Tidy up yaml configs (#121)

lerobot/common/policies/act/configuration_act.py

@@ -112,15 +112,6 @@ class ActionChunkingTransformerConfig:
     dropout: float = 0.1
     kl_weight: float = 10.0
 
-    # ---
-    # TODO(alexander-soare): Remove these from the policy config.
-    batch_size: int = 8
-    lr: float = 1e-5
-    lr_backbone: float = 1e-5
-    weight_decay: float = 1e-4
-    grad_clip_norm: float = 10
-    utd: int = 1
-
     def __post_init__(self):
         """Input validation (not exhaustive)."""
         if not self.vision_backbone.startswith("resnet"):

lerobot/common/policies/diffusion/configuration_diffusion.py

@@ -119,15 +119,6 @@ class DiffusionConfig:
 
     # ---
     # TODO(alexander-soare): Remove these from the policy config.
-    batch_size: int = 64
-    grad_clip_norm: int = 10
-    lr: float = 1.0e-4
-    lr_scheduler: str = "cosine"
-    lr_warmup_steps: int = 500
-    adam_betas: tuple[float, float] = (0.95, 0.999)
-    adam_eps: float = 1.0e-8
-    adam_weight_decay: float = 1.0e-6
-    utd: int = 1
     use_ema: bool = True
     ema_update_after_step: int = 0
     ema_min_alpha: float = 0.0

lerobot/common/policies/factory.py

@@ -35,7 +35,7 @@ def make_policy(hydra_cfg: DictConfig, dataset_stats=None):
         from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy
 
         policy_cfg = _policy_cfg_from_hydra_cfg(DiffusionConfig, hydra_cfg)
-        policy = DiffusionPolicy(policy_cfg, hydra_cfg.offline_steps, dataset_stats)
+        policy = DiffusionPolicy(policy_cfg, hydra_cfg.training.offline_steps, dataset_stats)
         policy.to(get_safe_torch_device(hydra_cfg.device))
     elif hydra_cfg.policy.name == "act":
         from lerobot.common.policies.act.configuration_act import ActionChunkingTransformerConfig