60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
#!/usr/bin/env python
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# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import importlib
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import gymnasium as gym
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from omegaconf import DictConfig
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def make_env(cfg: DictConfig, n_envs: int | None = None) -> gym.vector.VectorEnv:
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"""Makes a gym vector environment according to the evaluation config.
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n_envs can be used to override eval.batch_size in the configuration. Must be at least 1.
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"""
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if n_envs is not None and n_envs < 1:
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raise ValueError("`n_envs must be at least 1")
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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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# batched version of the env that returns an observation of shape (b, c)
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env_cls = gym.vector.AsyncVectorEnv if cfg.eval.use_async_envs else gym.vector.SyncVectorEnv
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env = env_cls(
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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(n_envs if n_envs is not None else cfg.eval.batch_size)
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]
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)
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return env
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