code: def test_basic(self):
      state_dim = 8
      action_dim = 4
      model = FullyConnectedCritic(
          state_dim,
          action_dim,
          sizes=[8, 4],
          activations=["relu", "relu"],
          use_batch_norm=True,
      )
      state, action = model.input_prototype()
      self.assertEqual((1, state_dim), state.float_features.shape)
      self.assertEqual((1, action_dim), action.float_features.shape)
      # Using batch norm requires more than 1 example in training, avoid that
      model.eval()
      single_q_value = model(state, action)
      self.assertEqual((1, 1), single_q_value.shape)
  
file_path: ReAgent/reagent/test/models/test_critic.py
imports: import logging
  import unittest
  import torch
  import torch.nn
  from reagent.core import types
  from reagent.models.critic import FullyConnectedCritic
  from reagent.test.models.test_utils import run_model_jit_trace
label_desc: Use image node_id 2 for calling the TestFullyConnectedCritic obj's underlying member method code with example usage: obj.test_basic() without return types