code: def test_tweedie_regressor(self):
      clf = TweedieRegressor()
      X = [[1, 2], [2, 3], [3, 4], [4, 3]]
      y = [2, 3.5, 5, 5.5]
  
      clf.fit(X, y)
      hb_model = hummingbird.ml.convert(clf, "torch")
  
      np.testing.assert_allclose(
          clf.predict([[1, 1], [3, 4]]),
          hb_model.predict([[1, 1], [3, 4]]),
          rtol=1e-6,
          atol=1e-3,
      )
  
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 54 for calling the TestSklearnLinearClassifiers obj's underlying member method code with example usage: obj.test_tweedie_regressor() without return types