lerobot/lerobot/common/envs/factory.py

59 lines
2.0 KiB
Python

#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import gymnasium as gym
from omegaconf import DictConfig
def make_env(cfg: DictConfig, n_envs: int | None = None) -> gym.vector.VectorEnv | None:
"""Makes a gym vector environment according to the evaluation config.
n_envs can be used to override eval.batch_size in the configuration. Must be at least 1.
"""
if n_envs is not None and n_envs < 1:
raise ValueError("`n_envs must be at least 1")
if cfg.env.name == "real_world":
return
package_name = f"gym_{cfg.env.name}"
try:
importlib.import_module(package_name)
except ModuleNotFoundError as e:
print(
f"{package_name} is not installed. Please install it with `pip install 'lerobot[{cfg.env.name}]'`"
)
raise e
gym_handle = f"{package_name}/{cfg.env.task}"
gym_kwgs = dict(cfg.env.get("gym", {}))
if cfg.env.get("episode_length"):
gym_kwgs["max_episode_steps"] = cfg.env.episode_length
# batched version of the env that returns an observation of shape (b, c)
env_cls = gym.vector.AsyncVectorEnv if cfg.eval.use_async_envs else gym.vector.SyncVectorEnv
env = env_cls(
[
lambda: gym.make(gym_handle, disable_env_checker=True, **gym_kwgs)
for _ in range(n_envs if n_envs is not None else cfg.eval.batch_size)
]
)
return env