code: def test_fit_transform_tall():
      rng = np.random.RandomState(0)
      Y, _, _ = generate_toy_data(
          3, 65, (8, 8), random_state=rng
      )  # tall array
      spca_lars = SparsePCA(
          n_components=3, method="lars", random_state=rng
      )
      U1 = spca_lars.fit_transform(Y)
      spca_lasso = SparsePCA(
          n_components=3, method="cd", random_state=rng
      )
      U2 = spca_lasso.fit(Y).transform(Y)
      assert_array_almost_equal(U1, U2)
  
imports: import sys
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn.decomposition import PCA, MiniBatchSparsePCA, SparsePCA
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, if_safe_multiprocessing_with_blas
label_desc: Use image node_id 6 for calling a global function with example usage: test_fit_transform_tall() without return types