def test_choose_rank(self):
model = rl_client.live_model(self.config)
model.init()
event_id = "event_id"
context = '{"_multi":[{},{}]}'
model.choose_rank(event_id, context)
def main():
config = load_config_from_json("client.json")
test_cb = my_error_callback()
model = rl_client.live_model(config, test_cb)
model.init()
event_id = "event_id"
context = '{"User":{"id":"a","major":"eng","hobby":"hiking"},"_multi":[{"N1":{"F1":"V1"},"N2":{"F2":"V2"}},{"N3":{"F1":"V3"}}]}'
model_id, chosen_action_id, action_probabilities = model.choose_rank(
event_id, context)
print("event_id: " + event_id)
print("model_id: " + model_id)
print("chosen action id: " + str(chosen_action_id))
print("all action probabilities " + str(action_probabilities))
model_id, chosen_action_id, action_probabilities, event_id = model.choose_rank(
context)
print("event_id: " + event_id)
print("model_id: " + model_id)
print("chosen action id: " + str(chosen_action_id))
print("all action probabilities " + str(action_probabilities))
outcome = 1.0
model.report_outcome(event_id, outcome)
def test_choose_rank_invalid_event_id(self):
model = rl_client.live_model(self.config)
model.init()
invalid_event_id = ""
context = '{"_multi":[{},{}]}'
self.assertRaises(Exception, model.choose_rank, invalid_event_id,
context)
def test_choose_rank_invalid_context(self):
model = rl_client.live_model(self.config)
model.init()
event_id = "event_id"
invalid_context = ""
self.assertRaises(Exception, model.choose_rank, event_id,
invalid_context)
def test_report_outcome(self):
model = rl_client.live_model(self.config)
model.init()
event_id = "event_id"
context = '{"_multi":[{},{}]}'
model.choose_rank(event_id, context)
model.report_outcome(event_id, 1.0)
model.report_outcome(event_id, "{'result':'res'}")
def __init__(self, args):
self._options = args
self.config = load_config_from_json(self._options.json_config)
self._rl_client = rl_client.live_model(self.config, my_error_callback())
self._rl_client.init()
tp1 = {'HerbGarden': 0.3, "MachineLearning": 0.2 }
tp2 = {'HerbGarden': 0.1, "MachineLearning": 0.4 }
self._actions = ['HerbGarden', 'MachineLearning']
self._people = [
person('rnc', 'engineering', 'hiking', 'spock', tp1),
person('mk', 'psychology', 'kids', '7of9', tp2)]
def main(args):
options = process_cmd_line(args)
config = load_config_from_json(options.json_config)
model = rl_client.live_model(config, my_error_callback())
model.init()
with open(options.log_file) as fp:
for count, line in enumerate(fp):
current_example = json.loads(line)
context_json = json.dumps(current_example["c"])
model_id, chosen_action_id, actions_probabilities = model.choose_rank(
current_example["EventId"], context_json)
if ("o" in current_example):
for observation in current_example["o"]:
outcome = observation["v"] if isinstance(
observation["v"], numbers.Real) else json.dumps(
observation["v"])
model.report_outcome(observation["EventId"], outcome)