def test_active(self, envs):
for env_list in envs:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
subproc_wrapper.reset()
active = subproc_wrapper.active()
subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
seeds = subproc_wrapper.seed()
subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
subproc_wrapper.reset()
active = subproc_wrapper.active()
subproc_wrapper.close()
assert len(active) == ENV_NUM
def test_render(self, envs, idx, render_num):
for env_list in envs:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
subproc_wrapper.reset(idx)
rendered = subproc_wrapper.render(idx)
subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
subproc_wrapper.reset(idx)
rendered = subproc_wrapper.render(idx)
subproc_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:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
obsrvs = subproc_wrapper.reset(idx)
subproc_wrapper.close()
assert len(obsrvs) == reset_num
for obsrv in obsrvs:
assert subproc_wrapper.observation_space.contains(obsrv), \
"Required observation form: {}, Actual observation: {}" \
.format(str(subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
obsrvs = subproc_wrapper.reset(idx)
subproc_wrapper.close()
assert len(obsrvs) == reset_num
for obsrv in obsrvs:
assert subproc_wrapper.observation_space.contains(
obsrv
), "Required observation form: {}, Actual observation: {}".format(
str(subproc_wrapper.observation_space), obsrv)
def test_step(self, envs, idx, act_num):
for env_list in envs:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
action = [mock_action(subproc_wrapper.action_space)
for _ in range(act_num)]
subproc_wrapper.reset(idx)
obsrvs, reward, terminal, info = subproc_wrapper.step(action, idx)
subproc_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 subproc_wrapper.observation_space.contains(obsrv), \
"Required observation form: {}, Actual observation: {}" \
.format(str(subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
action = [
mock_action(subproc_wrapper.action_space)
for _ in range(act_num)
]
subproc_wrapper.reset(idx)
obsrvs, reward, terminal, info = subproc_wrapper.step(action, idx)
subproc_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 subproc_wrapper.observation_space.contains(
obsrv
), "Required observation form: {}, Actual observation: {}".format(
str(subproc_wrapper.observation_space), obsrv)
def test_size(self, envs):
subproc_wrapper = openai_gym.ParallelWrapperSubProc(envs[0])
assert subproc_wrapper.size() == ENV_NUM
subproc_wrapper.close()
def test_close(self, envs):
for env_list in envs:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
subproc_wrapper.close()
def test_seed(self, envs, idx):
for env_list in envs:
subproc_wrapper = openai_gym.ParallelWrapperSubProc(env_list)
seeds = subproc_wrapper.seed()
subproc_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}")
subproc_wrapper = openai_gym.ParallelWrapperSubProc(creators)
subproc_wrapper.close()
