BraxWrapper¶
- torchrl.envs.libs.brax.BraxWrapper(*args, _inplace_update=False, _batch_locked=True, **kwargs)[source]¶
Google Brax environment wrapper.
Examples
>>> env = brax.envs.get_environment("ant") >>> env = BraxWrapper(env) >>> env.set_seed(0) >>> td = env.reset() >>> td["action"] = env.action_spec.rand() >>> td = env.step(td) >>> print(td) TensorDict( fields={ action: Tensor(torch.Size([8]), dtype=torch.float32), done: Tensor(torch.Size([1]), dtype=torch.bool), next: TensorDict( fields={ observation: Tensor(torch.Size([87]), dtype=torch.float32)}, batch_size=torch.Size([]), device=cpu, is_shared=False), observation: Tensor(torch.Size([87]), dtype=torch.float32), reward: Tensor(torch.Size([1]), dtype=torch.float32), state: TensorDict(...)}, batch_size=torch.Size([]), device=cpu, is_shared=False) >>> print(env.available_envs) ['acrobot', 'ant', 'fast', 'fetch', ...]