Add normalization processor and related components

- Introduced `NormalizationProcessor` to handle both observation normalization and action unnormalization.
- Added `ObservationNormalizer` and `ActionUnnormalizer` classes for specific normalization tasks.
- Updated `__init__.py` to include the new `NormalizationProcessor` in the module exports.
- Enhanced `ObservationProcessor` with registration in the `ProcessorStepRegistry` for better modularity.
- Created `RenameProcessor` for renaming keys in observations, improving flexibility in data processing.

src/lerobot/processor/rename_processor.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+import torch
+
+from lerobot.processor.pipeline import EnvTransition, ProcessorStepRegistry, TransitionIndex
+
+
+@dataclass
+@ProcessorStepRegistry.register(name="rename_processor")
+class RenameProcessor:
+    """Rename processor that renames keys in the observation."""
+
+    rename_map: dict[str, str] = field(default_factory=dict)
+
+    def __call__(self, transition: EnvTransition) -> EnvTransition:
+        observation = transition[TransitionIndex.OBSERVATION]
+        if observation is None:
+            return transition
+
+        processed_obs = {}
+        for key, value in observation.items():
+            if key in self.rename_map:
+                processed_obs[self.rename_map[key]] = value
+            else:
+                processed_obs[key] = value
+        return (
+            processed_obs,
+            transition[TransitionIndex.ACTION],
+            transition[TransitionIndex.REWARD],
+            transition[TransitionIndex.DONE],
+            transition[TransitionIndex.TRUNCATED],
+            transition[TransitionIndex.INFO],
+            transition[TransitionIndex.COMPLEMENTARY_DATA],
+        )
+
+    def get_config(self) -> dict[str, Any]:
+        return {"rename_map": self.rename_map}
+
+    def state_dict(self) -> dict[str, torch.Tensor]:
+        return {}
+
+    def load_state_dict(self, state: dict[str, torch.Tensor]) -> None:
+        pass