Merge branch 'main' of...

Merge branch 'main' of git-ce.rwth-aachen.de:iop/workstreams/ws.a3/franka_wwl_demonstrator into main

TODOs

@@ -20,17 +20,15 @@ coscine_watchdog/coscine_client.py:185:    # TODO use update file rath then uplo
 coscine_watchdog/coscine_client.py:220:        ("datatype", "Datatype is missing"),  # , # TODO
 coscine_watchdog/coscine_client.py:221:        # ('dataset_type', 'Dataset type is missing') # TODO
 docs/index.rst:4:.. TODO change to two (or more) main pages + metadata. one on data generation one on ai. 
+dynamics_learning/benchmark_number_of_runs.py:141:        # TODO implement max number of trajectories used for benchmark training
 dynamics_learning/benchmark_number_of_runs.py:211:        # TODO load ITA model instead of dummy model
-dynamics_learning/benchmark_number_of_runs.py:240:        # TODO load LLT Data
-dynamics_learning/benchmark_number_of_runs.py:241:        # TODO load ITA model
-dynamics_learning/benchmark_number_of_runs.py:242:        # TODO set hyperparameters for LLT model based on ITA model with known hyperparameters
-dynamics_learning/benchmark_number_of_runs.py:256:        # TODO load LLT Data
-dynamics_learning/benchmark_number_of_runs.py:257:        # TODO load foundation model
-dynamics_learning/benchmark_number_of_runs.py:258:        # TODO set hyperparameters for LLT model based on foundation model
+dynamics_learning/benchmark_number_of_runs.py:262:        # TODO load ITA model instead of dummy model
 dynamics_learning/dynamics_learning/testing/__init__.py:256:        # somewhere FIXME: Daten scheinen zu kurz zu sein?
 dynamics_learning/dynamics_learning/testing/__init__.py:640:        # somewhere FIXME: Daten scheinen zu kurz zu sein?
 dynamics_learning/dynamics_learning/training/__init__.py:265:    )  # TODO implement another naming schema, as soon as a custom application profiles for the models is available in coscine.
 dynamics_learning/dynamics_learning/training/__init__.py:271:        f"{decision_metric}_val_loss"  # TODO implement custom coscine application profile for the models based on MITM base profile
+dynamics_learning/train_instance.py:38:    # TODO download data from ita / use data from ita
+dynamics_learning/train_instance.py:71:        # TODO save model and hyperparameters locally
 franka_lock_unlock/README.rst:1:.. TODO describe docker compose up for individual component
 src_jan/ROS/package.xml:16:  <license>TODO</license>
 src_jan/ROS/panda_auto_dynamics.py:5:# TODO DOCSTRING DOCUMENTATION