def test_step(self):
# Create a simple user
slate_size = 2
user_model = iev.IEvUserModel(
slate_size,
choice_model_ctor=choice_model.MultinomialLogitChoiceModel,
response_model_ctor=iev.IEvResponse)
# Create a candidate_set with 5 items
num_candidates = 5
document_sampler = iev.IEvVideoSampler()
ievsim = environment.Environment(user_model, document_sampler,
num_candidates, slate_size)
# Create agent
action_space = spaces.MultiDiscrete(num_candidates * np.ones((slate_size,)))
agent = random_agent.RandomAgent(action_space, random_seed=0)
# This agent doesn't use the previous user response
observation, documents = ievsim.reset()
slate = agent.step(1, dict(user=observation, doc=documents))
self.assertAllEqual(slate, [2, 0])
def test_slate_indices_and_length(self):
# Initialize agent
slate_size = 2
num_candidates = 100
action_space = spaces.MultiDiscrete(num_candidates * np.ones((slate_size,)))
user_model = iev.IEvUserModel(
slate_size,
choice_model_ctor=choice_model.MultinomialLogitChoiceModel,
response_model_ctor=iev.IEvResponse)
agent = random_agent.RandomAgent(action_space, random_seed=0)
# Create a set of documents
document_sampler = iev.IEvVideoSampler()
ievenv = environment.Environment(user_model, document_sampler,
num_candidates, slate_size)
# Test that slate indices in correct range and length is correct
observation, documents = ievenv.reset()
slate = agent.step(1, dict(user=observation, doc=documents))
self.assertLen(slate, slate_size)
self.assertAllInSet(slate, range(num_candidates))
def iev_document_sampler_creator(env_ctx):
return iev.IEvVideoSampler(doc_ctor=SingleClusterIEvVideo,
seed=env_ctx["seed"])