env-ssl-wrapper
One line turns any simulator's environment — gymnasium, dm_control, isaac, maniskill, pybullet, robosuite, pufferlib — into the same torch-native interface.
Install
pip install env-ssl-wrapper
Usage
import torch
from env_ssl_wrapper import compose_env
env = compose_env(
any_env, # any env from any sim
('tensor', dict(device='cpu')), # wrap with whatever you need
'done_tracker',
)
obs, info = env.reset() # torch.float32, batched
while not env.all_done:
actions = torch.randint(0, 2, (8,))
obs, reward, terminated, truncated, info = env.step(actions)
Works identically for every simulator.
Wrappers
Pass wrappers as strings (default config) or (name, dict) tuples (custom config), in any order.
| Wrapper | What it does |
|---|---|
standardize |
Normalizes any sim's step/reset signatures, vectorization, and autoreset into (obs, reward, terminated, truncated, info). Applied automatically. |
time_limit |
Caps episodes, sets truncated=True. ('time_limit', dict(max_timesteps=200)) |
done_tracker |
Tracks per-env episode_lengths, exposes env.all_done / env.needs_reset. |
auto_batch |
Gives single envs a leading batch dim: (4,) → (1, 4). |
action_transform |
Rescales actions from a canonical (0, 1) range to the env's bounds. |
tensor |
NumPy → torch on a device, torch actions → numpy for the sim. |
flatten_obs |
Flattens dict/tuple observations into a single vector. |
Every env emits the same contract: obs torch.float32, rewards torch.float32, terminated/truncated torch.bool. env.seed(n) works on every sim.
Mock sims
env_ssl_wrapper.mocks ships dependency-free stand-ins emulating each simulator's quirks (GymnasiumMockEnv, IsaacMockEnv, DMControlMockEnv, ...) for testing your code without installing the real sims.
from env_ssl_wrapper.mocks import IsaacMockEnv
env = compose_env(IsaacMockEnv(), 'tensor', 'done_tracker')
Tests
uv sync --extra test
uv run pytest tests/test_real_envs.py
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