Merge branch 'feat/add_relative_action_pi_models' into feat/mirror

src/lerobot/policies/factory.py

@@ -471,7 +471,7 @@ def make_policy(
     if not cfg.input_features:
         cfg.input_features = {key: ft for key, ft in features.items() if key not in cfg.output_features}
 
-    # Store action feature names on config for delta_exclude_joints support
+    # Store action feature names for delta_exclude_joints support
     if ds_meta is not None and hasattr(cfg, "action_feature_names"):
         action_names = ds_meta.features.get(ACTION, {}).get("names")
         if action_names is not None:

src/lerobot/policies/pi0/configuration_pi0.py

@@ -52,9 +52,9 @@ class PI0Config(PreTrainedConfig):
 
     # Delta actions: converts absolute actions to delta (relative to state).
     use_delta_actions: bool = False
-    # Joint names to exclude from delta conversion (kept as absolute).
+    # Joint names to exclude from delta (kept absolute). Empty list = all dims delta.
     delta_exclude_joints: list[str] = field(default_factory=lambda: ["gripper"])
-    # Populated at runtime by make_policy from dataset metadata.
+    # Populated at runtime from dataset metadata by make_policy.
     action_feature_names: list[str] | None = None
 
     # Real-Time Chunking (RTC) configuration

src/lerobot/policies/pi0/modeling_pi0.py

@@ -44,7 +44,6 @@ from lerobot.configs.policies import PreTrainedConfig
 from lerobot.policies.pi0.configuration_pi0 import DEFAULT_IMAGE_SIZE, PI0Config
 from lerobot.policies.pretrained import PreTrainedPolicy, T
 from lerobot.policies.rtc.modeling_rtc import RTCProcessor
-from lerobot.processor.delta_action_processor import to_absolute_actions, to_delta_actions
 from lerobot.utils.constants import (
     ACTION,
     OBS_LANGUAGE_ATTENTION_MASK,
@@ -1221,18 +1220,6 @@ class PI0Policy(PreTrainedPolicy):
         state = pad_vector(batch[OBS_STATE], self.config.max_state_dim)
         return state
 
-    def _build_delta_mask(self, action_dim: int) -> list[bool]:
-        """Build a boolean mask for delta action conversion.
-
-        Uses action_feature_names and delta_exclude_joints to determine which
-        dims get delta conversion. Falls back to all-True if names are unavailable.
-        """
-        names = self.config.action_feature_names
-        if names is None:
-            return [True] * action_dim
-        exclude = set(self.config.delta_exclude_joints)
-        return [n not in exclude for n in names]
-
     def prepare_action(self, batch):
         """Pad action"""
         actions = pad_vector(batch[ACTION], self.config.max_action_dim)
@@ -1272,9 +1259,6 @@ class PI0Policy(PreTrainedPolicy):
         original_action_dim = self.config.output_features[ACTION].shape[0]
         actions = actions[:, :, :original_action_dim]
 
-        if self.config.use_delta_actions:
-            actions = to_absolute_actions(actions, state, self._build_delta_mask(actions.shape[-1]))
-
         return actions
 
     def forward(self, batch: dict[str, Tensor], reduction: str = "mean") -> tuple[Tensor, dict]:
@@ -1292,9 +1276,6 @@ class PI0Policy(PreTrainedPolicy):
         state = self.prepare_state(batch)
         actions = self.prepare_action(batch)
 
-        if self.config.use_delta_actions:
-            actions = to_delta_actions(actions, state, self._build_delta_mask(actions.shape[-1]))
-
         # Compute loss
         losses = self.model.forward(images, img_masks, lang_tokens, lang_masks, state, actions)
 

src/lerobot/policies/pi0/processor_pi0.py

@@ -21,6 +21,7 @@ import torch
 from lerobot.configs.types import PipelineFeatureType, PolicyFeature
 from lerobot.policies.pi0.configuration_pi0 import PI0Config
 from lerobot.processor import (
+    AbsoluteActionsProcessorStep,
     AddBatchDimensionProcessorStep,
     ComplementaryDataProcessorStep,
     DeltaActionsProcessorStep,
@@ -127,7 +128,13 @@ def make_pi0_pre_post_processors(
         A tuple containing the configured pre-processor and post-processor pipelines.
     """
 
-    # Add remaining processors
+    delta_step = DeltaActionsProcessorStep(
+        enabled=config.use_delta_actions,
+        exclude_joints=getattr(config, "delta_exclude_joints", []),
+        action_names=getattr(config, "action_feature_names", None),
+    )
+
+    # OpenPI order: raw → delta → normalize → model → unnormalize → absolute
     input_steps: list[ProcessorStep] = [
         RenameObservationsProcessorStep(rename_map={}),  # To mimic the same processor as pretrained one
         AddBatchDimensionProcessorStep(),
@@ -139,18 +146,19 @@ def make_pi0_pre_post_processors(
             padding="max_length",
         ),
         DeviceProcessorStep(device=config.device),
+        delta_step,
         NormalizerProcessorStep(
             features={**config.input_features, **config.output_features},
             norm_map=config.normalization_mapping,
             stats=dataset_stats,
         ),
-        DeltaActionsProcessorStep(enabled=config.use_delta_actions),
     ]
 
     output_steps: list[ProcessorStep] = [
         UnnormalizerProcessorStep(
             features=config.output_features, norm_map=config.normalization_mapping, stats=dataset_stats
         ),
+        AbsoluteActionsProcessorStep(enabled=config.use_delta_actions, delta_step=delta_step),
         DeviceProcessorStep(device="cpu"),
     ]
 

src/lerobot/policies/pi05/configuration_pi05.py

@@ -52,9 +52,9 @@ class PI05Config(PreTrainedConfig):
 
     # Delta actions: converts absolute actions to delta (relative to state).
     use_delta_actions: bool = False
-    # Joint names to exclude from delta conversion (kept as absolute).
+    # Joint names to exclude from delta (kept absolute). Empty list = all dims delta.
     delta_exclude_joints: list[str] = field(default_factory=lambda: ["gripper"])
-    # Populated at runtime by make_policy from dataset metadata.
+    # Populated at runtime from dataset metadata by make_policy.
     action_feature_names: list[str] | None = None
 
     # Real-Time Chunking (RTC) configuration

src/lerobot/policies/pi05/modeling_pi05.py

@@ -44,12 +44,10 @@ from lerobot.configs.policies import PreTrainedConfig
 from lerobot.policies.pi05.configuration_pi05 import DEFAULT_IMAGE_SIZE, PI05Config
 from lerobot.policies.pretrained import PreTrainedPolicy, T
 from lerobot.policies.rtc.modeling_rtc import RTCProcessor
-from lerobot.processor.delta_action_processor import to_absolute_actions, to_delta_actions
 from lerobot.utils.constants import (
     ACTION,
     OBS_LANGUAGE_ATTENTION_MASK,
     OBS_LANGUAGE_TOKENS,
-    OBS_STATE,
     OPENPI_ATTENTION_MASK_VALUE,
 )
 
@@ -1201,14 +1199,6 @@ class PI05Policy(PreTrainedPolicy):
         actions = pad_vector(batch[ACTION], self.config.max_action_dim)
         return actions
 
-    def _build_delta_mask(self, action_dim: int) -> list[bool]:
-        """Build a boolean mask for delta action conversion."""
-        names = self.config.action_feature_names
-        if names is None:
-            return [True] * action_dim
-        exclude = set(self.config.delta_exclude_joints)
-        return [n not in exclude for n in names]
-
     @torch.no_grad()
     def select_action(self, batch: dict[str, Tensor]) -> Tensor:
         """Select a single action given environment observations."""
@@ -1242,10 +1232,6 @@ class PI05Policy(PreTrainedPolicy):
         original_action_dim = self.config.output_features[ACTION].shape[0]
         actions = actions[:, :, :original_action_dim]
 
-        if self.config.use_delta_actions:
-            state = pad_vector(batch[OBS_STATE], self.config.max_state_dim)
-            actions = to_absolute_actions(actions, state, self._build_delta_mask(actions.shape[-1]))
-
         return actions
 
     def forward(self, batch: dict[str, Tensor], reduction: str = "mean") -> tuple[Tensor, dict]:
@@ -1263,10 +1249,6 @@ class PI05Policy(PreTrainedPolicy):
 
         actions = self.prepare_action(batch)
 
-        if self.config.use_delta_actions:
-            state = pad_vector(batch[OBS_STATE], self.config.max_state_dim)
-            actions = to_delta_actions(actions, state, self._build_delta_mask(actions.shape[-1]))
-
         # Compute loss (no separate state needed for PI05)
         losses = self.model.forward(images, img_masks, tokens, masks, actions)
 

src/lerobot/policies/pi05/processor_pi05.py

@@ -25,6 +25,7 @@ from lerobot.configs.types import PipelineFeatureType, PolicyFeature
 from lerobot.policies.pi05.configuration_pi05 import PI05Config
 from lerobot.policies.pi05.modeling_pi05 import pad_vector
 from lerobot.processor import (
+    AbsoluteActionsProcessorStep,
     AddBatchDimensionProcessorStep,
     DeltaActionsProcessorStep,
     DeviceProcessorStep,
@@ -130,10 +131,19 @@ def make_pi05_pre_post_processors(
         A tuple containing the configured pre-processor and post-processor pipelines.
     """
 
-    # Add remaining processors
+    delta_step = DeltaActionsProcessorStep(
+        enabled=config.use_delta_actions,
+        exclude_joints=getattr(config, "delta_exclude_joints", []),
+        action_names=getattr(config, "action_feature_names", None),
+    )
+
+    # OpenPI order: raw → delta → normalize → model → unnormalize → absolute
+    # NOTE: NormalizerProcessorStep MUST come before Pi05PrepareStateTokenizerProcessorStep
+    # because the tokenizer step expects normalized state in [-1, 1] range for discretization
     input_steps: list[ProcessorStep] = [
         RenameObservationsProcessorStep(rename_map={}),  # To mimic the same processor as pretrained one
         AddBatchDimensionProcessorStep(),
+        delta_step,
         # NOTE: NormalizerProcessorStep MUST come before Pi05PrepareStateTokenizerProcessorStep
         # because the tokenizer step expects normalized state in [-1, 1] range for discretization
         NormalizerProcessorStep(
@@ -141,7 +151,6 @@ def make_pi05_pre_post_processors(
             norm_map=config.normalization_mapping,
             stats=dataset_stats,
         ),
-        DeltaActionsProcessorStep(enabled=config.use_delta_actions),
         Pi05PrepareStateTokenizerProcessorStep(max_state_dim=config.max_state_dim),
         TokenizerProcessorStep(
             tokenizer_name="google/paligemma-3b-pt-224",
@@ -156,6 +165,7 @@ def make_pi05_pre_post_processors(
         UnnormalizerProcessorStep(
             features=config.output_features, norm_map=config.normalization_mapping, stats=dataset_stats
         ),
+        AbsoluteActionsProcessorStep(enabled=config.use_delta_actions, delta_step=delta_step),
         DeviceProcessorStep(device="cpu"),
     ]
 

src/lerobot/processor/__init__.py

@@ -29,6 +29,7 @@ from .core import (
     TransitionKey,
 )
 from .delta_action_processor import (
+    AbsoluteActionsProcessorStep,
     DeltaActionsProcessorStep,
     MapDeltaActionToRobotActionStep,
     MapTensorToDeltaActionDictStep,
@@ -103,6 +104,7 @@ __all__ = [
     "make_default_teleop_action_processor",
     "make_default_robot_action_processor",
     "make_default_robot_observation_processor",
+    "AbsoluteActionsProcessorStep",
     "DeltaActionsProcessorStep",
     "MapDeltaActionToRobotActionStep",
     "MapTensorToDeltaActionDictStep",

src/lerobot/processor/delta_action_processor.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 
 from collections.abc import Sequence
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import Any
 
 import torch
@@ -188,33 +188,102 @@ class MapDeltaActionToRobotActionStep(RobotActionProcessorStep):
 @ProcessorStepRegistry.register("delta_actions_processor")
 @dataclass
 class DeltaActionsProcessorStep(ProcessorStep):
-    """Converts absolute actions to delta actions (action -= state) for all dimensions.
+    """Converts absolute actions to delta actions (action -= state) for masked dimensions.
 
     Mirrors OpenPI's DeltaActions transform. Applied during preprocessing so the model
     trains on relative offsets instead of absolute positions.
+    Caches the last seen state so a paired AbsoluteActionsProcessorStep can reverse
+    the conversion during postprocessing.
 
     Attributes:
         enabled: Whether to apply the delta conversion.
+        exclude_joints: Joint names to keep absolute (not converted to delta).
+        action_names: Action dimension names from dataset metadata, used to build
+            the mask from exclude_joints. If None, all dims are converted.
     """
 
     enabled: bool = False
+    exclude_joints: list[str] = field(default_factory=list)
+    action_names: list[str] | None = None
+    _last_state: torch.Tensor | None = field(default=None, init=False, repr=False)
+
+    def _build_mask(self, action_dim: int) -> list[bool]:
+        if not self.exclude_joints or self.action_names is None:
+            return [True] * action_dim
+        exclude = set(self.exclude_joints)
+        return [n not in exclude for n in self.action_names]
+
+    def __call__(self, transition: EnvTransition) -> EnvTransition:
+        observation = transition.get(TransitionKey.OBSERVATION, {})
+        state = observation.get(OBS_STATE) if observation else None
+
+        # Always cache state for the paired AbsoluteActionsProcessorStep
+        if state is not None:
+            self._last_state = state
+
+        if not self.enabled:
+            return transition
+
+        new_transition = transition.copy()
+        action = new_transition.get(TransitionKey.ACTION)
+        if action is None or state is None:
+            return new_transition
+
+        mask = self._build_mask(action.shape[-1])
+        new_transition[TransitionKey.ACTION] = to_delta_actions(action, state, mask)
+        return new_transition
+
+    def get_config(self) -> dict[str, Any]:
+        return {"enabled": self.enabled, "exclude_joints": self.exclude_joints}
+
+    def transform_features(
+        self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
+    ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
+        return features
+
+
+@ProcessorStepRegistry.register("absolute_actions_processor")
+@dataclass
+class AbsoluteActionsProcessorStep(ProcessorStep):
+    """Converts delta actions back to absolute actions (action += state) for all dimensions.
+
+    Mirrors OpenPI's AbsoluteActions transform. Applied during postprocessing so
+    predicted deltas are converted back to absolute positions for execution.
+    Reads the cached state from its paired DeltaActionsProcessorStep.
+
+    Attributes:
+        enabled: Whether to apply the absolute conversion.
+        delta_step: Reference to the paired DeltaActionsProcessorStep that caches state.
+    """
+
+    enabled: bool = False
+    delta_step: DeltaActionsProcessorStep | None = field(default=None, repr=False)
 
     def __call__(self, transition: EnvTransition) -> EnvTransition:
         if not self.enabled:
             return transition
 
+        if self.delta_step is None:
+            raise RuntimeError(
+                "AbsoluteActionsProcessorStep requires a paired DeltaActionsProcessorStep "
+                "but delta_step is None. Ensure delta_step is set when constructing the postprocessor."
+            )
+
+        if self.delta_step._last_state is None:
+            raise RuntimeError(
+                "AbsoluteActionsProcessorStep requires state from DeltaActionsProcessorStep "
+                "but no state has been cached. Ensure the preprocessor runs before the postprocessor."
+            )
+
         new_transition = transition.copy()
         action = new_transition.get(TransitionKey.ACTION)
         if action is None:
             return new_transition
 
-        observation = new_transition.get(TransitionKey.OBSERVATION, {})
-        state = observation.get(OBS_STATE) if observation else None
-        if state is None:
-            return new_transition
-
-        mask = [True] * action.shape[-1]
-        new_transition[TransitionKey.ACTION] = to_delta_actions(action, state, mask)
+        mask = self.delta_step._build_mask(action.shape[-1])
+        new_transition[TransitionKey.ACTION] = to_absolute_actions(
+            action, self.delta_step._last_state, mask
+        )
         return new_transition
 
     def get_config(self) -> dict[str, Any]:

src/lerobot/scripts/lerobot_train.py

@@ -248,7 +248,7 @@ def train(cfg: TrainPipelineConfig, accelerator: Accelerator | None = None):
         logging.info("use_delta_actions is enabled — recomputing action stats as delta (action - state)")
         from lerobot.datasets.dataset_tools import recompute_stats
 
-        exclude = getattr(cfg.policy, "delta_exclude_joints", ["gripper"])
+        exclude = getattr(cfg.policy, "delta_exclude_joints", [])
         recompute_stats(dataset, skip_image_video=True, delta_action=True, delta_exclude_joints=exclude)
 
     # Wait for all processes to finish policy creation before continuing