code: def test_init(shape, dim):
      concentration = torch.randn(shape + (dim,)).requires_grad_()
  
      def model():
          with pyro.plate_stack("plates", shape):
              return pyro.sample(
                  "x", dist.ProjectedNormal(concentration)
              )
  
      check_init_reparam(model, ProjectedNormalReparam())
  
file_path: pyro/tests/infer/reparam/test_projected_normal.py
imports: import pytest
  import torch
  from torch.autograd import grad
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.infer.reparam import ProjectedNormalReparam
  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(shape, dim) and returns: pyro