fix(pi0, pi05): stabilize torch.compile and expand test coverage (#3610)

* chore(gr00t): sync with #3606 for fixing gr00t config crash

* fix(pi0&pi05): fix graph break caused by deepcopy of past_key_values in sample_actions

* fix(pi0&pi05): fix frequent recompile caused by compute_layer_complete

* feat(test): add compile test and benchamrk for pi0 and pi05

* feat(test): add comprehensive testing for pi0 and pi05. Including processor, forward, sample action, etc.

src/lerobot/policies/groot/groot_n1.py

@@ -14,7 +14,7 @@
 # limitations under the License.
 
 from pathlib import Path
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 
 import numpy as np
 import torch
@@ -26,9 +26,14 @@ from lerobot.utils.import_utils import _transformers_available
 
 # Conditional import for type checking and lazy loading
 if TYPE_CHECKING or _transformers_available:
+    from huggingface_hub.dataclasses import strict
     from transformers import AutoConfig, AutoModel, PretrainedConfig, PreTrainedModel
     from transformers.feature_extraction_utils import BatchFeature
 else:
+
+    def strict(cls):
+        return cls
+
     AutoConfig = None
     AutoModel = None
     PretrainedConfig = object
@@ -173,19 +178,20 @@ N_COLOR_CHANNELS = 3
 
 
 # config
+@strict
 class GR00TN15Config(PretrainedConfig):
     model_type = "gr00t_n1_5"
 
-    backbone_cfg: dict
-    action_head_cfg: dict
-    action_horizon: int
-    action_dim: int
+    backbone_cfg: dict[str, Any] | None = None
+    action_head_cfg: dict[str, Any] | None = None
+    action_horizon: int = 0
+    action_dim: int = 0
     compute_dtype: str = "float32"
 
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-        for key, value in kwargs.items():
-            setattr(self, key, value)
+    def __post_init__(self, **kwargs):
+        self.backbone_cfg = {} if self.backbone_cfg is None else self.backbone_cfg
+        self.action_head_cfg = {} if self.action_head_cfg is None else self.action_head_cfg
+        super().__post_init__(**kwargs)
 
 
 # real model