code: def test_distribution(df, loc, scale):
      def model():
          with pyro.plate("particles", 20000):
              return pyro.sample("x", dist.StudentT(df, loc, scale))
  
      expected = model()
      with poutine.reparam(config={"x": StudentTReparam()}):
          actual = model()
      assert ks_2samp(expected, actual).pvalue > 0.05
  
file_path: pyro/tests/infer/reparam/test_studentt.py
imports: import pytest
  import torch
  from scipy.stats import ks_2samp
  from torch.autograd import grad
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.infer.reparam import StudentTReparam
  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_distribution(df, loc, scale) and returns: pyro