Merge branch 'fix_automatic_render' into pr_v0.3.0
This commit is contained in:
commit
1008c84a4b
40
.github/workflows/host_docs_static.yml
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40
.github/workflows/host_docs_static.yml
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name: Deploy static docs to Pages
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on:
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push:
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branches: ["release"]
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# Allows you to run this workflow manually from the Actions tab
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workflow_dispatch:
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# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
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permissions:
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contents: read
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pages: write
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id-token: write
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# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
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# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
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concurrency:
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group: "pages"
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cancel-in-progress: false
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jobs:
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# Single deploy job since we're just deploying
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deploy:
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environment:
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name: github-pages
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url: ${{ steps.deployment.outputs.page_url }}
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Setup Pages
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uses: actions/configure-pages@v4
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- name: Upload artifact
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uses: actions/upload-pages-artifact@v3
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with:
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path: 'docs/build/html'
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- name: Deploy to GitHub Pages
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id: deployment
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uses: actions/deploy-pages@v4
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@ -115,6 +115,7 @@ class AntJumpEnv(AntEnvCustomXML):
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contact_force_range=contact_force_range,
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reset_noise_scale=reset_noise_scale,
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exclude_current_positions_from_observation=exclude_current_positions_from_observation, **kwargs)
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self.render_active = False
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def step(self, action):
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self.current_step += 1
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@ -153,8 +154,15 @@ class AntJumpEnv(AntEnvCustomXML):
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}
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truncated = False
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if self.render_active and self.render_mode=='human':
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self.render()
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return obs, reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def _get_obs(self):
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return np.append(super()._get_obs(), self.goal)
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@ -44,6 +44,7 @@ class BeerPongEnv(MujocoEnv, utils.EzPickle):
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}
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def __init__(self, **kwargs):
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utils.EzPickle.__init__(self)
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self._steps = 0
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# Small Context -> Easier. Todo: Should we do different versions?
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# self.xml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets", "beerpong_wo_cup.xml")
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@ -89,7 +90,7 @@ class BeerPongEnv(MujocoEnv, utils.EzPickle):
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observation_space=self.observation_space,
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**kwargs
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)
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utils.EzPickle.__init__(self)
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self.render_active = False
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@property
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def start_pos(self):
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@ -169,8 +170,15 @@ class BeerPongEnv(MujocoEnv, utils.EzPickle):
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truncated = False
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if self.render_active and self.render_mode=='human':
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self.render()
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return ob, reward, terminated, truncated, infos
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def render(self):
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self.render_active = True
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return super().render()
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def _get_obs(self):
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theta = self.data.qpos.flat[:7].copy()
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theta_dot = self.data.qvel.flat[:7].copy()
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@ -4,6 +4,7 @@ import numpy as np
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from gymnasium import utils, spaces
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from gymnasium.envs.mujoco import MujocoEnv
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from fancy_gym.envs.mujoco.box_pushing.box_pushing_utils import rot_to_quat, get_quaternion_error, rotation_distance
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from fancy_gym.envs.mujoco.box_pushing.box_pushing_utils import rot_to_quat, get_quaternion_error, rotation_distance
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from fancy_gym.envs.mujoco.box_pushing.box_pushing_utils import q_max, q_min, q_dot_max, q_torque_max
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from fancy_gym.envs.mujoco.box_pushing.box_pushing_utils import desired_rod_quat
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@ -60,6 +61,7 @@ class BoxPushingEnvBase(MujocoEnv, utils.EzPickle):
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frame_skip=self.frame_skip,
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observation_space=self.observation_space, **kwargs)
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self.action_space = spaces.Box(low=-1, high=1, shape=(7,))
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self.render_active = False
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def step(self, action):
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action = 10 * np.clip(action, self.action_space.low, self.action_space.high)
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@ -108,8 +110,15 @@ class BoxPushingEnvBase(MujocoEnv, utils.EzPickle):
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terminated = episode_end and infos['is_success']
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truncated = episode_end and not infos['is_success']
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if self.render_active and self.render_mode=='human':
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self.render()
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return obs, reward, terminated, truncated, infos
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def render(self):
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self.render_active = True
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return super().render()
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def reset_model(self):
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# rest box to initial position
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self.set_state(self.init_qpos_box_pushing, self.init_qvel_box_pushing)
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@ -60,7 +60,11 @@ class HalfCheetahEnvCustomXML(HalfCheetahEnv):
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default_camera_config=DEFAULT_CAMERA_CONFIG,
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**kwargs,
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)
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self.render_active = False
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def render(self):
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self.render_active = True
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return super().render()
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class HalfCheetahJumpEnv(HalfCheetahEnvCustomXML):
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"""
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@ -120,6 +124,9 @@ class HalfCheetahJumpEnv(HalfCheetahEnvCustomXML):
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'max_height': self.max_height
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}
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def _get_obs(self):
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@ -88,6 +88,12 @@ class HopperEnvCustomXML(HopperEnv):
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**kwargs,
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)
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self.render_active = False
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def render(self):
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self.render_active = True
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return super().render()
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class HopperJumpEnv(HopperEnvCustomXML):
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"""
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@ -201,6 +207,10 @@ class HopperJumpEnv(HopperEnvCustomXML):
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healthy=self.is_healthy,
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contact_dist=self.contact_dist or 0
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)
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def _get_obs(self):
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@ -140,6 +140,9 @@ class HopperJumpOnBoxEnv(HopperEnvCustomXML):
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truncated = self.current_step >= self.max_episode_steps and not terminated
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def _get_obs(self):
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@ -61,6 +61,8 @@ class HopperThrowEnv(HopperEnvCustomXML):
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exclude_current_positions_from_observation=exclude_current_positions_from_observation,
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**kwargs)
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self.render_active = False
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def step(self, action):
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self.current_step += 1
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self.do_simulation(action, self.frame_skip)
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@ -94,8 +96,15 @@ class HopperThrowEnv(HopperEnvCustomXML):
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}
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truncated = False
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def _get_obs(self):
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return np.append(super()._get_obs(), self.goal)
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@ -68,6 +68,7 @@ class HopperThrowInBasketEnv(HopperEnvCustomXML):
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reset_noise_scale=reset_noise_scale,
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exclude_current_positions_from_observation=exclude_current_positions_from_observation,
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**kwargs)
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self.render_active = False
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def step(self, action):
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@ -118,8 +119,15 @@ class HopperThrowInBasketEnv(HopperEnvCustomXML):
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}
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truncated = False
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def _get_obs(self):
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return np.append(super()._get_obs(), self.basket_x)
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@ -47,6 +47,8 @@ class ReacherEnv(MujocoEnv, utils.EzPickle):
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**kwargs
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)
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self.render_active = False
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def step(self, action):
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self._steps += 1
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@ -77,8 +79,15 @@ class ReacherEnv(MujocoEnv, utils.EzPickle):
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goal=self.goal if hasattr(self, "goal") else None
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)
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if self.render_active and self.render_mode=='human':
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self.render()
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return ob, reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def distance_reward(self):
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vec = self.get_body_com("fingertip") - self.get_body_com("target")
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return -self._reward_weight * np.linalg.norm(vec)
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@ -71,6 +71,8 @@ class TableTennisEnv(MujocoEnv, utils.EzPickle):
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observation_space=self.observation_space,
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**kwargs)
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self.render_active = False
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if ctxt_dim == 2:
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self.context_bounds = CONTEXT_BOUNDS_2DIMS
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elif ctxt_dim == 4:
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@ -158,8 +160,15 @@ class TableTennisEnv(MujocoEnv, utils.EzPickle):
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terminated, truncated = self._terminated, False
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if self.render_active and self.render_mode=='human':
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self.render()
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return self._get_obs(), reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def _contact_checker(self, id_1, id_2):
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for coni in range(0, self.data.ncon):
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con = self.data.contact[coni]
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@ -79,6 +79,8 @@ class Walker2dEnvCustomXML(Walker2dEnv):
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**kwargs,
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)
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self.render_active = False
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class Walker2dJumpEnv(Walker2dEnvCustomXML):
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"""
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@ -145,8 +147,15 @@ class Walker2dJumpEnv(Walker2dEnvCustomXML):
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}
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truncated = False
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if self.render_active and self.render_mode=='human':
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self.render()
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return observation, reward, terminated, truncated, info
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def render(self):
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self.render_active = True
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return super().render()
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def _get_obs(self):
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return np.append(super()._get_obs(), self.goal)
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