def test_simple_run(self):
arm_num = 5
horizon = 10
learner = UCB(arm_num=arm_num)
learner.reset()
mock_ucb = np.array([1.2, 1, 1, 1, 1])
# pylint: disable=protected-access
learner._UCB__UCB = MagicMock(return_value=mock_ucb)
# During the initial time steps, each arm is pulled once
for time in range(1, arm_num + 1):
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: {arm_id}
>
times: 1
>
""".format(arm_id=time - 1), Actions()).SerializeToString()
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: {arm_id}
>
rewards: 0
>
""".format(arm_id=time - 1), Feedback()))
# For the left time steps, arm 0 is always the choice
for _ in range(arm_num + 1, horizon + 1):
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: 0
>
times: 1
>
""", Actions()).SerializeToString()
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: 0
>
rewards: 0
>
""", Feedback()))
def test_simple_run(self):
arm_num = 5
horizon = 10
learner = Uniform(arm_num=arm_num)
learner.reset()
for time in range(1, horizon + 1):
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: {arm_id}
>
times: 1
>
""".format(arm_id=(time - 1) % arm_num),
Actions()).SerializeToString()
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: 0
>
rewards: 0
>
""", Feedback()))
def test_simple_run(self):
means = [0, 0.5, 0.7, 1]
arms = [BernoulliArm(mean) for mean in means]
learner = EpsGreedy(arm_num=len(arms))
learner.reset()
# Pull each arm once during the initial steps
for time in range(1, len(arms) + 1):
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: {arm_id}
>
times: 1
>
""".format(arm_id=time - 1), Actions()).SerializeToString()
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: {arm_id}
>
rewards: 0
>
""".format(arm_id=time - 1), Feedback()))
def test_simple_run(self):
revenues = np.array([0, 0.7, 0.8, 0.9, 1.0])
horizon = 100
reward = CvarReward(0.7)
learner = ThompsonSampling(revenues=revenues,
horizon=horizon,
reward=reward)
# Test warm start
learner.reset()
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls {
arm {
set {
id: 1
}
}
times: 1
}
""", Actions()).SerializeToString()
learner.reset()
# pylint: disable=protected-access
learner._ThompsonSampling__within_warm_start = MagicMock(
return_value=False)
mock_preference_params = np.array([1, 1, 1, 1, 1])
learner._ThompsonSampling__correlated_sampling = MagicMock(
return_value=mock_preference_params)
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls {
arm {
set {
id: 1
id: 2
id: 3
id: 4
}
}
times: 1
}
""", Actions()).SerializeToString()
def test_simple_run(self):
ts_learner = ThompsonSampling(arm_num=4)
ts_learner.reset()
# pylint: disable=protected-access
ts_learner._ThompsonSampling__sample_from_beta_prior = MagicMock(
return_value=1)
# always pull arm 1
assert ts_learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: 1
>
times: 1
>
""", Actions()).SerializeToString()
def test_simple_run(self):
arm_num = 5
budget = 20
learner = SH(arm_num=arm_num, budget=budget)
learner.reset()
while True:
actions = learner.actions(Context())
if not actions.arm_pulls:
break
feedback = Feedback()
for arm_pull in actions.arm_pulls:
arm_feedback = feedback.arm_feedbacks.add()
arm_feedback.arm.id = arm_pull.arm.id
arm_feedback.rewards.extend(list(np.zeros(arm_pull.times)))
learner.update(feedback)
assert learner.best_arm in list(range(arm_num))
def test_simple_run(self):
arm_num = 3
confidence = 0.95
learner = ExpGap(arm_num=arm_num, confidence=confidence)
learner.reset()
while True:
actions = learner.actions(Context())
if not actions.arm_pulls:
break
feedback = Feedback()
for arm_pull in actions.arm_pulls:
arm_feedback = feedback.arm_feedbacks.add()
arm_feedback.arm.id = arm_pull.arm.id
arm_feedback.rewards.extend(
list(
np.random.normal(arm_pull.arm.id / arm_num, 1,
arm_pull.times)))
learner.update(feedback)
assert learner.best_arm in list(range(arm_num))
def test_simple_run(self):
arm_num = 5
horizon = 10
learner = ExploreThenCommit(arm_num=arm_num, T_prime=6)
learner.reset()
for _ in range(1, horizon + 1):
actions = learner.actions(Context())
assert len(actions.arm_pulls) == 1
arm_pull = actions.arm_pulls[0]
arm_id = arm_pull.arm.id
assert arm_pull.times == 1
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: {arm_id}
>
rewards: 0
>
""".format(arm_id=arm_id), Feedback()))
def test_simple_run(self):
horizon = 10
features = [
np.array([1, 0]),
np.array([1, 0]),
np.array([1, 0]),
np.array([1, 0]),
np.array([0, 1])
]
learner = LinUCB(features, 0.1, 1e-3)
learner.reset()
mock_ucb = np.array([1.2, 1, 1, 1, 1])
# pylint: disable=protected-access
learner._LinUCB__LinUCB = MagicMock(return_value=mock_ucb)
# Always 0th arm is picked
# not the most efficient test
for _ in range(1, horizon + 1):
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls <
arm <
id: 0
>
times: 1
>
""", Actions()).SerializeToString()
learner.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: 0
>
rewards: 0
>
""", Feedback()))
def test_actions(self):
# Test actions are in the right range
arm_num = 10
budget = 15
apt = APT(arm_num=arm_num, theta=0.5, eps=0)
apt.reset()
for _ in range(budget):
actions = apt.actions(Context())
assert len(actions.arm_pulls) == 1
arm_id = actions.arm_pulls[0].arm.id
assert 0 <= arm_id < arm_num
apt.update(
text_format.Parse(
"""
arm_feedbacks <
arm <
id: {arm_id}
>
rewards: 0
>
""".format(arm_id=arm_id), Feedback()))
def test_simple_run(self):
revenues = np.array([0, 0.45, 0.8, 0.9, 1.0])
reward = MeanReward()
learner = EpsGreedy(revenues=revenues, reward=reward)
learner.reset()
mock_random_assortment = {2, 3, 4}
# pylint: disable=protected-access
learner._EpsGreedy__select_ramdom_assort = MagicMock(
return_value=mock_random_assortment)
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls {
arm {
set {
id: 2
id: 3
id: 4
}
}
times: 1
}
""", Actions()).SerializeToString()
def test_simple_run(self):
revenues = np.array([0, 0.7, 0.8, 0.9, 1.0])
reward = CvarReward(0.7)
learner = UCB(revenues=revenues, reward=reward)
learner.reset()
mock_preference_params = np.array([1, 1, 1, 1, 1])
# pylint: disable=protected-access
learner._UCB__UCB = MagicMock(return_value=mock_preference_params)
assert learner.actions(
Context()).SerializeToString() == text_format.Parse(
"""
arm_pulls {
arm {
set {
id: 1
id: 2
id: 3
id: 4
}
}
times: 1
}
""", Actions()).SerializeToString()
def context(self) -> Context: self.__context_and_rewards = self.__context_generator.context() context = Context() context.sequential_context.value.extend(self.__context_and_rewards[0]) return context
def context(self) -> Context:
return Context()