code: def test_interaction_Lambda0():
      data = h2o.import_file(
          pyunit_utils.locate("smalldata/census_income/adult_data.csv")
      )
      data["y"] = data["hours-per-week"] / data["age"]
  
      model_cust = H2OGeneralizedLinearEstimator(
          interactions=["income", "sex"],
          family="tweedie",
          tweedie_variance_power=1.7,
          tweedie_link_power=0,
          Lambda=0,
          intercept=True,
          compute_p_values=True,
          remove_collinear_columns=True,
          standardize=True,
          weights_column="age",
          solver="IRLSM",
      )
      model_cust.train(x=["income", "sex"], y="y", training_frame=data)
      coef = len(model_cust.coef())
      expected_coeff_len = (
          1 + 1 + 1 + 1
      )  # 1 for gender, 1 for income, 1 for gender_income interaction and 1 for intercept
      assert (
          coef == expected_coeff_len
      ), "Expected coefficient length: {0}, actual: {1} and they are different.".format(
          expected_coeff_len, coef
      )
  
imports: import sys
  import h2o
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_interaction_Lambda0() without return types