-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathkitchen_lowdim_wrapper.py
49 lines (42 loc) · 1.42 KB
/
kitchen_lowdim_wrapper.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
from typing import List, Dict, Optional, Optional
import numpy as np
import gym
from gym.spaces import Box
from diffusion_policy.env.kitchen.base import KitchenBase
class KitchenLowdimWrapper(gym.Env):
def __init__(self,
env: KitchenBase,
init_qpos: Optional[np.ndarray]=None,
init_qvel: Optional[np.ndarray]=None,
render_hw = (240,360)
):
self.env = env
self.init_qpos = init_qpos
self.init_qvel = init_qvel
self.render_hw = render_hw
@property
def action_space(self):
return self.env.action_space
@property
def observation_space(self):
return self.env.observation_space
def seed(self, seed=None):
return self.env.seed(seed)
def reset(self):
if self.init_qpos is not None:
# reset anyway to be safe, not very expensive
_ = self.env.reset()
# start from known state
self.env.set_state(self.init_qpos, self.init_qvel)
obs = self.env._get_obs()
return obs
# obs, _, _, _ = self.env.step(np.zeros_like(
# self.action_space.sample()))
# return obs
else:
return self.env.reset()
def render(self, mode='rgb_array'):
h, w = self.render_hw
return self.env.render(mode=mode, width=w, height=h)
def step(self, a):
return self.env.step(a)