refactor(pipeline): Remove model card generation and streamline processor methods

- Eliminated the _generate_model_card method from RobotProcessor, which was responsible for generating README.md files from a template.
- Updated save_pretrained method to remove model card generation, focusing on serialization of processor definitions and parameters.
- Added default implementations for get_config, state_dict, load_state_dict, reset, and feature_contract methods in various processor classes to enhance consistency and usability.

tests/envs/test_envs.py

@@ -22,7 +22,7 @@ from gymnasium.utils.env_checker import check_env
 
 import lerobot
 from lerobot.envs.factory import make_env, make_env_config
-from lerobot.processor import RobotProcessor, TransitionKey, VanillaObservationProcessor
+from lerobot.envs.utils import preprocess_observation
 from tests.utils import require_env
 
 OBS_TYPES = ["state", "pixels", "pixels_agent_pos"]
@@ -48,12 +48,7 @@ def test_factory(env_name):
     cfg = make_env_config(env_name)
     env = make_env(cfg, n_envs=1)
     obs, _ = env.reset()
-
-    # Process observation using processor
-    obs_processor = RobotProcessor([VanillaObservationProcessor()])
-    transition = (obs, None, None, None, None, None, None)
-    processed_transition = obs_processor(transition)
-    obs = processed_transition[TransitionKey.OBSERVATION]
+    obs = preprocess_observation(obs)
 
     # test image keys are float32 in range [0,1]
     for key in obs:

tests/policies/test_policies.py

@@ -30,6 +30,7 @@ from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
 from lerobot.datasets.factory import make_dataset
 from lerobot.datasets.utils import cycle, dataset_to_policy_features
 from lerobot.envs.factory import make_env, make_env_config
+from lerobot.envs.utils import preprocess_observation
 from lerobot.optim.factory import make_optimizer_and_scheduler
 from lerobot.policies.act.modeling_act import ACTTemporalEnsembler
 from lerobot.policies.factory import (
@@ -39,7 +40,6 @@ from lerobot.policies.factory import (
 )
 from lerobot.policies.normalize import Normalize, Unnormalize
 from lerobot.policies.pretrained import PreTrainedPolicy
-from lerobot.processor import RobotProcessor, TransitionKey, VanillaObservationProcessor
 from lerobot.utils.random_utils import seeded_context
 from tests.artifacts.policies.save_policy_to_safetensors import get_policy_stats
 from tests.utils import DEVICE, require_cpu, require_env, require_x86_64_kernel
@@ -185,10 +185,7 @@ def test_policy(ds_repo_id, env_name, env_kwargs, policy_name, policy_kwargs):
     observation, _ = env.reset(seed=train_cfg.seed)
 
     # apply transform to normalize the observations
-    obs_processor = RobotProcessor([VanillaObservationProcessor()])
-    transition = (observation, None, None, None, None, None, None)
-    processed_transition = obs_processor(transition)
-    observation = processed_transition[TransitionKey.OBSERVATION]
+    observation = preprocess_observation(observation)
 
     # send observation to device/gpu
     observation = {key: observation[key].to(DEVICE, non_blocking=True) for key in observation}