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Refactor env to add key word arguments from config yaml (#223)

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Co-authored-by: Simon Alibert <75076266+aliberts@users.noreply.github.com>
This commit is contained in:
Remi
2024-05-30 13:45:22 +02:00
committed by GitHub
parent 2c2e4e14ed
commit 265b0ec44d
7 changed files with 59 additions and 36 deletions
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14
lerobot/common/envs/factory.py
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@@ -27,14 +27,6 @@ def make_env(cfg: DictConfig, n_envs: int | None = None) -> gym.vector.VectorEnv
if n_envs is not None and n_envs < 1:
raise ValueError("`n_envs must be at least 1")
kwargs = {
"obs_type": "pixels_agent_pos",
"render_mode": "rgb_array",
"max_episode_steps": cfg.env.episode_length,
"visualization_width": 384,
"visualization_height": 384,
}
package_name = f"gym_{cfg.env.name}"
try:
@@ -46,12 +38,16 @@ def make_env(cfg: DictConfig, n_envs: int | None = None) -> gym.vector.VectorEnv
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, **kwargs)
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)
]
)