TaskEg1.py

import os

from libero.libero import benchmark, get_libero_path
from libero.libero.envs import OffScreenRenderEnv

if __name__ == '__main__':

    benchmark_dict = benchmark.get_benchmark_dict()
    task_suite_name = "libero_10" # can also choose libero_spatial, libero_object, etc.
    task_suite = benchmark_dict[task_suite_name]()

    # retrieve a specific task
    task_id = 0
    task = task_suite.get_task(task_id)
    task_name = task.name
    task_description = task.language
    task_bddl_file = os.path.join(get_libero_path("bddl_files"), task.problem_folder, task.bddl_file)
    print(f"[info] retrieving task {task_id} from suite {task_suite_name}, the " + \
          f"language instruction is {task_description}, and the bddl file is {task_bddl_file}")

    # step over the environment
    env_args = {
        "bddl_file_name": task_bddl_file,
        "camera_heights": 128,
        "camera_widths": 128
    }
    env = OffScreenRenderEnv(**env_args)
    env.seed(0)
    env.reset()
    init_states = task_suite.get_task_init_states(task_id) # for benchmarking purpose, we fix the a set of initial states
    init_state_id = 0
    env.set_init_state(init_states[init_state_id])

    dummy_action = [0.] * 7
    for step in range(10):
        obs, reward, done, info = env.step(dummy_action)
    env.close()