rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.hand_base.multi_task_vec_task#

1.  Module Contents#

1.1.  Classes#

VecTask

MultiTaskVecTaskPython

1.2.  API#

class rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.hand_base.multi_task_vec_task.VecTask(task, rl_device, clip_observations=5.0, clip_actions=1.0)[source]#

Initialization

abstract step(actions)[source]#
abstract reset()[source]#
get_number_of_agents()[source]#
uniform_random_strategy(num_tasks, _)[source]#

A function for sampling tasks uniformly at random.

Args:

num_tasks (int): Total number of tasks. _ (object): Ignored by this sampling strategy.

Returns:

int: task id.

round_robin_strategy(num_tasks, last_task=None)[source]#

A function for sampling tasks in round robin fashion.

Args:

num_tasks (int): Total number of tasks. last_task (int): Previously sampled task.

Returns:

int: task id.

property observation_space#
property action_space#
property num_envs#
property num_acts#
property num_obs#
class rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.hand_base.multi_task_vec_task.MultiTaskVecTaskPython(task, rl_device, clip_observations=5.0, clip_actions=1.0)[source]#

Bases: rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.hand_base.multi_task_vec_task.VecTask

Initialization

set_task(task)[source]#
get_state()[source]#
step(actions)[source]#
reset()[source]#