code: def tile(cls, op):
      if has_unknown_shape(*op.inputs):
          yield
  
      out = op.outputs[0]
      chunk_size = out.extra_params.raw_chunk_size or options.chunk_size
      nsplits = decide_chunk_sizes(
          out.shape, chunk_size, out.dtype.itemsize
      )
      inputs = op.inputs
  
      a, p = op.a, op.p
      if p is not None:
          # we cannot handle p in a parallel fashion
          inputs = []
          if isinstance(a, TENSOR_TYPE):
              a = yield from recursive_tile(a.rechunk(a.shape))
              inputs.append(a)
          p = yield from recursive_tile(p.rechunk(p.shape))
          inputs.append(p)
  
          # ignore nsplits if p is specified
          nsplits = ((s,) for s in out.shape)
  
      # all inputs and outputs has 1 chunk
      if all(len(inp.chunks) == 1 for inp in inputs) and all(
          len(ns) == 1 for ns in nsplits
      ):
          return cls._tile_one_chunk(op, a, p)
  
      if op.replace:
          return (
              yield from cls._tile_sample_with_replacement(
                  op, a, nsplits
              )
          )
      else:
          return (
              yield from cls._tile_sample_without_replacement(
                  op, a, nsplits
              )
          )
  
imports: from numbers import Integral
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import recursive_tile
  from ...serialization.serializables import FieldTypes, AnyField, KeyField, BoolField, TupleField
  from ...utils import has_unknown_shape, ceildiv
  from ..operands import TensorOperandMixin
  from ..core import TENSOR_TYPE, TENSOR_CHUNK_TYPE, TensorOrder
  from ..datasource import arange, array
  from ..utils import decide_chunk_sizes, normalize_chunk_sizes, gen_random_seeds
  from ..array_utils import as_same_device, device
  from .core import TensorRandomOperand, RandomState
label_desc: Use image node_id 6 for calling the TensorChoice obj's underlying member method code with example usage: obj.tile(cls, op) and returns: cls, unknown, unknown