code: def _tile_one_chunk(cls, op):
      outs = op.outputs
      ins = op.inputs
  
      chunk_op = op.copy().reset_key()
      in_chunk = ins[0].chunks[0]
      kws = cls._gen_kws(chunk_op, in_chunk, chunk=True)
      out_chunks = chunk_op.new_chunks(
          [in_chunk], kws=kws, order=outs[0].order
      )
      new_op = op.copy()
      kws = [out.params.copy() for out in outs]
      for kw, out_chunk in zip(kws, out_chunks):
          kw["chunks"] = [out_chunk]
          kw["nsplits"] = tuple((s,) for s in out_chunk.shape)
      return new_op.new_tensors(ins, kws=kws, order=outs[0].order)
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import recursive_tile
  from ...core.operand import OperandStage
  from ...lib import sparse
  from ...lib.sparse.core import get_array_module
  from ...serialization.serializables import BoolField, Int32Field, Int64Field
  from ...utils import has_unknown_shape
  from ..operands import TensorMapReduceOperand, TensorOperandMixin, TensorShuffleProxy
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..utils import validate_axis, hash_on_axis
label_desc: Use image node_id 11 for calling the TensorUnique obj's underlying member method code with example usage: obj._tile_one_chunk(cls, op) and returns: new_op