code: def test_init(temperature, shape, dim):
      temperature = torch.tensor(temperature)
      logits = torch.randn(shape + (dim,)).requires_grad_()
  
      def model():
          with pyro.plate_stack("plates", shape):
              return pyro.sample(
                  "x",
                  dist.RelaxedOneHotCategorical(
                      temperature, logits=logits
                  ),
              )
  
      check_init_reparam(model, GumbelSoftmaxReparam())
  
file_path: pyro/tests/infer/reparam/test_softmax.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 GumbelSoftmaxReparam
  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(temperature, shape, dim) and returns: pyro