code: def test_split_at_indices_coverage_complete(
      ray_start_regular_shared,
      num_blocks,
      indices,
  ):
      # Test that split_at_indices() creates the expected splits on a set of partition and
      # indices configurations.
      ds = ray.data.range(5, parallelism=num_blocks)
      splits = ds.split_at_indices(indices)
      r = [extract_values("id", s.take_all()) for s in splits]
      # Use np.array_split() semantics as our correctness ground-truth.
      assert r == [
          arr.tolist()
          for arr in np.array_split(list(range(5)), indices)
      ]
  
imports: import itertools
  import math
  import random
  import time
  from unittest.mock import patch
  import numpy
  import pandas
  import pytest
  import ray
  from ray.data._internal.block_list import BlockList
  from ray.data._internal.equalize import _equalize
  from ray.data._internal.execution.interfaces import RefBundle
  from ray.data._internal.logical.interfaces import LogicalPlan
  from ray.data._internal.logical.operators.input_data_operator import InputData
  from ray.data._internal.plan import ExecutionPlan
  from ray.data._internal.split import _drop_empty_block_split, _generate_global_split_results, _generate_per_block_split_indices, _generate_valid_indices, _split_at_indices, _split_single_block
  from ray.data._internal.stats import DatasetStats
  from ray.data.block import BlockAccessor, BlockMetadata
  from ray.data.dataset import Dataset
  from ray.data.tests.conftest import *
  from ray.data.tests.util import extract_values
  from ray.tests.conftest import *
label_desc: Use image node_id 8 for calling a global function with example usage: test_split_at_indices_coverage_complete(ray_start_regular_shared, num_blocks, indices) without return types