diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index f5cf7090..6e71849f 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -95,7 +95,7 @@ jobs:
 
       - name: Test with pytest
         run: |
-          pytest 'tests/test_control_robot.py::test_record_and_replay_and_policy[koch-True]' -v --cov=./lerobot --durations=0 \
+          pytest -sx 'tests/test_control_robot.py::test_record_and_replay_and_policy[koch-True]' -v --cov=./lerobot --durations=0 \
             -W ignore::DeprecationWarning:imageio_ffmpeg._utils:7 \
             -W ignore::UserWarning:torch.utils.data.dataloader:558 \
             -W ignore::UserWarning:gymnasium.utils.env_checker:247 \
diff --git a/lerobot/common/datasets/push_dataset_to_hub/aloha_hdf5_format.py b/lerobot/common/datasets/push_dataset_to_hub/aloha_hdf5_format.py
index de19c696..b5efc953 100644
--- a/lerobot/common/datasets/push_dataset_to_hub/aloha_hdf5_format.py
+++ b/lerobot/common/datasets/push_dataset_to_hub/aloha_hdf5_format.py
@@ -200,13 +200,13 @@ def to_hf_dataset(data_dict, video) -> Dataset:
     features["next.done"] = Value(dtype="bool", id=None)
     features["index"] = Value(dtype="int64", id=None)
 
-    # for key in data_dict:
-    #     if isinstance(data_dict[key], list):
-    #         print(key, len(data_dict[key]))
-    #     elif isinstance(data_dict[key], torch.Tensor):
-    #         print(key, data_dict[key].shape)
-    #     else:
-    #         print(key, data_dict[key])
+    for key in data_dict:
+        if isinstance(data_dict[key], list):
+            print(key, len(data_dict[key]))
+        elif isinstance(data_dict[key], torch.Tensor):
+            print(key, data_dict[key].shape)
+        else:
+            print(key, data_dict[key])
 
     data_dict["episode_index"] = data_dict["episode_index"].tolist()
     data_dict["frame_index"] = data_dict["frame_index"].tolist()
@@ -214,6 +214,14 @@ def to_hf_dataset(data_dict, video) -> Dataset:
     data_dict["next.done"] = data_dict["next.done"].tolist()
     data_dict["index"] = data_dict["index"].tolist()
 
+    for key in data_dict:
+        if isinstance(data_dict[key], list):
+            print(key, len(data_dict[key]))
+        elif isinstance(data_dict[key], torch.Tensor):
+            print(key, data_dict[key].shape)
+        else:
+            print(key, data_dict[key])
+
     hf_dataset = Dataset.from_dict(data_dict, features=Features(features))
     hf_dataset.set_transform(hf_transform_to_torch)
     return hf_dataset