code: def _tile_one_chunk(cls, op, a, v, out):
      chunks = []
      if len(op.inputs) == 1:
          v_chunks = [v]
      else:
          v_chunks = v.chunks
      for v_chunk in v_chunks:
          chunk_op = op.copy().reset_key()
          in_chunks = [a.chunks[0]]
          if len(op.inputs) == 2:
              in_chunks.append(v_chunk)
          v_shape = v_chunk.shape if hasattr(v_chunk, "shape") else ()
          chunk_idx = v_chunk.index if len(op.inputs) == 2 else (0,)
          chunk = chunk_op.new_chunk(
              in_chunks, shape=v_shape, index=chunk_idx, order=out.order
          )
          chunks.append(chunk)
      new_op = op.copy().reset_key()
      nsplits = (
          ((s,) for s in out.shape)
          if len(op.inputs) == 1
          else v.nsplits
      )
      return new_op.new_tensors(
          op.inputs, out.shape, chunks=chunks, nsplits=nsplits
      )
  
imports: import itertools
  from typing import Any, List, Tuple, Type
  import numpy
  from ...None import opcodes
  from ...core import TILEABLE_TYPE
  from ...core.operand import OperandStage
  from ...serialization.serializables import StringField, AnyField, Int64Field, Int32Field
  from ...typing import TileableType, ChunkType
  from ...config import options
  from ...utils import has_unknown_shape
  from ..operands import TensorOperand, TensorOperandMixin
  from ..core import TENSOR_TYPE, TensorOrder
  from ..datasource.array import tensor
  from ..array_utils import as_same_device, device
label_desc: Use image node_id 3 for calling the TensorSearchsorted obj's underlying member method code with example usage: obj._tile_one_chunk(cls, op, a, v, out) and returns: new_op