code: def test_basic(self):
      state_dim = 8
      action_dim = 4
      model = DirichletFullyConnectedActor(
          state_dim,
          action_dim,
          sizes=[7, 6],
          activations=["relu", "relu"],
          use_batch_norm=True,
      )
      input = model.input_prototype()
      self.assertEqual((1, state_dim), input.float_features.shape)
      # Using batch norm requires more than 1 example in training, avoid that
      model.eval()
      action = model(input)
      self.assertEqual((1, action_dim), action.action.shape)
      self.assertEqual((1, 1), action.log_prob.shape)
  
imports: import logging
  import unittest
  from typing import Union
  import numpy.testing
  import torch
  import torch.nn
  from reagent.core import types
  from reagent.models.actor import DirichletFullyConnectedActor, FullyConnectedActor, GaussianFullyConnectedActor
  from reagent.test.models.test_utils import run_model_jit_trace
label_desc: Use image node_id 1 for calling the TestDirichletFullyConnectedActor obj's underlying member method code with example usage: obj.test_basic() without return types