def test_maml_compilation(self):
"""Test whether a MAMLTrainer can be built with all frameworks."""
config = maml.MAMLConfig().rollouts(num_rollout_workers=1, horizon=200)
num_iterations = 1
# Test for tf framework (torch not implemented yet).
for fw in framework_iterator(config, frameworks=("tf", "torch")):
for env in [
"pendulum_mass.PendulumMassEnv",
"cartpole_mass.CartPoleMassEnv",
]:
if fw == "tf" and env.startswith("cartpole"):
continue
print("env={}".format(env))
env_ = "ray.rllib.examples.env.{}".format(env)
trainer = config.build(env=env_)
for i in range(num_iterations):
results = trainer.train()
check_train_results(results)
print(results)
check_compute_single_action(trainer,
include_prev_action_reward=True)
trainer.stop()
def _import_maml():
import ray.rllib.algorithms.maml as maml
return maml.MAML, maml.MAMLConfig().to_dict()