提交记录:https://github.com/NM512/dreamerv3-torch/issues/18 [392996] model_loss 3.3 / model_grad_norm 9.6 / image_loss 1.4 / reward_loss 0.1 / cont_loss 0.0 / kl_free 1.0 / dyn_scale 0.5 / rep_scale 0.1 / dyn_loss 3.0 / rep_loss 3.0 / kl 3.0 / prior_ent 46.1 / post_ent...
= "nt" ): # compilation is not supported on windows self._wm = torch.compile(self._wm) self._task_behavior = torch.compile(self._task_behavior) reward = lambda f, s, a: self._wm.heads["reward"](f).mean() self._expl_behavior = dict( greedy=lambda: self._task_behavior, random...
https://github.com/NM512/dreamerv3-torch/issues/18 CreateAMind 2023/09/01 2200 开源世界模型dreamerv3 大杀器收集钻石不用GPT外挂 开源gpt模型数据算法 第一个在没有人类数据或课程的情况下从头开始在 Minecraft 中收集钻石的算法 CreateAMind 2023/09/01 5380 DeepMind Dreamer 在这个任务上栽了 测试代理华...
第三方 (pytorch):https://github.com/NM512/dreamerv3-torch Dreamer系列属于Model Based Reinforcement Learning中有代表性的工作之一(还有Zero系列),由DeepMind贡献。框架分两部分,World Model Learning和Actic-Critic Learning。 与实际的代码相比,论文中的配图过于简洁,以至于可以用抽象来形容了。为了方便与代码对照...
File "/home/jz/github/dreamerv3-torch-zdx/envs/wrappers.py", line 193, in reset obs = self._env.reset() File "/home/jz/github/dreamerv3-torch-zdx/envs/wrappers.py", line 53, in reset transition["reward"] = 0.0 IndexError: only integers, slices (:), ellipsis (...), numpy.new...
torch 2.6.0 torchaudio 2.6.0 torchvision 0.21.0 tqdm 4.67.1 typer 0.15.2 typing_extensions 4.12.2 tzdata 2025.1 urllib3 2.3.0 virtualenv 20.29.3 Werkzeug 3.1.3 wheel 0.35.1 wrapt 1.17.0 yarl 1.18.0 Reproduction script Run the tuned example foundhere ...
关注HyperAI超神经,了解更多有趣的 AI 算法、应用;还有定期更新教程,一起学习进步! 往期精彩内容: HyperAI超神经:机器学习在化学上的应用实例:90 后学霸博士 8 年进击战,用机器学习为化学工程研究叠 BUFF2 赞同 · 1 评论 HyperAI超神经:TorchServe 详解:5 步将模型部署到生产环境5 赞同 · 0 评论...
参考DeepMind Dreamer 在这个任务上栽了这个任务考验AI记忆能力的泛化 欢迎改进提升AI的记忆能力; {"step": 601000, "dataset_size": 300500.0, "train_return": 6.0, "train_length": 500.0, "train_episodes": 601.0} {"step": 704000, "dataset_size": 352000.0, "train_return": 6.0, "train_length"...
Tensor: """ 对称log变换: 能同时处理正值和负值 symlog(x) = sign(x) * log(|x| + 1) 使得对于大值/负值都能进行「压缩」, 缓解回归时的数值不稳定 """ return torch.sign(x) * torch.log(torch.abs(x) + 1.0 + eps) def symexp(x: torch.Tensor) -> torch.Tensor: """ symlog 的反...
) .env_runners(num_env_runners=1# https://github.com/ray-project/ray/issues/47527) .resources(num_gpus=1) )# Make sure you always set the framework to "torch"...# See https://docs.ray.io/en/latest/rllib/new-api-stack-migration-guide.htmlconfig.framework("torch")# ... and drop...