def test_pg_compilation(self):
"""Test whether a PGTrainer can be built with both frameworks."""
config = pg.DEFAULT_CONFIG.copy()
config["num_workers"] = 0 # Run locally.
num_iterations = 2
for _ in framework_iterator(config):
trainer = pg.PGTrainer(config=config, env="CartPole-v0")
for i in range(num_iterations):
trainer.train()
check_compute_single_action(trainer,
include_prev_action_reward=True)
def test_pg_compilation(self):
"""Test whether a PGTrainer can be built with both frameworks."""
config = pg.DEFAULT_CONFIG.copy()
config["num_workers"] = 1
config["rollout_fragment_length"] = 500
num_iterations = 1
for _ in framework_iterator(config):
for env in ["FrozenLake-v0", "CartPole-v0"]:
trainer = pg.PGTrainer(config=config, env=env)
for i in range(num_iterations):
print(trainer.train())
check_compute_single_action(
trainer, include_prev_action_reward=True)
def test_pg_compilation(self):
"""Test whether a PGTrainer can be built with both frameworks."""
config = pg.DEFAULT_CONFIG.copy()
config["num_workers"] = 0
num_iterations = 2
for fw in framework_iterator(config):
# For tf, build with fake-GPUs.
config["_fake_gpus"] = fw == "tf"
config["num_gpus"] = 2 if fw == "tf" else 0
trainer = pg.PGTrainer(config=config, env="CartPole-v0")
for i in range(num_iterations):
print(trainer.train())
check_compute_single_action(trainer,
include_prev_action_reward=True)
