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fix: terrain start level 0, clear ep_report after consume

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This commit is contained in:
8x54zj-m
2026-06-30 15:43:02 +08:00
parent 6348cf72bc
commit 361502a8a5
3 changed files with 5 additions and 4 deletions
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2
motrix_envs/src/motrix_envs/locomotion/go1/dreamwaq.py
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@@ -410,7 +410,7 @@ class DreamWaQTask(Go1WalkTask):
all_indices = np.tile(np.arange(self._num_cols), self._num_rows) all_indices = np.tile(np.arange(self._num_cols), self._num_rows)
all_origins = self._make_origins(all_levels, all_indices) all_origins = self._make_origins(all_levels, all_indices)
self._terrain_origins = all_origins.reshape(self._num_rows, self._num_cols, 2) self._terrain_origins = all_origins.reshape(self._num_rows, self._num_cols, 2)
self._max_init_level = 5 self._max_init_level = 0 # 从平地起步，靠课程升级
if num_reset > 0 and self._init_done and state is not None and hasattr(state, 'info'): if num_reset > 0 and self._init_done and state is not None and hasattr(state, 'info'):
old_info = state.info old_info = state.info

5
motrix_rl/src/motrix_rl/rslrl/torch/wrap_vec_env.py
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@@ -127,9 +127,10 @@ class RslrlNpEnvWrap(VecEnv):
if "time_outs" in state.info: if "time_outs" in state.info:
extras["time_outs"] = torch.from_numpy(state.info["time_outs"]).to(self._device) extras["time_outs"] = torch.from_numpy(state.info["time_outs"]).to(self._device)
# 将 episode 各项奖励传入 TensorBoard # 将 episode 各项奖励传入 TensorBoard（消费后清除，防止重复上报）
if "ep_report" in state.info: if "ep_report" in state.info:
extras["episode"] = state.info["ep_report"] extras["episode"] = dict(state.info["ep_report"])
del state.info["ep_report"]
return obs, rewards, dones, extras return obs, rewards, dones, extras

2
motrix_rl/src/motrix_rl/tasks/go1.py
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@@ -135,7 +135,7 @@ class rslrl:
runner.actor.class_name = ( runner.actor.class_name = (
"motrix_rl.rslrl.torch.models.cenet_actor:CENetActorModel") "motrix_rl.rslrl.torch.models.cenet_actor:CENetActorModel")
runner.actor.hidden_dims = [512, 256, 128] runner.actor.hidden_dims = [512, 256, 128]
runner.actor.init_noise_std = 0.5 # 降噪声先学站稳，再探索行走 runner.actor.init_noise_std = 1.0 # 上游原值
# Critic：标准 MLPModel，输入 privileged_obs # Critic：标准 MLPModel，输入 privileged_obs
runner.critic.class_name = "MLPModel" runner.critic.class_name = "MLPModel"