def test_process_rewards_info_logs_kwargs_partial(self):
task = OnlineOnPolicyEvalTask(time=False)
learner = RecordingLearner(with_info=True, with_log=True)
interactions = [
SimulatedInteraction(1,[1,2,3],rewards=[7,8,9]),
SimulatedInteraction(2,[4,5,6],rewards=[4,5,6],letters=['d','e','f']),
SimulatedInteraction(3,[7,8,9],rewards=[1,2,3],letters=['g','h','i']),
]
task_results = list(task.process(learner, interactions))
expected_predict_calls = [(1,[1,2,3]),(2,[4,5,6]),(3,[7,8,9])]
expected_predict_returns = [([1,0,0],1),([0,1,0],2),([0,0,1],3)]
expected_learn_calls = [(1,1,7,1,1),(2,5,5,1,2),(3,9,3,1,3)]
expected_task_results = [
{"rewards":7,'learn':1,'predict':1},
{"rewards":5,'learn':2,'predict':2,'letters':'e'},
{"rewards":3,'learn':3,'predict':3,'letters':'i'}
]
self.assertEqual(expected_predict_calls, learner.predict_calls)
self.assertEqual(expected_predict_returns, learner.predict_returns)
self.assertEqual(expected_learn_calls, learner.learn_calls)
self.assertEqual(expected_task_results, task_results)
def test_time(self):
task = OnlineOnPolicyEvalTask(time=True)
learner = RecordingLearner()
interactions = [SimulatedInteraction(1,[1,2,3],rewards=[7,8,9])]
task_results = list(task.process(learner, interactions))
self.assertAlmostEqual(0, task_results[0]["predict_time"], places=2)
self.assertAlmostEqual(0, task_results[0]["learn_time" ], places=2)
def test_process_sparse_rewards_no_info_no_logs_no_kwargs(self):
task = OnlineOnPolicyEvalTask(time=False)
learner = RecordingLearner(with_info=False, with_log=False)
interactions = [
SimulatedInteraction({'c':1},[{'a':1},{'a':2}],rewards=[7,8]),
SimulatedInteraction({'c':2},[{'a':4},{'a':5}],rewards=[4,5]),
]
task_results = list(task.process(learner, interactions))
expected_predict_calls = [({'c':1},[{'a':1},{'a':2}]),({'c':2},[{'a':4},{'a':5}])]
expected_predict_returns = [[1,0],[0,1]]
expected_learn_calls = [({'c':1},{'a':1},7,1,None),({'c':2},{'a':5},5,1,None)]
expected_task_results = [{"rewards":7},{"rewards":5}]
self.assertEqual(expected_predict_calls, learner.predict_calls)
self.assertEqual(expected_predict_returns, learner.predict_returns)
self.assertEqual(expected_learn_calls, learner.learn_calls)
self.assertEqual(expected_task_results, task_results)
def test_process_reveals_rewards_no_info_no_logs_no_kwargs(self):
task = OnlineOnPolicyEvalTask(time=False)
learner = RecordingLearner(with_info=False, with_log=False)
interactions = [
SimulatedInteraction(1,[1,2,3],reveals=[7,8,9],rewards=[1,3,5]),
SimulatedInteraction(2,[4,5,6],reveals=[4,5,6],rewards=[2,4,6]),
SimulatedInteraction(3,[7,8,9],reveals=[1,2,3],rewards=[3,5,7]),
]
task_results = list(task.process(learner, interactions))
expected_predict_calls = [(1,[1,2,3]),(2,[4,5,6]),(3,[7,8,9])]
expected_predict_returns = [[1,0,0],[0,1,0],[0,0,1]]
expected_learn_calls = [(1,1,7,1,None),(2,5,5,1,None),(3,9,3,1,None)]
expected_task_results = [{"reveals":7,"rewards":1},{"reveals":5,"rewards":4}, {"reveals":3,"rewards":7}]
self.assertEqual(expected_predict_calls, learner.predict_calls)
self.assertEqual(expected_predict_returns, learner.predict_returns)
self.assertEqual(expected_learn_calls, learner.learn_calls)
self.assertEqual(expected_task_results, task_results)