code: def test_sklearn_linear_model_raises_wrong_type(self):
      warnings.filterwarnings("ignore")
      np.random.seed(0)
      X = np.random.rand(100, 200)
      X = np.array(X, dtype=np.float32)
      y = np.random.randint(3, size=100).astype(
          np.float32
      )  # y must be int, not float, should error
      model = SGDClassifier().fit(X, y)
      self.assertRaises(
          RuntimeError, hummingbird.ml.convert, model, "torch"
      )
  
imports: import unittest
  import warnings
  from packaging.version import Version, parse
  import numpy
  import torch
  from sklearn.linear_model import LinearRegression, LogisticRegression, SGDClassifier, LogisticRegressionCV, RidgeCV, Lasso, ElasticNet, Ridge, TweedieRegressor, PoissonRegressor, GammaRegressor
  from sklearn import datasets
  import hummingbird.ml
  from hummingbird.ml._utils import tvm_installed, pandas_installed
  from hummingbird.ml import constants
label_desc: Use image node_id 46 for calling the TestSklearnLinearClassifiers obj's underlying member method code with example usage: obj.test_sklearn_linear_model_raises_wrong_type() without return types