code: def test_regressor_correctness(loss, csr_container):
      y_bin = y.copy()
      y_bin[y != 1] = -1
  
      reg1 = MyPassiveAggressive(loss=loss, n_iter=2)
      reg1.fit(X, y_bin)
  
      data = csr_container(X) if csr_container is not None else X
      reg2 = PassiveAggressiveRegressor(
          tol=None, loss=loss, max_iter=2, shuffle=False
      )
      reg2.fit(data, y_bin)
  
      assert_array_almost_equal(reg1.w, reg2.coef_.ravel(), decimal=2)
  
imports: import numpy
  import pytest
  from sklearn.base import ClassifierMixin
  from sklearn.datasets import load_iris
  from sklearn.linear_model import PassiveAggressiveClassifier, PassiveAggressiveRegressor
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 12 for calling a global function with example usage: test_regressor_correctness(loss, csr_container) without return types