def test_active(self, envs):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
dummy_wrapper.reset()
active = dummy_wrapper.active()
dummy_wrapper.close()
assert len(active) == ENV_NUM
def test_seed(self, envs, idx):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
seeds = dummy_wrapper.seed()
dummy_wrapper.close()
assert len(seeds) == ENV_NUM
def test_active(self, envs):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
dummy_wrapper.reset()
active = dummy_wrapper.active()
dummy_wrapper.close()
assert len(active) == ENV_NUM
def test_render(self, envs, idx, render_num):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
dummy_wrapper.reset(idx)
rendered = dummy_wrapper.render(idx)
dummy_wrapper.close()
assert len(rendered) == render_num
assert isinstance(rendered[0], np.ndarray)
assert rendered[0].ndim == 3 and rendered[0].shape[-1] == 3
def test_render(self, envs, idx, render_num):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
dummy_wrapper.reset(idx)
rendered = dummy_wrapper.render(idx)
dummy_wrapper.close()
assert len(rendered) == render_num
assert isinstance(rendered[0], np.ndarray)
assert rendered[0].ndim == 3 and rendered[0].shape[-1] == 3
def test_reset(self, envs, idx, reset_num):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
obsrvs = dummy_wrapper.reset(idx)
dummy_wrapper.close()
assert len(obsrvs) == reset_num
for obsrv in obsrvs:
assert dummy_wrapper.observation_space.contains(obsrv), \
"Required observation form: {}, Actual observation: {}" \
.format(str(dummy_wrapper.observation_space), obsrv)
def test_reset(self, envs, idx, reset_num):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
obsrvs = dummy_wrapper.reset(idx)
dummy_wrapper.close()
assert len(obsrvs) == reset_num
for obsrv in obsrvs:
assert dummy_wrapper.observation_space.contains(
obsrv
), "Required observation form: {}, Actual observation: {}".format(
str(dummy_wrapper.observation_space), obsrv)
def test_step(self, envs, idx, act_num):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
action = [mock_action(dummy_wrapper.action_space)
for _ in range(act_num)]
dummy_wrapper.reset(idx)
obsrvs, reward, terminal, info = dummy_wrapper.step(action, idx)
dummy_wrapper.close()
assert len(obsrvs) == act_num
assert len(reward) == act_num
assert len(terminal) == act_num
assert len(info) == act_num and isinstance(info[0], dict)
for obsrv in obsrvs:
assert dummy_wrapper.observation_space.contains(obsrv), \
"Required observation form: {}, Actual observation: {}" \
.format(str(dummy_wrapper.observation_space), obsrv)
def test_step(self, envs, idx, act_num):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
action = [
mock_action(dummy_wrapper.action_space) for _ in range(act_num)
]
dummy_wrapper.reset(idx)
obsrvs, reward, terminal, info = dummy_wrapper.step(action, idx)
dummy_wrapper.close()
assert len(obsrvs) == act_num
assert len(reward) == act_num
assert len(terminal) == act_num
assert len(info) == act_num and isinstance(info[0], dict)
for obsrv in obsrvs:
assert dummy_wrapper.observation_space.contains(
obsrv
), "Required observation form: {}, Actual observation: {}".format(
str(dummy_wrapper.observation_space), obsrv)
def test_size(self, envs):
dummy_wrapper = openai_gym.ParallelWrapperDummy(envs[0])
assert dummy_wrapper.size() == ENV_NUM
dummy_wrapper.close()
def test_close(self, envs):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
dummy_wrapper.close()
def test_seed(self, envs, idx):
for env_list in envs:
dummy_wrapper = openai_gym.ParallelWrapperDummy(env_list)
seeds = dummy_wrapper.seed()
dummy_wrapper.close()
assert len(seeds) == ENV_NUM
def test_close(self, envs):
for name, creators in zip(*envs):
default_logger.info(f"Testing on env {name}")
dummy_wrapper = openai_gym.ParallelWrapperDummy(creators)
dummy_wrapper.close()
