code: def test_resample_stratify_sparse_error(csr_container):
      # resample must be ndarray
      rng = np.random.RandomState(0)
      n_samples = 100
      X = rng.normal(size=(n_samples, 2))
      y = rng.randint(0, 2, size=n_samples)
      stratify = csr_container(y.reshape(-1, 1))
      with pytest.raises(TypeError, match="Sparse data was passed"):
          X, y = resample(
              X, y, n_samples=50, random_state=rng, stratify=stratify
          )
  
imports: import string
  import timeit
  import warnings
  from copy import copy
  from itertools import chain
  import numpy
  import pytest
  from sklearn import config_context
  from sklearn.utils import _approximate_mode, _determine_key_type, _get_column_indices, _is_polars_df, _message_with_time, _print_elapsed_time, _safe_assign, _safe_indexing, _to_object_array, check_random_state, column_or_1d, deprecated, gen_even_slices, get_chunk_n_rows, is_scalar_nan, resample, safe_mask, shuffle
  from sklearn.utils._mocking import MockDataFrame
  from sklearn.utils._testing import _convert_container, assert_allclose_dense_sparse, assert_array_equal, assert_no_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 7 for calling a global function with example usage: test_resample_stratify_sparse_error(csr_container) without return types