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92 lines
2.6 KiB
Python
92 lines
2.6 KiB
Python
import numpy as np
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from gym import utils
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from gym.envs.mujoco import mujoco_env
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DEFAULT_CAMERA_CONFIG = {
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"distance": 4.0,
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}
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class HalfCheetahEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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def __init__(
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self,
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xml_file="half_cheetah.xml",
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forward_reward_weight=1.0,
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ctrl_cost_weight=0.1,
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reset_noise_scale=0.1,
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exclude_current_positions_from_observation=True,
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):
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utils.EzPickle.__init__(**locals())
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self._forward_reward_weight = forward_reward_weight
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self._ctrl_cost_weight = ctrl_cost_weight
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self._reset_noise_scale = reset_noise_scale
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self._exclude_current_positions_from_observation = (
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exclude_current_positions_from_observation
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)
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mujoco_env.MujocoEnv.__init__(self, xml_file, 5)
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def control_cost(self, action):
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control_cost = self._ctrl_cost_weight * np.sum(np.square(action))
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return control_cost
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def step(self, action):
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x_position_before = self.sim.data.qpos[0]
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self.do_simulation(action, self.frame_skip)
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x_position_after = self.sim.data.qpos[0]
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x_velocity = (x_position_after - x_position_before) / self.dt
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ctrl_cost = self.control_cost(action)
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forward_reward = self._forward_reward_weight * x_velocity
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observation = self._get_obs()
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reward = forward_reward - ctrl_cost
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done = False
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info = {
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"x_position": x_position_after,
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"x_velocity": x_velocity,
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"reward_run": forward_reward,
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"reward_ctrl": -ctrl_cost,
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}
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return observation, reward, done, info
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def _get_obs(self):
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position = self.sim.data.qpos.flat.copy()
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velocity = self.sim.data.qvel.flat.copy()
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if self._exclude_current_positions_from_observation:
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position = position[1:]
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observation = np.concatenate((position, velocity)).ravel()
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return observation
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def reset_model(self):
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noise_low = -self._reset_noise_scale
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noise_high = self._reset_noise_scale
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qpos = self.init_qpos + self.np_random.uniform(
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low=noise_low, high=noise_high, size=self.model.nq
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)
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qvel = self.init_qvel + self._reset_noise_scale * self.np_random.randn(
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self.model.nv
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)
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self.set_state(qpos, qvel)
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observation = self._get_obs()
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return observation
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def viewer_setup(self):
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for key, value in DEFAULT_CAMERA_CONFIG.items():
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if isinstance(value, np.ndarray):
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getattr(self.viewer.cam, key)[:] = value
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else:
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setattr(self.viewer.cam, key, value)
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