fix: MuJoCo sim2sim default_angles match MotrixSim training
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@@ -222,8 +222,8 @@ class DreamWaQPPO(PPO):
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cv = std_r / (mean_r + 1e-6)
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cv = std_r / (mean_r + 1e-6)
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if not (0 <= cv < 1e6): # NaN 或 Inf → 保持当前 prob
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if not (0 <= cv < 1e6): # NaN 或 Inf → 保持当前 prob
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return
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return
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# CV → bootstrap 概率(CV 高→不稳定→多用 GT;上限 0.9 保证 CENet vel head 有梯度)
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# CV → bootstrap 概率(CENet vel head 通过 VAE loss 已有梯度,无需额外保护)
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self.actor._adaboot_prob = max(0.0, min(0.9, cv * 5.0))
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self.actor._adaboot_prob = max(0.0, min(1.0, cv * 5.0))
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def _compute_surrogate_loss(
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def _compute_surrogate_loss(
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self, actions_batch, actions_log_prob_batch,
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self, actions_batch, actions_log_prob_batch,
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@@ -136,7 +136,7 @@ class rslrl:
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runner.actor.class_name = (
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runner.actor.class_name = (
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"motrix_rl.rslrl.torch.models.cenet_actor:CENetActorModel")
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"motrix_rl.rslrl.torch.models.cenet_actor:CENetActorModel")
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runner.actor.hidden_dims = [512, 256, 128]
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runner.actor.hidden_dims = [512, 256, 128]
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runner.actor.init_noise_std = 0.5 # 与 fixed schedule 配合
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runner.actor.init_noise_std = 1.0 # 论文原值
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# Critic:标准 MLPModel,输入 privileged_obs
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# Critic:标准 MLPModel,输入 privileged_obs
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runner.critic.class_name = "MLPModel"
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runner.critic.class_name = "MLPModel"
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@@ -37,11 +37,12 @@ MAX_VX, MAX_VY, MAX_WZ = 1.0, 1.0, 1.0
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# DreamWaQ default joint angles — MUST match MuJoCo XML joint order:
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# DreamWaQ default joint angles — MUST match MuJoCo XML joint order:
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# qpos[7:19] = FR_hip,FR_thigh,FR_calf, FL_hip,FL_thigh,FL_calf, RR_hip,RR_thigh,RR_calf, RL_hip,RL_thigh,RL_calf
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# qpos[7:19] = FR_hip,FR_thigh,FR_calf, FL_hip,FL_thigh,FL_calf, RR_hip,RR_thigh,RR_calf, RL_hip,RL_thigh,RL_calf
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# 必须与 MotrixSim 训练的 default_angles 完全一致!
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DEFAULT_ANGLES = np.array([
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DEFAULT_ANGLES = np.array([
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-0.1, 0.8, -1.5, # FR
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0.0, 0.9, -1.8, # FR
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0.1, 0.8, -1.5, # FL
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0.0, 0.9, -1.8, # FL
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-0.1, 1.0, -1.5, # RR
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0.0, 0.9, -1.8, # RR
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0.1, 1.0, -1.5, # RL
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0.0, 0.9, -1.8, # RL
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], dtype=np.float32)
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], dtype=np.float32)
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