code: def test_split_operator_random(
      ray_start_regular_shared, equal, random_seed
  ):
      random.seed(random_seed)
      inputs = make_ref_bundles(
          [[i] * random.randint(0, 10) for i in range(100)]
      )
      num_inputs = sum(x.num_rows() for x in inputs)
      input_op = InputDataBuffer(inputs)
      op = OutputSplitter(input_op, 3, equal=equal)
  
      # Feed data and implement streaming exec.
      output_splits = collections.defaultdict(list)
      op.start(ExecutionOptions())
      while input_op.has_next():
          op.add_input(input_op.get_next(), 0)
      op.all_inputs_done()
      while op.has_next():
          ref = op.get_next()
          assert ref.owns_blocks, ref
          for block, _ in ref.blocks:
              output_splits[ref.output_split_idx].extend(
                  list(ray.get(block)["id"])
              )
      if equal:
          actual = [len(output_splits[i]) for i in range(3)]
          expected = [num_inputs // 3] * 3
          assert actual == expected
      else:
          assert (
              sum(len(output_splits[i]) for i in range(3)) == num_inputs
          ), output_splits
  
imports: import collections
  import random
  import time
  from typing import Any, Iterable, List
  from unittest.mock import MagicMock
  import numpy
  import pandas
  import pytest
  import ray
  from ray._private.test_utils import wait_for_condition
  from ray.data._internal.compute import ActorPoolStrategy, TaskPoolStrategy
  from ray.data._internal.execution.interfaces import ExecutionOptions, PhysicalOperator, RefBundle
  from ray.data._internal.execution.operators.actor_pool_map_operator import ActorPoolMapOperator
  from ray.data._internal.execution.operators.base_physical_operator import AllToAllOperator
  from ray.data._internal.execution.operators.input_data_buffer import InputDataBuffer
  from ray.data._internal.execution.operators.limit_operator import LimitOperator
  from ray.data._internal.execution.operators.map_operator import MapOperator, _BlockRefBundler
  from ray.data._internal.execution.operators.map_transformer import create_map_transformer_from_block_fn
  from ray.data._internal.execution.operators.output_splitter import OutputSplitter
  from ray.data._internal.execution.operators.task_pool_map_operator import TaskPoolMapOperator
  from ray.data._internal.execution.operators.union_operator import UnionOperator
  from ray.data._internal.execution.util import make_ref_bundles
  from ray.data.block import Block
  from ray.data.context import DataContext
  from ray.data.tests.util import run_one_op_task, run_op_tasks_sync
  from ray.tests.conftest import *
label_desc: Use image node_id 10 for calling a global function with example usage: test_split_operator_random(ray_start_regular_shared, equal, random_seed) without return types