code: def test_csr_get_row(test_data):
      X = test_data["X"]
      csr_ds = test_data["dataset_csr"]
      for i in range(X.shape[0]):
          indices, data, n_nz = csr_ds.get_row(i)
          for jj in range(n_nz):
              j = indices[jj]
              assert X[i, j] == data[jj]
  
file_path: lightning/lightning/impl/tests/test_dataset.py
imports: import pickle
  import numpy
  import pytest
  import scipy.sparse
  from sklearn.datasets import make_classification
  from sklearn.utils import check_random_state
  from lightning.impl.dataset_fast import ContiguousDataset
  from lightning.impl.dataset_fast import FortranDataset
  from lightning.impl.dataset_fast import CSRDataset
  from lightning.impl.dataset_fast import CSCDataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_csr_get_row(test_data) without return types