43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import importlib
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import gymnasium as gym
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def make_env(cfg, num_parallel_envs=0) -> gym.Env | gym.vector.SyncVectorEnv:
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"""
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Note: When `num_parallel_envs > 0`, this function returns a `SyncVectorEnv` which takes batched action as input and
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returns batched observation, reward, terminated, truncated of `num_parallel_envs` items.
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"""
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kwargs = {
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"obs_type": "pixels_agent_pos",
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"render_mode": "rgb_array",
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"max_episode_steps": cfg.env.episode_length,
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"visualization_width": 384,
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"visualization_height": 384,
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}
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package_name = f"gym_{cfg.env.name}"
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try:
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importlib.import_module(package_name)
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except ModuleNotFoundError as e:
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print(
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f"{package_name} is not installed. Please install it with `pip install 'lerobot[{cfg.env.name}]'`"
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)
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raise e
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gym_handle = f"{package_name}/{cfg.env.task}"
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if num_parallel_envs == 0:
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# non-batched version of the env that returns an observation of shape (c)
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env = gym.make(gym_handle, disable_env_checker=True, **kwargs)
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else:
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# batched version of the env that returns an observation of shape (b, c)
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env = gym.vector.SyncVectorEnv(
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[
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lambda: gym.make(gym_handle, disable_env_checker=True, **kwargs)
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for _ in range(num_parallel_envs)
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]
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)
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return env
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