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https://github.com/huggingface/lerobot.git
synced 2026-05-22 20:19:43 +00:00
refactor: revert policy changes, keep env-only camera mapping fixes
- Revert GR00T N1.5 default_factory/default changes (transformers compat) - Revert SmolVLA use_peft legacy field - Apply ruff formatting fixes - camera_name_mapping stays entirely in env/eval layer (no policy changes) Made-with: Cursor
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@@ -103,6 +103,7 @@ class EnvConfig(draccus.ChoiceRegistry, abc.ABC):
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try:
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try:
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from gymnasium.vector import AutoresetMode
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from gymnasium.vector import AutoresetMode
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vec = env_cls([_make_one for _ in range(n_envs)], autoreset_mode=AutoresetMode.SAME_STEP)
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vec = env_cls([_make_one for _ in range(n_envs)], autoreset_mode=AutoresetMode.SAME_STEP)
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except ImportError:
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except ImportError:
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vec = env_cls([_make_one for _ in range(n_envs)])
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vec = env_cls([_make_one for _ in range(n_envs)])
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@@ -176,13 +176,13 @@ N_COLOR_CHANNELS = 3
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@dataclass
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@dataclass
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class GR00TN15Config(PretrainedConfig):
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class GR00TN15Config(PretrainedConfig):
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model_type = "gr00t_n1_5"
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model_type = "gr00t_n1_5"
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backbone_cfg: dict = field(init=False, default_factory=dict, metadata={"help": "Backbone configuration."})
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backbone_cfg: dict = field(init=False, metadata={"help": "Backbone configuration."})
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action_head_cfg: dict = field(init=False, default_factory=dict, metadata={"help": "Action head configuration."})
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action_head_cfg: dict = field(init=False, metadata={"help": "Action head configuration."})
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action_horizon: int = field(init=False, default=0, metadata={"help": "Action horizon."})
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action_horizon: int = field(init=False, metadata={"help": "Action horizon."})
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action_dim: int = field(init=False, default=0, metadata={"help": "Action dimension."})
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action_dim: int = field(init=False, metadata={"help": "Action dimension."})
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compute_dtype: str = field(default="float32", metadata={"help": "Compute dtype."})
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compute_dtype: str = field(default="float32", metadata={"help": "Compute dtype."})
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def __init__(self, **kwargs):
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def __init__(self, **kwargs):
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@@ -109,7 +109,6 @@ class SmolVLAConfig(PreTrainedConfig):
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compile_model: bool = False # Whether to use torch.compile for model optimization
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compile_model: bool = False # Whether to use torch.compile for model optimization
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compile_mode: str = "max-autotune" # Torch compile mode
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compile_mode: str = "max-autotune" # Torch compile mode
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def __post_init__(self):
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def __post_init__(self):
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super().__post_init__()
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super().__post_init__()
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