class_docstr: Tests methods specific to the Categorical distribution
code: def test_log_prob_sum(self):
      log_px_torch = (
          dist.Categorical(self.probs)
          .log_prob(self.test_data)
          .sum()
          .item()
      )
      log_px_np = float(
          sp.multinomial.logpmf(
              np.array([0, 0, 1]), 1, self.probs.detach().cpu().numpy()
          )
      )
      assert_equal(log_px_torch, log_px_np, prec=1e-4)
  
imports: from unittest import TestCase
  import numpy
  import pytest
  import scipy.stats
  import torch
  import pyro.distributions
  from tests.common import assert_equal
label_desc: Use image node_id 2 for calling the TestCategorical obj's underlying member method code with example usage: obj.test_log_prob_sum() without return types