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adding test for deterministic action playback (#178)
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""" | ||
Test script for recording a sequence of random actions and playing them back | ||
""" | ||
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import os | ||
import h5py | ||
import argparse | ||
import random | ||
import numpy as np | ||
import json | ||
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import robosuite | ||
from robosuite.controllers import load_controller_config | ||
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def test_playback(): | ||
# set seeds | ||
random.seed(0) | ||
np.random.seed(0) | ||
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env = robosuite.make( | ||
"Lift", | ||
robots=["Panda"], | ||
controller_configs=load_controller_config(default_controller="OSC_POSE"), | ||
has_renderer=False, | ||
has_offscreen_renderer=False, | ||
ignore_done=True, | ||
use_camera_obs=False, | ||
reward_shaping=True, | ||
control_freq=20, | ||
) | ||
env.reset() | ||
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# task instance | ||
task_xml = env.sim.model.get_xml() | ||
task_init_state = np.array(env.sim.get_state().flatten()) | ||
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# trick for ensuring that we can play MuJoCo demonstrations back | ||
# deterministically by using the recorded actions open loop | ||
env.reset_from_xml_string(task_xml) | ||
env.sim.reset() | ||
env.sim.set_state_from_flattened(task_init_state) | ||
env.sim.forward() | ||
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# random actions to play | ||
n_actions = 100 | ||
actions = 0.1 * np.random.uniform(low=-1., high=1., size=(n_actions, env.action_spec[0].shape[0])) | ||
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# play actions | ||
print("playing random actions...") | ||
states = [task_init_state] | ||
for i in range(n_actions): | ||
env.step(actions[i]) | ||
states.append(np.array(env.sim.get_state().flatten())) | ||
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# try playback | ||
print("attempting playback...") | ||
env.reset() | ||
env.reset_from_xml_string(task_xml) | ||
env.sim.reset() | ||
env.sim.set_state_from_flattened(task_init_state) | ||
env.sim.forward() | ||
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for i in range(n_actions): | ||
env.step(actions[i]) | ||
state_playback = env.sim.get_state().flatten() | ||
assert(np.all(np.equal(states[i + 1], state_playback))) | ||
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print("test passed!") | ||
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if __name__ == "__main__": | ||
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test_playback() | ||
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