code: def test_init(dist_type, centered, shape):
      loc = torch.empty(shape).uniform_(-1.0, 1.0)
      scale = torch.empty(shape).uniform_(0.5, 1.5)
  
      def model():
          with pyro.plate_stack("plates", shape):
              if "dist_type" == "Normal":
                  return pyro.sample("x", dist.Normal(loc, scale))
              elif "dist_type" == "StudentT":
                  return pyro.sample(
                      "x", dist.StudentT(10.0, loc, scale)
                  )
              else:
                  return pyro.sample(
                      "x", dist.AsymmetricLaplace(loc, scale, 1.5)
                  )
  
      check_init_reparam(model, LocScaleReparam(centered))
  
file_path: pyro/tests/infer/reparam/test_loc_scale.py
imports: import pytest
  import torch
  from torch.autograd import grad
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.distributions.util import is_identically_one
  from pyro.infer.autoguide.initialization import InitMessenger, init_to_uniform
  from pyro.infer.reparam import LocScaleReparam
  from tests.common import assert_close
  from .util import check_init_reparam
label_desc: Use image node_id 3 for calling a global function with example usage: test_init(dist_type, centered, shape) and returns: pyro, pyro, pyro