code: def _tile_one_chunk(cls, op, y, x):
      out = op.outputs[0]
      chunk_op = op.copy().reset_key()
      inputs = [y.chunks[0]]
      if x is not None:
          inputs.append(x.chunks[0])
      chunk = chunk_op.new_chunk(
          inputs,
          shape=out.shape,
          order=out.order,
          index=(0,) * out.ndim,
      )
  
      new_op = op.copy()
      return new_op.new_tensors(
          op.inputs,
          shape=out.shape,
          order=out.order,
          nsplits=tuple((s,) for s in out.shape),
          chunks=[chunk],
      )
  
imports: import numpy
  from ...None import opcodes
  from ...core import recursive_tile
  from ...serialization.serializables import KeyField, Float64Field, Int8Field
  from ...utils import has_unknown_shape
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..datasource import tensor
  from ..operands import TensorOperand, TensorOperandMixin
  from ..utils import validate_axis
label_desc: Use image node_id 9 for calling the TensorTrapz obj's underlying member method code with example usage: obj._tile_one_chunk(cls, op, y, x) and returns: new_op