feat(processor): multiple improvements to the pipeline porting (#1749)

* [Port codebase pipeline] General fixes for RL and scripts (#1748)

* Refactor dataset configuration in documentation and codebase

- Updated dataset configuration keys from `dataset_root` to `root` and `num_episodes` to `num_episodes_to_record` for consistency.
- Adjusted replay episode handling by renaming `episode` to `replay_episode`.
- Enhanced documentation
- added specific processor to transform from policy actions to delta actions

* Added Robot action to tensor processor
Added new processor script for dealing with gym specific action processing

* removed RobotAction2Tensor processor; imrpoved choosing observations in actor

* nit in delta action

* added missing reset functions to kinematics

* Adapt teleoperate and replay to pipeline similar to record

* refactor(processors): move to inheritance (#1750)

* fix(teleoperator): improvements phone implementation (#1752)

* fix(teleoperator): protect shared state in phone implementation

* refactor(teleop): separate classes in phone

* fix: solve breaking changes (#1753)

* refactor(policies): multiple improvements (#1754)

* refactor(processor): simpler logic in device processor (#1755)

* refactor(processor): euclidean distance in delta action processor (#1757)

* refactor(processor): improvements to joint observations processor migration (#1758)

* refactor(processor): improvements to tokenizer migration (#1759)

* refactor(processor): improvements to tokenizer migration

* fix(tests): tokenizer tests regression from #1750

* fix(processors): fix float comparison and config in hil processors (#1760)

* chore(teleop): remove unnecessary callbacks in KeyboardEndEffectorTeleop (#1761)

* refactor(processor): improvements normalize pipeline migration (#1756)

* refactor(processor): several improvements normalize processor step

* refactor(processor): more improvements normalize processor

* refactor(processor): more changes to normalizer

* refactor(processor): take a different approach to DRY

* refactor(processor): final design

* chore(record): revert comment and continue deleted (#1764)

* refactor(examples): pipeline phone examples (#1769)

* refactor(examples): phone teleop + teleop script

* refactor(examples): phone replay + replay

* chore(examples): rename phone example files & folders

* feat(processor): fix improvements to the pipeline porting (#1796)

* refactor(processor): enhance tensor device handling in normalization process (#1795)

* refactor(tests): remove unsupported device detection test for complementary data (#1797)

* chore(tests): update ToBatchProcessor test (#1798)

* refactor(tests): remove in-place mutation tests for actions and complementary data in batch processor

* test(tests): add tests for action and task processing in batch processor

* add names for android and ios phone (#1799)

* use _tensor_stats in normalize processor (#1800)

* fix(normalize_processor): correct device reference for tensor epsilon handling (#1801)

* add point 5 add missing feature contracts (#1806)

* Fix PR comments 1452 (#1807)

* use key to determine image

* Address rest of PR comments

* use PolicyFeatures in transform_features

---------

Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>

---------

Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>

tests/processor/test_act_processor.py

@@ -23,7 +23,7 @@ import torch
 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
 from lerobot.constants import ACTION, OBS_STATE
 from lerobot.policies.act.configuration_act import ACTConfig
-from lerobot.policies.act.processor_act import make_act_processor
+from lerobot.policies.act.processor_act import make_act_pre_post_processors
 from lerobot.processor import (
     DeviceProcessor,
     NormalizerProcessor,
@@ -78,7 +78,7 @@ def test_make_act_processor_basic():
     config = create_default_config()
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Check processor names
     assert preprocessor.name == "robot_preprocessor"
@@ -102,7 +102,7 @@ def test_act_processor_normalization():
     config = create_default_config()
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Create test data
     observation = {OBS_STATE: torch.randn(7)}
@@ -131,7 +131,7 @@ def test_act_processor_cuda():
     config.device = "cuda"
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Create CPU data
     observation = {OBS_STATE: torch.randn(7)}
@@ -160,7 +160,7 @@ def test_act_processor_accelerate_scenario():
     config.device = "cuda:0"
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Simulate Accelerate: data already on GPU
     device = torch.device("cuda:0")
@@ -183,7 +183,7 @@ def test_act_processor_multi_gpu():
     config.device = "cuda:0"
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Simulate data on different GPU (like in multi-GPU training)
     device = torch.device("cuda:1")
@@ -203,7 +203,7 @@ def test_act_processor_without_stats():
     """Test ACT processor creation without dataset statistics."""
     config = create_default_config()
 
-    preprocessor, postprocessor = make_act_processor(config, dataset_stats=None)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, dataset_stats=None)
 
     # Should still create processors, but normalization won't have stats
     assert preprocessor is not None
@@ -223,7 +223,7 @@ def test_act_processor_save_and_load():
     config = create_default_config()
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     with tempfile.TemporaryDirectory() as tmpdir:
         # Save preprocessor
@@ -249,7 +249,7 @@ def test_act_processor_device_placement_preservation():
 
     # Test with CPU config
     config.device = "cpu"
-    preprocessor, _ = make_act_processor(config, stats)
+    preprocessor, _ = make_act_pre_post_processors(config, stats)
 
     # Process CPU data
     observation = {OBS_STATE: torch.randn(7)}
@@ -269,7 +269,7 @@ def test_act_processor_mixed_precision():
     stats = create_default_stats()
 
     # Modify the device processor to use float16
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Replace DeviceProcessor with one that uses float16
     for i, step in enumerate(preprocessor.steps):
@@ -294,7 +294,7 @@ def test_act_processor_batch_consistency():
     config = create_default_config()
     stats = create_default_stats()
 
-    preprocessor, postprocessor = make_act_processor(config, stats)
+    preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Test single sample (unbatched)
     observation = {OBS_STATE: torch.randn(7)}