code: def test_sqeuclidean_row_norms(
      global_random_seed,
      dtype,
      csr_container,
  ):
      rng = np.random.RandomState(global_random_seed)
      spread = 100
      n_samples = rng.choice([97, 100, 101, 1000])
      n_features = rng.choice([5, 10, 100])
      num_threads = rng.choice([1, 2, 8])
      X = rng.rand(n_samples, n_features).astype(dtype) * spread
  
      X_csr = csr_container(X)
  
      sq_row_norm_reference = np.linalg.norm(X, axis=1) ** 2
      sq_row_norm = sqeuclidean_row_norms(X, num_threads=num_threads)
  
      sq_row_norm_csr = sqeuclidean_row_norms(
          X_csr, num_threads=num_threads
      )
  
      assert_allclose(sq_row_norm_reference, sq_row_norm)
      assert_allclose(sq_row_norm_reference, sq_row_norm_csr)
  
      with pytest.raises(ValueError):
          X = np.asfortranarray(X)
          sqeuclidean_row_norms(X, num_threads=num_threads)
  
imports: import itertools
  import re
  import warnings
  from functools import partial
  import numpy
  import pytest
  import threadpoolctl
  from scipy.spatial.distance import cdist
  from sklearn.metrics import euclidean_distances, pairwise_distances
  from sklearn.metrics._pairwise_distances_reduction import ArgKmin, ArgKminClassMode, BaseDistancesReductionDispatcher, RadiusNeighbors, RadiusNeighborsClassMode, sqeuclidean_row_norms
  from sklearn.utils._testing import assert_allclose, assert_array_equal, create_memmap_backed_data
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 21 for calling a global function with example usage: test_sqeuclidean_row_norms(global_random_seed, dtype, csr_container) without return types