diff --git a/tests/test_cosypose_detector_training.py b/tests/test_cosypose_detector_training.py
index 15cedac7..915387da 100644
--- a/tests/test_cosypose_detector_training.py
+++ b/tests/test_cosypose_detector_training.py
@@ -1,16 +1,55 @@
+import functools
 import os
+import time
+from collections import defaultdict
 
 import numpy as np
 import pytest
+import torch
+import torch.distributed as dist
+import yaml
 from omegaconf import OmegaConf
+from torch.backends import cudnn
+from torch.hub import load_state_dict_from_url
+from torch.utils.data import DataLoader
+from torchnet.meter import AverageValueMeter
+from tqdm import tqdm
+
+from happypose.pose_estimators.cosypose.cosypose.config import EXP_DIR
+from happypose.pose_estimators.cosypose.cosypose.datasets.detection_dataset import (
+    DetectionDataset,
+)
 
+# Evaluation
+from happypose.pose_estimators.cosypose.cosypose.training.detector_models_cfg import (
+    check_update_config,
+    create_model_detector,
+)
+from happypose.pose_estimators.cosypose.cosypose.training.maskrcnn_forward_loss import (
+    h_maskrcnn,
+)
+from happypose.pose_estimators.cosypose.cosypose.training.train_detector import (
+    collate_fn,
+)
 from happypose.pose_estimators.cosypose.cosypose.utils.distributed import (
     get_world_size,
     init_distributed_mode,
     reduce_dict,
     sync_model,
 )
+from happypose.toolbox.datasets.datasets_cfg import make_scene_dataset
+from happypose.toolbox.datasets.scene_dataset import (
+    IterableMultiSceneDataset,
+    RandomIterableSceneDataset,
+)
+
+# from happypose.pose_estimators.cosypose.cosypose.utils.logging import get_logger
 from happypose.toolbox.utils.logging import get_logger
+from happypose.toolbox.utils.resources import (
+    get_cuda_memory,
+    get_gpu_memory,
+    get_total_memory,
+)
 
 logger = get_logger(__name__)
 
@@ -120,47 +159,6 @@ def test_detector_training(self):
         train_detector(self.cfg_detector)
 
 
-import functools
-import time
-from collections import defaultdict
-
-import torch
-import torch.distributed as dist
-import yaml
-from torch.backends import cudnn
-from torch.hub import load_state_dict_from_url
-from torch.utils.data import DataLoader
-from torchnet.meter import AverageValueMeter
-from tqdm import tqdm
-
-from happypose.pose_estimators.cosypose.cosypose.config import EXP_DIR
-from happypose.pose_estimators.cosypose.cosypose.datasets.detection_dataset import (
-    DetectionDataset,
-)
-
-# Evaluation
-from happypose.pose_estimators.cosypose.cosypose.training.detector_models_cfg import (
-    check_update_config,
-    create_model_detector,
-)
-from happypose.pose_estimators.cosypose.cosypose.training.maskrcnn_forward_loss import (
-    h_maskrcnn,
-)
-from happypose.pose_estimators.cosypose.cosypose.training.train_detector import (
-    collate_fn,
-)
-from happypose.pose_estimators.cosypose.cosypose.utils.logging import get_logger
-from happypose.toolbox.datasets.datasets_cfg import make_scene_dataset
-from happypose.toolbox.datasets.scene_dataset import (
-    IterableMultiSceneDataset,
-    RandomIterableSceneDataset,
-)
-from happypose.toolbox.utils.resources import (
-    get_cuda_memory,
-    get_gpu_memory,
-    get_total_memory,
-)
-
 cudnn.benchmark = True
 logger = get_logger(__name__)
 
diff --git a/tests/test_cosypose_pose_training.py b/tests/test_cosypose_pose_training.py
index 95ace819..f627faaf 100644
--- a/tests/test_cosypose_pose_training.py
+++ b/tests/test_cosypose_pose_training.py
@@ -1,16 +1,56 @@
+import functools
 import os
+import time
+from collections import defaultdict
 
 import numpy as np
 import pytest
+import torch
+import torch.distributed as dist
+import yaml
 from omegaconf import OmegaConf
+from torch.backends import cudnn
+from torch.utils.data import DataLoader
+from torchnet.meter import AverageValueMeter
+from tqdm import tqdm
 
+from happypose.pose_estimators.cosypose.cosypose.config import EXP_DIR
+from happypose.pose_estimators.cosypose.cosypose.training.pose_forward_loss import (
+    h_pose,
+)
+from happypose.pose_estimators.cosypose.cosypose.training.pose_models_cfg import (
+    check_update_config,
+    create_pose_model_cosypose,
+)
+from happypose.pose_estimators.cosypose.cosypose.training.train_pose import (
+    make_eval_bundle,
+    run_eval,
+)
 from happypose.pose_estimators.cosypose.cosypose.utils.distributed import (
     get_world_size,
     init_distributed_mode,
     reduce_dict,
     sync_model,
 )
+from happypose.toolbox.datasets.datasets_cfg import (
+    make_object_dataset,
+    make_scene_dataset,
+)
+from happypose.toolbox.datasets.pose_dataset import PoseDataset
+from happypose.toolbox.datasets.scene_dataset import (
+    IterableMultiSceneDataset,
+    RandomIterableSceneDataset,
+)
+from happypose.toolbox.lib3d.rigid_mesh_database import MeshDataBase
+from happypose.toolbox.renderer.panda3d_batch_renderer import Panda3dBatchRenderer
+
+# from happypose.pose_estimators.cosypose.cosypose.utils.logging import get_logger
 from happypose.toolbox.utils.logging import get_logger
+from happypose.toolbox.utils.resources import (
+    get_cuda_memory,
+    get_gpu_memory,
+    get_total_memory,
+)
 
 logger = get_logger(__name__)
 
@@ -209,48 +249,6 @@ def test_pose_training(self):
         train_pose(self.cfg_pose)
 
 
-import functools
-import time
-from collections import defaultdict
-
-import torch
-import torch.distributed as dist
-import yaml
-from torch.backends import cudnn
-from torch.utils.data import DataLoader
-from torchnet.meter import AverageValueMeter
-from tqdm import tqdm
-
-from happypose.pose_estimators.cosypose.cosypose.config import EXP_DIR
-from happypose.pose_estimators.cosypose.cosypose.training.pose_forward_loss import (
-    h_pose,
-)
-from happypose.pose_estimators.cosypose.cosypose.training.pose_models_cfg import (
-    check_update_config,
-    create_pose_model_cosypose,
-)
-from happypose.pose_estimators.cosypose.cosypose.training.train_pose import (
-    make_eval_bundle,
-    run_eval,
-)
-from happypose.pose_estimators.cosypose.cosypose.utils.logging import get_logger
-from happypose.toolbox.datasets.datasets_cfg import (
-    make_object_dataset,
-    make_scene_dataset,
-)
-from happypose.toolbox.datasets.pose_dataset import PoseDataset
-from happypose.toolbox.datasets.scene_dataset import (
-    IterableMultiSceneDataset,
-    RandomIterableSceneDataset,
-)
-from happypose.toolbox.lib3d.rigid_mesh_database import MeshDataBase
-from happypose.toolbox.renderer.panda3d_batch_renderer import Panda3dBatchRenderer
-from happypose.toolbox.utils.resources import (
-    get_cuda_memory,
-    get_gpu_memory,
-    get_total_memory,
-)
-
 cudnn.benchmark = True
 logger = get_logger(__name__)
 
diff --git a/tests/test_evaluation.py b/tests/test_evaluation.py
index a1ca9f2b..f8253c08 100644
--- a/tests/test_evaluation.py
+++ b/tests/test_evaluation.py
@@ -8,10 +8,7 @@
 # Third Party
 from omegaconf import OmegaConf
 
-from happypose.pose_estimators.megapose.config import (
-    LOCAL_DATA_DIR,
-    RESULTS_DIR,
-)
+from happypose.pose_estimators.megapose.config import LOCAL_DATA_DIR, RESULTS_DIR
 from happypose.pose_estimators.megapose.evaluation.bop import run_evaluation
 from happypose.pose_estimators.megapose.evaluation.eval_config import (
     BOPEvalConfig,
@@ -19,15 +16,11 @@
     FullEvalConfig,
     HardwareConfig,
 )
-from happypose.pose_estimators.megapose.evaluation.evaluation import (
-    get_save_dir,
-)
+from happypose.pose_estimators.megapose.evaluation.evaluation import get_save_dir
 from happypose.pose_estimators.megapose.scripts.run_full_megapose_eval import (
     create_eval_cfg,
 )
-from happypose.toolbox.utils.distributed import (
-    get_rank,
-)
+from happypose.toolbox.utils.distributed import get_rank
 from happypose.toolbox.utils.logging import get_logger
 
 logger = get_logger(__name__)
@@ -110,11 +103,11 @@ def test_config(self):
         assert (
             self.cfg["inference"]["n_pose_hypotheses"] == 5
         ), "Error: n_pose_hypotheses is not correct"
+        assert not self.cfg["inference"][
+            "run_depth_refiner"
+        ], "Error: run_depth_refiner is not correct"
         assert (
-            self.cfg["inference"]["run_depth_refiner"] == False
-        ), "Error: run_depth_refiner is not correct"
-        assert (
-            self.cfg["inference"]["depth_refiner"] == None
+            self.cfg["inference"]["depth_refiner"] is None
         ), "Error: depth_refiner is not correct"
         assert (
             self.cfg["inference"]["bsz_objects"] == 16
@@ -129,34 +122,30 @@ def test_config(self):
         assert (
             self.cfg["n_rendering_workers"] == 8
         ), "Error: n_rendering_workers is not correct"
-        assert self.cfg["n_frames"] == None, "Error: n_frames is not correct"
+        assert self.cfg["n_frames"] is None, "Error: n_frames is not correct"
         assert self.cfg["batch_size"] == 1, "Error: batch_size is not correct"
         assert (
             self.cfg["save_dir"] == f"{LOCAL_DATA_DIR}/results/ycbv-debug"
         ), "Error: save_dir is not correct"
         assert self.cfg["bsz_images"] == 256, "Error: bsz_images is not correct"
         assert self.cfg["bsz_objects"] == 16, "Error: bsz_objects is not correct"
+        assert self.cfg["skip_inference"], "Error: skip_inference is not correct"
+        assert self.cfg["skip_evaluation"], "Error: skip_evaluation is not correct"
         assert (
-            self.cfg["skip_inference"] == True
-        ), "Error: skip_inference is not correct"
-        assert (
-            self.cfg["skip_evaluation"] == True
-        ), "Error: skip_evaluation is not correct"
-        assert (
-            self.cfg["global_batch_size"] == None
+            self.cfg["global_batch_size"] is None
         ), "Error: global_batch_size is not correct"
         assert self.cfg["hardware"]["n_cpus"] == 10, "Error: n_cpus is not correct"
         assert self.cfg["hardware"]["n_gpus"] == 1, "Error: n_gpus is not correct"
-        assert self.cfg["debug"] == False, "Error: debug is not correct"
+        assert not self.cfg["debug"], "Error: debug is not correct"
         assert self.cfg["detection_coarse_types"] == [
             ["detector", "S03_grid"]
         ], "Error: detection_coarse_types is not correct"
         assert self.cfg["ds_names"] == ["ycbv.bop19"], "Error: ds_names is not correct"
-        assert self.cfg["run_bop_eval"] == True, "Error: run_bop_eval is not correct"
-        assert (
-            self.cfg["eval_coarse_also"] == False
-        ), "Error: eval_coarse_also is not correct"
-        assert self.cfg["convert_only"] == False, "Error: convert_only is not correct"
+        assert self.cfg["run_bop_eval"], "Error: run_bop_eval is not correct"
+        assert not self.cfg[
+            "eval_coarse_also"
+        ], "Error: eval_coarse_also is not correct"
+        assert not self.cfg["convert_only"], "Error: convert_only is not correct"
 
     # TODO
     # Rajouter un test pour save_dir ?