code: def _tile_one_chunk(cls, op: "TensorIndex"):
      inp = op.inputs[0]
      out = op.outputs[0]
      chunk_op = op.copy().reset_key()
      chunk_params = out.params.copy()
      chunk_params["shape"] = shape = tuple(
          calc_shape(inp.shape, op.indexes)
      )
      chunk_params["index"] = (0,) * out.ndim
      chunk = chunk_op.new_chunk(
          [inp.chunks[0] for inp in op.inputs], kws=[chunk_params]
      )
      params = out.params.copy()
      params["chunks"] = [chunk]
      params["nsplits"] = tuple((s,) for s in shape)
      return op.copy().new_tensors(op.inputs, kws=[params])
  
imports: from numbers import Integral
  import numpy
  from ...None import opcodes
  from ...core import ENTITY_TYPE
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, ListField, TupleField, Int32Field
  from ..core import TENSOR_TYPE, TensorOrder
  from ..utils import split_indexes_into_chunks, calc_pos, filter_inputs
  from ..operands import TensorHasInput, TensorOperandMixin, TensorMapReduceOperand
  from ..array_utils import get_array_module
  from .core import process_index, calc_shape
  from .index_lib import TensorIndexesHandler
label_desc: Use image node_id 7 for calling the TensorIndex obj's underlying member method code with example usage: obj._tile_one_chunk(cls, op) and returns: op