def test_profiling(self):
cartpole_env = gym.make('CartPole-v1')
env = gym_wrapper.GymWrapper(cartpole_env)
profile = [None]
def profile_fn(p):
self.assertIsInstance(p, cProfile.Profile)
profile[0] = p
env = wrappers.PerformanceProfiler(
env, process_profile_fn=profile_fn,
process_steps=2)
env.reset()
# Resets are also profiled.
s = pstats.Stats(env._profile)
self.assertGreater(s.total_calls, 0) # pytype: disable=attribute-error
for _ in range(2):
env.step(np.array(1, dtype=np.int32))
self.assertIsNotNone(profile[0])
previous_profile = profile[0]
updated_s = pstats.Stats(profile[0])
self.assertGreater(updated_s.total_calls, s.total_calls) # pytype: disable=attribute-error
for _ in range(2):
env.step(np.array(1, dtype=np.int32))
self.assertIsNotNone(profile[0])
# We saw a new profile.
self.assertNotEqual(profile[0], previous_profile)
def profile_env(env_str, max_ep_len, n_steps=None, env_wrappers=[]):
n_steps = n_steps or max_ep_len * 2
profile = [None]
def profile_fn(p):
assert isinstance(p, cProfile.Profile)
profile[0] = p
py_env = suite_gym.load(env_str, gym_env_wrappers=env_wrappers,
max_episode_steps=max_ep_len)
env = wrappers.PerformanceProfiler(
py_env, process_profile_fn=profile_fn,
process_steps=n_steps)
policy = random_py_policy.RandomPyPolicy(env.time_step_spec(), env.action_spec())
driver = py_driver.PyDriver(env, policy, [], max_steps=n_steps)
time_step = env.reset()
policy_state = policy.get_initial_state()
for _ in range(n_steps):
time_step, policy_state = driver.run(time_step, policy_state)
stats = pstats.Stats(profile[0])
stats.print_stats()
