code: def test_random_yield(
      iterables, probabilities, sample_size, samples, random_state
  ):
      it = iter(
          RandomYield(
              iterables, probabilities, random_state=random_state
          )
      )
      generated_samples = list(take(sample_size, it))
      assert generated_samples == samples
  
imports: import itertools
  import pickle
  import tempfile
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Iterable, List, Tuple
  import numpy
  from numpy.testing import assert_equal
  from toolz import take
  import pytest
  from gluonts.dataset.artificial import constant_dataset
  from gluonts.itertools import batcher, Cached, Chain, PickleCached, Cyclic, IterableSlice, SizedIterableSlice, PseudoShuffled, rows_to_columns, columns_to_rows, select, pluck_attr, power_set, Map, StarMap, Filter, join_items, RandomYield
label_desc: Use image node_id 16 for calling a global function with example usage: test_random_yield(iterables, probabilities, sample_size, samples, random_state) without return types