code: def test_attibutes_shapes(Est):
      # Make sure attributes are of the correct shape depending on n_components
      d = load_linnerud()
      X = d.data
      Y = d.target
      n_components = 2
      pls = Est(n_components=n_components)
      pls.fit(X, Y)
      assert all(
          attr.shape[1] == n_components
          for attr in (pls.x_weights_, pls.y_weights_)
      )
  
imports: import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.cross_decomposition import CCA, PLSSVD, PLSCanonical, PLSRegression
  from sklearn.cross_decomposition._pls import _center_scale_xy, _get_first_singular_vectors_power_method, _get_first_singular_vectors_svd, _svd_flip_1d
  from sklearn.datasets import load_linnerud, make_regression
  from sklearn.ensemble import VotingRegressor
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.utils import check_random_state
  from sklearn.utils.extmath import svd_flip
label_desc: Use image node_id 8 for calling a global function with example usage: test_attibutes_shapes(Est) without return types