code: def test_bootstrap_resample(rng_name):
      rng = getattr(np.random, rng_name, None)
      if rng is None:
          pytest.skip(f"{rng_name} not available.")
      rng1 = rng(0)
      rng2 = rng(0)
  
      n_resamples = 10
      shape = 3, 4, 5, 6
  
      np.random.seed(0)
      x = np.random.rand(*shape)
      y = _bootstrap._bootstrap_resample(
          x, n_resamples, random_state=rng1
      )
  
      for i in range(n_resamples):
          # each resample is indexed along second to last axis
          # (last axis is the one the statistic will be taken over / consumed)
          slc = y[..., i, :]
  
          js = rng_integers(rng2, 0, shape[-1], shape[-1])
          expected = x[..., js]
  
          assert np.array_equal(slc, expected)
  
imports: import numpy
  import pytest
  from scipy.stats import bootstrap
  from numpy.testing import assert_allclose, assert_equal
  from scipy import stats
  from scipy.stats import _bootstrap
  from scipy._lib._util import rng_integers
label_desc: Use image node_id 12 for calling a global function with example usage: test_bootstrap_resample(rng_name) without return types