def construct_envs(config: Config, env_class: Type[Union[Env,
RLEnv]]) -> VectorEnv:
r"""Create VectorEnv object with specified config and env class type.
To allow better performance, dataset are split into small ones for
each individual env, grouped by scenes.
Args:
config: configs that contain num_processes as well as information
necessary to create individual environments.
env_class: class type of the envs to be created.
Returns:
VectorEnv object created according to specification.
"""
num_processes = config.NUM_PROCESSES
configs = []
env_classes = [env_class for _ in range(num_processes)]
dataset = make_dataset(config.TASK_CONFIG.DATASET.TYPE)
scenes = dataset.get_scenes_to_load(config.TASK_CONFIG.DATASET)
if len(scenes) > 0:
random.shuffle(scenes)
assert len(scenes) >= num_processes, (
"reduce the number of processes as there "
"aren't enough number of scenes")
scene_splits = [[] for _ in range(num_processes)]
for idx, scene in enumerate(scenes):
scene_splits[idx % len(scene_splits)].append(scene)
assert sum(map(len, scene_splits)) == len(scenes)
for i in range(num_processes):
task_config = config.TASK_CONFIG.clone()
task_config.defrost()
if len(scenes) > 0:
task_config.DATASET.CONTENT_SCENES = scene_splits[i]
task_config.SIMULATOR.HABITAT_SIM_V0.GPU_DEVICE_ID = (
config.SIMULATOR_GPU_ID)
task_config.SIMULATOR.AGENT_0.SENSORS = config.SENSORS
task_config.freeze()
config.defrost()
config.TASK_CONFIG = task_config
config.freeze()
configs.append(config.clone())
envs = habitat.VectorEnv(
make_env_fn=make_env_fn,
env_fn_args=tuple(
tuple(zip(configs, env_classes, range(num_processes)))),
)
return envs
def __init__(self, task_config: Optional[Config] = None) -> None:
r"""..
:param task_config: config to be used for creating the environment
"""
dummy_config = Config()
dummy_config.RL = Config()
dummy_config.RL.SLACK_REWARD = -0.01
dummy_config.RL.SUCCESS_REWARD = 10
dummy_config.RL.WITH_TIME_PENALTY = True
dummy_config.RL.DISTANCE_REWARD_SCALE = 1
dummy_config.RL.WITH_DISTANCE_REWARD = True
dummy_config.RL.defrost()
dummy_config.TASK_CONFIG = task_config
dummy_config.freeze()
dataset = make_dataset(id_dataset=task_config.DATASET.TYPE,
config=task_config.DATASET)
self._env = NavRLEnv(config=dummy_config, dataset=dataset)
def construct_envs(config: Config, env_class: Type[Union[Env,
RLEnv]]) -> VectorEnv:
r"""Create VectorEnv object with specified config and env class type.
To allow better performance, dataset are split into small ones for
each individual env, grouped by scenes.
Args:
config: configs that contain num_processes as well as information
necessary to create individual environments.
env_class: class type of the envs to be created
Returns:
VectorEnv object created according to specification.
"""
num_processes = config.NUM_PROCESSES
configs = []
env_classes = [env_class for _ in range(num_processes)]
dataset = make_dataset(config.TASK_CONFIG.DATASET.TYPE)
scenes = dataset.get_scenes_to_load(config.TASK_CONFIG.DATASET)
# rearrange scenes in the order of scene size since there is a severe imbalance of data size
if "replica" in config.TASK_CONFIG.DATASET.SCENES_DIR:
scenes_new = list()
for scene in SCENES:
if scene in scenes:
scenes_new.append(scene)
scenes = scenes_new
if len(scenes) > 0:
# random.shuffle(scenes)
assert len(scenes) >= num_processes, (
"reduce the number of processes as there "
"aren't enough number of scenes")
scene_splits = [[] for _ in range(num_processes)]
for idx, scene in enumerate(scenes):
scene_splits[idx % len(scene_splits)].append(scene)
assert sum(map(len, scene_splits)) == len(scenes)
for i in range(num_processes):
task_config = config.TASK_CONFIG.clone()
task_config.defrost()
if len(scenes) > 0:
task_config.DATASET.CONTENT_SCENES = scene_splits[i]
logging.debug('All scenes: {}'.format(','.join(scene_splits[i])))
# overwrite the task config with top-level config file
task_config.SIMULATOR.HABITAT_SIM_V0.GPU_DEVICE_ID = (
config.SIMULATOR_GPU_ID)
task_config.SIMULATOR.AGENT_0.SENSORS = config.SENSORS
task_config.freeze()
config.defrost()
config.TASK_CONFIG = task_config
config.freeze()
configs.append(config.clone())
# use VectorEnv for the best performance and ThreadedVectorEnv for debugging
if config.USE_SYNC_VECENV:
env_launcher = SyncVectorEnv
logging.info('Using SyncVectorEnv')
elif config.USE_VECENV:
env_launcher = habitat.VectorEnv
logging.info('Using VectorEnv')
else:
env_launcher = habitat.ThreadedVectorEnv
logging.info('Using ThreadedVectorEnv')
envs = env_launcher(
make_env_fn=make_env_fn,
env_fn_args=tuple(
tuple(zip(configs, env_classes, range(num_processes)))),
)
return envs
