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import pytest |
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import numpy as np |
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from easydict import EasyDict |
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from ding.utils import set_pkg_seed |
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from dizoo.evogym.envs import EvoGymEnv |
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@pytest.mark.envtest |
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@pytest.mark.parametrize('robot', ['speed_bot', 'random']) |
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def test_evogym_env_eval_episode_return(robot): |
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set_pkg_seed(1234, use_cuda=False) |
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env = EvoGymEnv(EasyDict({'env_id': 'Walker-v0', 'robot': robot, 'robot_dir': '../'})) |
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env.seed(1234) |
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env.reset() |
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action_dim = env.action_space.shape |
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eval_episode_return = np.array([0.], dtype=np.float32) |
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if robot == 'speed_bot': |
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assert env.observation_space.shape == (58, ) |
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assert action_dim == (10, ) |
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while True: |
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action = np.random.random(size=action_dim) |
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timestep = env.step(action) |
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eval_episode_return += timestep.reward |
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print("{}(dtype: {})".format(timestep.reward, timestep.reward.dtype)) |
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if timestep.done: |
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print( |
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"{}({}), {}({})".format( |
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timestep.info['eval_episode_return'], type(timestep.info['eval_episode_return']), |
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eval_episode_return, type(eval_episode_return) |
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) |
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) |
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assert abs(timestep.info['eval_episode_return'].item() - eval_episode_return.item()) / \ |
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abs(timestep.info['eval_episode_return'].item()) < 1e-5 |
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break |
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