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#!/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 lerobot.common.envs.configs import AlohaEnv, EnvConfig, PushtEnv, XarmEnv
def make_env_config(env_type: str, **kwargs) -> EnvConfig:
if env_type == "aloha":
return AlohaEnv(**kwargs)
elif env_type == "pusht":
return PushtEnv(**kwargs)
elif env_type == "xarm":
return XarmEnv(**kwargs)
else:
raise ValueError(f"Policy type '{env_type}' is not available.")
def make_env(cfg: EnvConfig, n_envs: int = 1, use_async_envs: bool = False) -> gym.vector.VectorEnv | None:
"""Makes a gym vector environment according to the config.
Args:
cfg (EnvConfig): the config of the environment to instantiate.
n_envs (int, optional): The number of parallelized env to return. Defaults to 1.
use_async_envs (bool, optional): Whether to return an AsyncVectorEnv or a SyncVectorEnv. Defaults to
False.
Raises:
ValueError: if n_envs < 1
ModuleNotFoundError: If the requested env package is not installed
Returns:
gym.vector.VectorEnv: The parallelized gym.env instance.
"""
if n_envs < 1:
raise ValueError("`n_envs must be at least 1")
package_name = f"gym_{cfg.type}"
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.type}]'`")
raise e
gym_handle = f"{package_name}/{cfg.task}"
# batched version of the env that returns an observation of shape (b, c)
env_cls = gym.vector.AsyncVectorEnv if use_async_envs else gym.vector.SyncVectorEnv
env = env_cls(
[lambda: gym.make(gym_handle, disable_env_checker=True, **cfg.gym_kwargs) for _ in range(n_envs)]
)
return env
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