in_tensor = op.input
      tensor = op.outputs[0]
      new_shape = op.newshape
      shuffle_inputs, shuffle_outputs = [], []
      axis_offsets = [
          [0] + np.cumsum(ns)[:-1].tolist() for ns in in_tensor.nsplits
      ]
  
      max_chunk_size = max(max(tp) for tp in in_tensor.nsplits)
      out_nsplits = decide_chunk_sizes(
          new_shape, max_chunk_size, tensor.dtype.itemsize
      )
      chunk_size_idxes = (range(len(size)) for size in out_nsplits)
  
      for inp in in_tensor.chunks:
          offset = tuple(
              axis_offsets[axis][idx]
              for axis, idx in enumerate(inp.index)
          )
          chunk_op = TensorReshape(
              stage=OperandStage.map,
              axis_offsets=offset,
              oldshape=in_tensor.shape,
              newshape=new_shape,
              new_chunk_size=(max_chunk_size,) * len(new_shape),
              dtype=inp.dtype,
          )
          shuffle_inputs.append(
              chunk_op.new_chunk(
                  [inp], shape=(np.nan,), index=inp.index
              )
          )
  
      proxy_chunk = TensorShuffleProxy(
          dtype=in_tensor.dtype, _tensor_keys=[in_tensor.op.key]
      ).new_chunk(shuffle_inputs, shape=())
  
      out_indices = list(
          zip(
              itertools.product(*out_nsplits),
              itertools.product(*chunk_size_idxes),
          )
      )
      for chunk_shape, chunk_idx in out_indices:
          chunk_op = TensorReshape(
              stage=OperandStage.reduce,
              dtype=tensor.dtype,
              n_reducers=len(out_indices),
          )
          shuffle_outputs.append(
              chunk_op.new_chunk(
                  [proxy_chunk],
                  shape=chunk_shape,
                  order=tensor.order,
                  index=chunk_idx,
              )
          )
  
      new_op = op.copy()
      return new_op.new_tensors(
          op.inputs,
          new_shape,
          order=tensor.order,
          chunks=shuffle_outputs,
          nsplits=out_nsplits,
      )
  
imports: import itertools
  import logging
  import numpy
  from ...None import opcodes
  from ...core import recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, TupleField, StringField
  from ...utils import has_unknown_shape
  from ..array_utils import as_same_device, device
  from ..datasource import tensor
  from ..operands import TensorOperandMixin, TensorMapReduceOperand, TensorShuffleProxy
  from ..utils import get_order, decide_chunk_sizes
label_desc: Use image node_id 15 for calling the TensorReshape obj's underlying member method code with example usage: obj._tile_as_shuffle(op) and returns: new_op