Gym-fetch

1. now sample goal offsets for tracking targets once per episode (upon reset, saved in goal_offsets cache)
2. add the following sub-tasks in the table cleaning taskset for faster experiments

python
Fixing the objects in-place
register(id='Clean-i-fixed-v0', entry_point=vec_clean_env, kwargs=dict(
initial_qpos={'object1:joint': [1.35, 0.75, .45, 0, 0., 0., 0.]},
obj_reset={'object0': dict(pos=[1.35, 0.7, 0.42478468]),
'object1': dict(pos=[1.35, 0.8, 0.42478468]), },
goal_sampling={'object0': dict(target="box", range=0, ),
'object1': dict(target="object1", range=0, offset=[0, 0, 0]), },
), **kw)

register(id='Clean-ii-fixed-v0', entry_point=vec_clean_env, kwargs=dict(
obj_reset={'object0': dict(track='box', avoid=['gripper'], range=0, h=0.43456914),
'object1': dict(pos=[1.35, 0.8, 0.42478468]), },
goal_sampling={'object0': dict(target="box", range=0),
'object1': dict(target="object0", range=0), },
), **kw)

register(id='Clean-train-fixed-v0', entry_point=SampleEnv,
kwargs={'fetch:Clean-i-fixed-v0': 0.5, 'fetch:Clean-ii-fixed-v0': 0.5, }, **kw)

register(id='Clean-train-fixed-80-20-v0', entry_point=SampleEnv,
kwargs={'fetch:Clean-i-fixed-v0': 0.8, 'fetch:Clean-ii-fixed-v0': 0.2, }, **kw)

register(id='Clean-fixed-v0', entry_point=vec_clean_env, kwargs=dict(
obj_reset={'object0': dict(pos=[1.35, 0.7, 0.42478468]),
'object1': dict(pos=[1.35, 0.8, 0.42478468]), },
goal_sampling={'object0': dict(target="box", range=0),
'object1': dict(target="box", range=0), },
), **kw)

Task: Cleaning Table

**Primitives**
1. place A into box, both on table.
2. place B into box, with A already inside the box.

**Training Mixture**: 1 + 2, 50:50.

**Test**: Both A and B on table, and place both into the box. (edited)

| Name | Observation Spec | Goal Init/Comment | |
| ----------------- | ---------------- | ------- | ------|
| **Clean-i-v0** | achieved_goal: (6,)<br>desired_goal: (6,)<br>observation: (43,) | place the first object<br>into the box | |
| **Clean-ii-v0** | achieved_goal: (6,)<br>desired_goal: (6,)<br>observation: (43,) | place the second object<br>into the box while the<br>first one is already in there. | |
| **Clean-train-v0** | achieved_goal: (6,)<br>desired_goal: (6,)<br>observation: (43,) | 50/50 mixture of both | |
| **Clean-v0** | achieved_goal: (6,)<br>desired_goal: (6,)<br>observation: (43,) | Start with both on the<br>table, place both into<br>the box. | |

python
twin_box_envs = [
'fetch:Clean-i-v0',
'fetch:Clean-ii-v0',
'fetch:Clean-train-v0',
'fetch:Clean-v0',
'fetch:Clean-aside-i-v0',
'fetch:Clean-aside-ii-v0',
'fetch:Clean-aside-train-v0',
'fetch:Clean-aside-v0',
]

| **Clean-i-v0** | **distribution** | |
|:--------------:|:----------------:|:-:|
|  |  |  |
| **Clean-ii-v0** | **distribution** | |
|  |  |  |
| **Clean-train-v0** | **distribution** | |
|  |  |  |
| **Clean-v0** | **distribution** | |
|  |  |  |
| **Clean-aside-i-v0** | **distribution** | |
|  |  |  |
| **Clean-aside-ii-v0** | **distribution** | |
|  |  |  |
| **Clean-aside-train-v0** | **distribution** | |
|  |  |  |
| **Clean-aside-v0** | **distribution** | |
|  |  |  |

It turned out that goals that depend on the position of other objects are wrong right after `env.reset()` call, but they are good otherwise (for the rest of the trajectory).

See `rc7` for env list and installation guides.

write_protected: true
---
Cloning and Installing A Specific Version

**For those who do not use pip**, you can pull/checkout specific versions of the repository using a git `tag`. Github integrates with git, such that it shows tagged versions under the `<project-repo>/releases` URL. You can check out the releases for this repo at https://github.com/geyang/gym-fetch/releases. To pull a specific version, just run: