Пример #1
0
    def test_set_reward_signal_nan_inf(self, float_case: float) -> None:
        """Test (not) keeping the reward signal for nan/inf."""
        predictor = TemporalDifference()
        state = State()
        state.add_resolved_dependency(
            ("tensorflow", "2.3.0", "https://pypi.org/simple"))
        state.add_resolved_dependency(
            ("flask", "0.12", "https://pypi.org/simple"))
        state.add_unresolved_dependency(
            ("termial-random", "0.0.2", "https://pypi.org/simple"))
        predictor._policy = {
            ("flask", "0.12", "https://pypi.org/simple"): [0.2, 1],
        }
        predictor._steps_taken = 2
        predictor._steps_reward = 1.2
        predictor._next_state = state

        assert (predictor.set_reward_signal(
            state, ("tensorflow", "2.0.0", "https://pypi.org/simple"),
            float_case) is None)

        assert predictor._policy == {
            ("flask", "0.12", "https://pypi.org/simple"): [1.4, 2],
            ("tensorflow", "2.3.0", "https://pypi.org/simple"): [1.2, 1],
        }
        assert predictor._steps_taken == 0
        assert predictor._steps_reward == 0.0
        assert predictor._next_state is None
Пример #2
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    def test_pre_run(self) -> None:
        """Test initialization done before running."""
        predictor = TemporalDifference()

        predictor._policy = {("tensorflow", "2.0.0", "https://pypi.org/simple"): [1.0, 2]}
        predictor._temperature_history = [(0.212, True, 0.23, 100)]
        predictor._temperature = 12.3

        context = flexmock(limit=42)
        with predictor.assigned_context(context):
            predictor.pre_run()

        assert predictor._policy == {}
        assert predictor._temperature_history == []
        assert isinstance(predictor._temperature, float)
        assert predictor._temperature == float(context.limit)
Пример #3
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    def test_set_reward_signal_unseen(self) -> None:
        """Test keeping the reward signal for an unseen step."""
        reward = 42.24
        package_tuple = ("tensorflow", "2.0.0", "https://thoth-station.ninja")

        state = flexmock()
        state.should_receive("iter_resolved_dependencies").and_return([package_tuple]).once()

        predictor = TemporalDifference()
        predictor._policy = {
            ("numpy", "1.0.0", "https://pypi.org/simple"): [30.30, 92],
        }

        predictor._steps_taken = 1
        predictor.set_reward_signal(state, None, reward)

        assert predictor._policy == {
            package_tuple: [42.24, 1],
            ("numpy", "1.0.0", "https://pypi.org/simple"): [30.30, 92],
        }
Пример #4
0
    def test_do_exploitation(self) -> None:
        """Tests on exploitation computation."""
        predictor = TemporalDifference()
        predictor._policy = {
            ("tensorflow", "2.1.0", "https://thoth-station.ninja"):
            [2020.21, 666],
            ("tensorflow", "2.0.0", "https://thoth-station.ninja"):
            [16.61, 1992],
            ("numpy", "1.0.0", "https://pypi.org/simple"): [30.30, 92],
        }

        state = flexmock()
        state.should_receive("iter_unresolved_dependencies").and_return([
            ("spacy", "2.2.4", "https://pypi.org/simple"),
            ("numpy", "1.0.0", "https://pypi.org/simple"),
            ("tensorflow", "2.1.0", "https://thoth-station.ninja"),
        ]).once()

        state.should_receive("get_random_unresolved_dependency").times(0)
        assert predictor._do_exploitation(state) == (
            "tensorflow",
            "2.1.0",
            "https://thoth-station.ninja",
        )