code: def check_size_generated(random_matrix):
      inputs = [(1, 5), (5, 1), (5, 5), (1, 1)]
      for n_components, n_features in inputs:
          assert random_matrix(n_components, n_features).shape == (
              n_components,
              n_features,
          )
  
imports: import functools
  import warnings
  from typing import Any, List
  import numpy
  import pytest
  import scipy.sparse
  from sklearn.exceptions import DataDimensionalityWarning, NotFittedError
  from sklearn.metrics import euclidean_distances
  from sklearn.random_projection import GaussianRandomProjection, SparseRandomProjection, _gaussian_random_matrix, _sparse_random_matrix, johnson_lindenstrauss_min_dim
  from sklearn.utils._testing import assert_allclose, assert_allclose_dense_sparse, assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import COO_CONTAINERS
label_desc: Use image node_id 6 for calling a global function with example usage: check_size_generated(random_matrix) without return types