code: def test_auto_scale(diabetes_data):
      # By default, should scale everything except custom bmb.Prior() objects
      priors = {"BP": bmb.Prior("Cauchy", alpha=1, beta=17.5)}
      model = bmb.Model(
          "BMI ~ S1 + S2 + BP", diabetes_data, priors=priors
      )
      p1 = model.response_component.terms["S1"].prior
      p2 = model.response_component.terms["S2"].prior
      p3 = model.response_component.terms["BP"].prior
      assert p1.name == p2.name == "Normal"
      assert 0 < p1.args["sigma"] < 1
      assert p2.args["sigma"] > p1.args["sigma"]
      assert p3.name == "Cauchy"
      assert p3.args["beta"] == 17.5
  
      # With auto_scale off, custom priors are considered.
      priors = {"BP": bmb.Prior("Cauchy", alpha=1, beta=17.5)}
      model = bmb.Model(
          "BMI ~ S1 + S2 + BP",
          diabetes_data,
          priors=priors,
          auto_scale=False,
      )
      p2_off = model.response_component.terms["S2"].prior
      p3_off = model.response_component.terms["BP"].prior
      assert p2_off.name == "Flat"
      assert "sigma" not in p2_off.args
      assert p3_off.name == "Cauchy"
  
imports: from os.path import dirname, join
  import pytest
  import numpy
  import pymc
  import pandas
  from scipy import special
  import bambi
label_desc: Use image node_id 8 for calling a global function with example usage: test_auto_scale(diabetes_data) without return types