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import competitive_rl
import pytest
import numpy as np
from easydict import EasyDict
from dizoo.competitive_rl.envs.competitive_rl_env import CompetitiveRlEnv
@pytest.mark.envtest
class TestCompetitiveRlEnv:
def test_pong_single(self):
cfg = dict(
opponent_type="builtin",
is_evaluator=True,
env_id='cPongDouble-v0',
)
cfg = EasyDict(cfg)
env = CompetitiveRlEnv(cfg)
env.seed(314)
assert env._seed == 314
obs = env.reset()
assert obs.shape == env.info().obs_space.shape
# act_shape = env.info().act_space.shape
act_val = env.info().act_space.value
min_val, max_val = act_val['min'], act_val['max']
np.random.seed(314)
i = 0
while True:
random_action = np.random.randint(min_val, max_val, size=(1, ))
timestep = env.step(random_action)
if timestep.done:
print(timestep)
print('Env episode has {} steps'.format(i))
break
assert isinstance(timestep.obs, np.ndarray)
assert isinstance(timestep.done, bool)
assert timestep.obs.shape == env.info().obs_space.shape
assert timestep.reward.shape == env.info().rew_space.shape
assert timestep.reward >= env.info().rew_space.value['min']
assert timestep.reward <= env.info().rew_space.value['max']
i += 1
print(env.info())
env.close()
def test_pong_double(self):
cfg = dict(env_id='cPongDouble-v0', )
cfg = EasyDict(cfg)
env = CompetitiveRlEnv(cfg)
env.seed(314)
assert env._seed == 314
obs = env.reset()
assert obs.shape == env.info().obs_space.shape
act_val = env.info().act_space.value
min_val, max_val = act_val['min'], act_val['max']
np.random.seed(314)
i = 0
while True:
random_action = [np.random.randint(min_val, max_val, size=(1, )) for _ in range(2)]
timestep = env.step(random_action)
if timestep.done:
print(timestep)
print('Env episode has {} steps'.format(i))
break
assert isinstance(timestep.obs, np.ndarray)
assert isinstance(timestep.done, bool)
assert timestep.obs.shape == env.info().obs_space.shape
assert timestep.reward.shape == env.info().rew_space.shape
i += 1
print(env.info())
env.close()
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