diff --git a/examples/custom_train/sentinel-2a-rgbnir/cnn_on_rgbnir_torchgeo.py b/examples/custom_train/sentinel-2a-rgbnir/cnn_on_rgbnir_torchgeo.py
index a991888c..e5be483c 100644
--- a/examples/custom_train/sentinel-2a-rgbnir/cnn_on_rgbnir_torchgeo.py
+++ b/examples/custom_train/sentinel-2a-rgbnir/cnn_on_rgbnir_torchgeo.py
@@ -83,7 +83,7 @@ def main(cfg: DictConfig) -> None:
         test_data_point = test_data_point.resize_(1, *test_data_point.shape)
 
         prediction = model_loaded.predict_point(cfg.run.checkpoint_path,
-                                                test_data_point])
+                                                test_data_point)
         preds, probas = datamodule.predict_logits_to_class(prediction,
                                                            datamodule.get_test_dataset().unique_labels)
         datamodule.export_predict_csv(preds, probas,
diff --git a/malpolon/models/standard_prediction_systems.py b/malpolon/models/standard_prediction_systems.py
index 25932893..23373722 100644
--- a/malpolon/models/standard_prediction_systems.py
+++ b/malpolon/models/standard_prediction_systems.py
@@ -339,7 +339,7 @@ def predict_point(
         self.load_state_dict(ckpt['state_dict'])
         self.model.eval()
         with torch.no_grad():
-            if '__iter__' in dir(data):
+            if isinstance(data, (tuple, list, set, dict)):
                 for i, d in enumerate(data):
                     data[i] = d.to(device) if isinstance(d, torch.Tensor) else d
                 prediction = self.model(*data)
diff --git a/malpolon/tests/test_examples.py b/malpolon/tests/test_examples.py
index 71cda14c..813a0f56 100644
--- a/malpolon/tests/test_examples.py
+++ b/malpolon/tests/test_examples.py
@@ -258,7 +258,7 @@
     ],
 }
 
-# @pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
+@pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
 def test_train_inference_examples():
     ckpt_path = ''
     for expe_name, v in EXAMPLE_PATHS.items():
@@ -304,7 +304,7 @@ def test_train_inference_examples():
     print(f'\n{INFO}[INFO] Done. {RESET}')
 
 
-@pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
+# @pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
 def test_GLC22_examples():
     ckpt_path = ''
     for expe_name, v in GLC22_EXAMPLE_PATHS.items():
@@ -353,7 +353,7 @@ def test_GLC22_examples():
     print(f'\n{INFO}[INFO] Done. {RESET}')
 
 
-# @pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
+@pytest.mark.skip(reason="Slow or no guarantee of having the data available.")
 def test_GLC23_examples():
     ckpt_path = ''
     for expe_name, v in GLC23_EXAMPLE_PATHS.items():
@@ -402,7 +402,7 @@ def test_GLC23_examples():
     print(f'\n{INFO}[INFO] Done. {RESET}')
 
 
-@pytest.mark.skip(reason="Impossible for pytest to run because user input is needed to validate data download.")
+# @pytest.mark.skip(reason="Impossible for pytest to run because user input is needed to validate data download.")
 def test_GLC24_pre_extracted_examples():
     ckpt_path = ''
     for expe_name, v in GLC24_PRE_EXTRACTED_EXAMPLE_PATHS.items():
diff --git a/requirements_python3.10.txt b/requirements_python3.10.txt
index fd875ba5..5c8e07d1 100644
--- a/requirements_python3.10.txt
+++ b/requirements_python3.10.txt
@@ -9,7 +9,7 @@ ipykernel==6.18.2
 ipython==8.17.2
 jupyter==1.0.0
 jupyter-server==2.11.2
-jupyterlab==3.6.7
+jupyterlab==3.6.8
 kaggle==1.5.16
 lightning==2.0.9.post0
 Markdown==3.4.1
@@ -19,7 +19,7 @@ numpy==1.26.4
 odc-geo==0.3.2
 odc-stac==0.3.3
 omegaconf==2.3.0
-opencv-python==4.7.0.72
+opencv-python==4.8.1.78
 pandas==2.2.1
 Pillow==10.3.0
 planetary-computer==1.0.0
@@ -30,7 +30,7 @@ pyproj==3.6.1
 pystac==1.6.1
 pystac-client==0.5.1
 pytest==7.2.2
-pytorch-lightning==2.1.0
+pytorch-lightning==2.3.3
 PyYAML==6.0.1
 rasterio==1.3.8.post1
 scikit-learn==1.5.0
@@ -42,10 +42,10 @@ tensorboard==2.14.1
 protobuf==4.25
 tifffile==2022.10.10
 timm==0.9.2
-torch==2.1.0
+torch==2.2.0
 torchgeo==0.5.0
 torchmetrics==1.2.0
-torchvision==0.16.0
+torchvision==0.17.0
 tqdm==4.66.3
 verde==1.8.0
 yarl==1.9.2