From 116059a43e299765b19446f3a3d64d85e55a4cbd Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 6 Jul 2025 19:31:23 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/lerobot/processor/normalize_processor.py | 14 +++++++-------
 tests/processor/test_batch_conversion.py     |  2 +-
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/src/lerobot/processor/normalize_processor.py b/src/lerobot/processor/normalize_processor.py
index 8e836dd50..cf653be1f 100644
--- a/src/lerobot/processor/normalize_processor.py
+++ b/src/lerobot/processor/normalize_processor.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass, field
-from typing import Any, Mapping, Optional, Set
+from typing import Any, Mapping
 
 import numpy as np
 import torch
@@ -51,12 +51,12 @@ class NormalizerProcessor:
     norm_map: dict[FeatureType, NormalizationMode]
 
     # Pre-computed statistics coming from dataset.meta.stats for instance.
-    stats: Optional[dict[str, dict[str, Any]]] = None
+    stats: dict[str, dict[str, Any]] | None = None
 
     # Explicit subset of keys to normalise. If ``None`` every key (except
     # "action") found in ``stats`` will be normalised. Using a ``set`` makes
     # membership checks O(1).
-    normalize_keys: Optional[Set[str]] = None
+    normalize_keys: set[str] | None = None
 
     eps: float = 1e-8
 
@@ -69,9 +69,9 @@ class NormalizerProcessor:
         features: dict[str, PolicyFeature],
         norm_map: dict[FeatureType, NormalizationMode],
         *,
-        normalize_keys: Optional[Set[str]] = None,
+        normalize_keys: set[str] | None = None,
         eps: float = 1e-8,
-    ) -> "NormalizerProcessor":
+    ) -> NormalizerProcessor:
         """Factory helper that pulls statistics from a :class:`LeRobotDataset`.
 
         The features and norm_map parameters are mandatory to match the design
@@ -195,7 +195,7 @@ class UnnormalizerProcessor:
 
     features: dict[str, PolicyFeature]
     norm_map: dict[FeatureType, NormalizationMode]
-    stats: Optional[dict[str, dict[str, Any]]] = None
+    stats: dict[str, dict[str, Any]] | None = None
     eps: float = 1e-8
 
     _tensor_stats: dict[str, dict[str, Tensor]] = field(default_factory=dict, init=False, repr=False)
@@ -208,7 +208,7 @@ class UnnormalizerProcessor:
         norm_map: dict[FeatureType, NormalizationMode],
         *,
         eps: float = 1e-8,
-    ) -> "UnnormalizerProcessor":
+    ) -> UnnormalizerProcessor:
         return cls(features=features, norm_map=norm_map, stats=dataset.meta.stats, eps=eps)
 
     def __post_init__(self):
diff --git a/tests/processor/test_batch_conversion.py b/tests/processor/test_batch_conversion.py
index 5b399a675..5cf8d3474 100644
--- a/tests/processor/test_batch_conversion.py
+++ b/tests/processor/test_batch_conversion.py
@@ -223,7 +223,7 @@ def test_complex_nested_observation():
     reconstructed_batch = _default_transition_to_batch(transition)
 
     # Check that all observation keys are preserved
-    original_obs_keys = {k for k in batch.keys() if k.startswith("observation.")}
+    original_obs_keys = {k for k in batch if k.startswith("observation.")}
     reconstructed_obs_keys = {k for k in reconstructed_batch.keys() if k.startswith("observation.")}
 
     assert original_obs_keys == reconstructed_obs_keys