def test_take_action_returns_nones_on_missing_values(): test_seed = 3 policy = TFPolicy(test_seed, basic_mock_brain(), basic_params()) policy.evaluate = MagicMock(return_value={}) brain_info_with_agents = BrainInfo([], [], [], agents=["an-agent-id"]) result = policy.get_action(brain_info_with_agents) assert result == ActionInfo(None, None, None, None, {})
def test_take_action_returns_nones_on_missing_values(): test_seed = 3 policy = TFPolicy(test_seed, basic_mock_brain(), basic_params()) policy.evaluate = MagicMock(return_value={}) policy.save_memories = MagicMock() step_with_agents = BatchedStepResult( [], np.array([], dtype=np.float32), np.array([False], dtype=np.bool), np.array([], dtype=np.bool), np.array([0]), None, ) result = policy.get_action(step_with_agents, worker_id=0) assert result == ActionInfo(None, None, {}, [0])
def test_take_action_returns_action_info_when_available(): test_seed = 3 policy = TFPolicy(test_seed, basic_mock_brain(), basic_params()) policy_eval_out = { "action": np.array([1.0], dtype=np.float32), "memory_out": np.array([[2.5]], dtype=np.float32), "value": np.array([1.1], dtype=np.float32), } policy.evaluate = MagicMock(return_value=policy_eval_out) brain_info_with_agents = BrainInfo([], [], [], agents=["an-agent-id"], local_done=[False]) result = policy.get_action(brain_info_with_agents) expected = ActionInfo(policy_eval_out["action"], policy_eval_out["value"], policy_eval_out) assert result == expected
def test_take_action_returns_action_info_when_available(): test_seed = 3 policy = TFPolicy(test_seed, basic_mock_brain(), basic_params()) policy_eval_out = { "action": np.array([1.0], dtype=np.float32), "memory_out": np.array([[2.5]], dtype=np.float32), "value": np.array([1.1], dtype=np.float32), } policy.evaluate = MagicMock(return_value=policy_eval_out) step_with_agents = BatchedStepResult( [], np.array([], dtype=np.float32), np.array([False], dtype=np.bool), np.array([], dtype=np.bool), np.array([0]), None, ) result = policy.get_action(step_with_agents) expected = ActionInfo(policy_eval_out["action"], policy_eval_out["value"], policy_eval_out, [0]) assert result == expected