68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
from typing import Tuple, Type, Union, Optional, Callable
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import gymnasium as gym
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import numpy as np
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import pytest
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from gymnasium import make
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from gymnasium.core import ActType, ObsType
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import fancy_gym
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from fancy_gym import register
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ENV_IDS = ['fancy/Reacher5d-v0', 'dm_control/ball_in_cup-catch-v0', 'metaworld/reach-v2', 'Reacher-v2']
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class Object(object):
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pass
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class ToyEnv(gym.Env):
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observation_space = gym.spaces.Box(low=-1, high=1, shape=(1,), dtype=np.float64)
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action_space = gym.spaces.Box(low=-1, high=1, shape=(1,), dtype=np.float64)
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dt = 0.02
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def __init__(self, a: int = 0, b: float = 0.0, c: list = [], d: dict = {}, e: Object = Object()):
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self.a, self.b, self.c, self.d, self.e = a, b, c, d, e
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def reset(self, *, seed: Optional[int] = None, return_info: bool = False,
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options: Optional[dict] = None) -> Union[ObsType, Tuple[ObsType, dict]]:
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obs, options = np.array([-1]), {}
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return obs, options
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def step(self, action: ActType) -> Tuple[ObsType, float, bool, dict]:
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obs, reward, terminated, truncated, info = np.array([-1]), 1, False, False, {}
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return obs, reward, terminated, truncated, info
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def render(self, mode="human"):
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pass
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@pytest.fixture(scope="session", autouse=True)
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def setup():
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register(
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id=f'toy2-v0',
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entry_point='test.test_black_box:ToyEnv',
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max_episode_steps=50,
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)
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@pytest.mark.parametrize('env_id', ENV_IDS)
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@pytest.mark.parametrize('mp_type', ['ProMP', 'DMP', 'ProDMP'])
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def test_make_mp(env_id: str, mp_type: str):
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parts = env_id.split('-')
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assert len(parts) >= 2 and parts[-1].startswith('v'), 'Malformed env id, must end in -v{int}.'
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fancy_id = '-'.join(parts[:-1]+[mp_type, parts[-1]])
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make(fancy_id)
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def test_make_raw_toy():
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make('toy2-v0')
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@pytest.mark.parametrize('mp_type', ['ProMP', 'DMP', 'ProDMP'])
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def test_make_mp_toy(mp_type: str):
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fancy_id = '-'.join(['toy2', mp_type, 'v0'])
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make(fancy_id)
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