code: def from_formula(
      cls, formula, data, exog_precision_formula=None, *args, **kwargs
  ):
      if exog_precision_formula is not None:
          if "subset" in kwargs:
              d = data.ix[kwargs["subset"]]
              Z = patsy.dmatrix(exog_precision_formula, d)
          else:
              Z = patsy.dmatrix(exog_precision_formula, data)
          kwargs["exog_precision"] = Z
  
      return super().from_formula(formula, data, *args, **kwargs)
  
imports: import numpy
  from scipy.special import gammaln
  import patsy
  import statsmodels.base.wrapper
  import statsmodels.regression.linear_model
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.base.model import GenericLikelihoodModel, GenericLikelihoodModelResults, _LLRMixin
  from statsmodels.genmod import families
label_desc: Use image node_id 2 for calling the BetaModel obj's underlying member method code with example usage: obj.from_formula(cls, formula, data, exog_precision_formula) and returns: super