[common] Move reusable files to new common package

src/mednet/scripts/saliency/completeness.py

@@ -203,9 +203,10 @@ def completeness(
     """
     import json
 
-    from ...engine.device import DeviceManager
+    from medbase.engine.device import DeviceManager
+    from medbase.utils.checkpointer import get_checkpoint_to_run_inference
+
     from ...engine.saliency.completeness import run
-    from ...utils.checkpointer import get_checkpoint_to_run_inference
 
     if device in ("cuda", "mps") and (parallel == 0 or parallel > 1):
         raise RuntimeError(

src/mednet/scripts/saliency/generate.py

@@ -168,9 +168,11 @@ def generate(
     The quality of saliency information depends on the saliency map
     algorithm and trained model.
     """
-    from ...engine.device import DeviceManager
+
+    from medbase.engine.device import DeviceManager
+    from medbase.utils.checkpointer import get_checkpoint_to_run_inference
+
     from ...engine.saliency.generator import run
-    from ...utils.checkpointer import get_checkpoint_to_run_inference
 
     logger.info(f"Output folder: {output_folder}")
     output_folder.mkdir(parents=True, exist_ok=True)

src/mednet/scripts/train.py

@@ -272,9 +272,10 @@ def train(
     import torch
     from lightning.pytorch import seed_everything
 
-    from ..engine.device import DeviceManager
-    from ..engine.trainer import run
-    from ..utils.checkpointer import get_checkpoint_to_resume_training
+    from medbase.engine.device import DeviceManager
+    from medbase.engine.trainer import run
+    from medbase.utils.checkpointer import get_checkpoint_to_resume_training
+
     from .utils import (
         device_properties,
         execution_metadata,

src/mednet/scripts/train_analysis.py

@@ -231,7 +231,7 @@ def train_analysis(
     import matplotlib.pyplot as plt
     from matplotlib.backends.backend_pdf import PdfPages
 
-    from ..utils.tensorboard import scalars_to_dict
+    from medbase.utils.tensorboard import scalars_to_dict
 
     data = scalars_to_dict(logdir)
 

tests/conftest.py

@@ -10,8 +10,9 @@ import numpy
 import numpy.typing
 import pytest
 import torch
-from mednet.data.split import JSONDatabaseSplit
-from mednet.data.typing import DatabaseSplit
+
+from medbase.data.split import JSONDatabaseSplit
+from medbase.data.typing import DatabaseSplit
 
 
 @pytest.fixture

tests/test_cli.py

@@ -204,11 +204,11 @@ def test_upload_help():
 @pytest.mark.slow
 @pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
 def test_train_pasa_montgomery(temporary_basedir):
-    from mednet.scripts.train import train
-    from mednet.utils.checkpointer import (
+    from medbase.utils.checkpointer import (
         CHECKPOINT_EXTENSION,
         _get_checkpoint_from_alias,
     )
+    from mednet.scripts.train import train
 
     runner = CliRunner()
 
@@ -260,11 +260,11 @@ def test_train_pasa_montgomery(temporary_basedir):
 @pytest.mark.slow
 @pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
 def test_train_pasa_montgomery_from_checkpoint(temporary_basedir):
-    from mednet.scripts.train import train
-    from mednet.utils.checkpointer import (
+    from medbase.utils.checkpointer import (
         CHECKPOINT_EXTENSION,
         _get_checkpoint_from_alias,
     )
+    from mednet.scripts.train import train
 
     runner = CliRunner()
 
@@ -337,12 +337,12 @@ def test_train_pasa_montgomery_from_checkpoint(temporary_basedir):
 
 @pytest.mark.slow
 @pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
-def test_predict_pasa_montgomery(temporary_basedir):
-    from mednet.scripts.predict import predict
-    from mednet.utils.checkpointer import (
+def test_predict_pasa_montgomery(temporary_basedir, datadir):
+    from medbase.utils.checkpointer import (
         CHECKPOINT_EXTENSION,
         _get_checkpoint_from_alias,
     )
+    from mednet.scripts.predict import predict
 
     runner = CliRunner()
 

tests/test_database_split.py

@@ -3,8 +3,7 @@
 # SPDX-License-Identifier: GPL-3.0-or-later
 """Test code for datasets."""
 
-from mednet.data.split import JSONDatabaseSplit
-
+from medbase.data.split import JSONDatabaseSplit
 
 def test_json_loading(datadir):
     # tests if we can build a simple JSON loader for the Iris Flower dataset

tests/test_image_utils.py

@@ -5,7 +5,8 @@
 
 import numpy
 import PIL.Image
-from mednet.data.image_utils import remove_black_borders
+
+from medbase.data.image_utils import remove_black_borders
 
 
 def test_remove_black_borders(datadir):

tests/test_summary.py

+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import unittest
+
+import mednet.config.models.pasa as pasa_config
+
+from medbase.utils.summary import summary
+
+
+class Tester(unittest.TestCase):
+    """Unit test for model architectures."""
+
+    def test_summary_driu(self):
+        model = pasa_config.model
+        s, param = summary(model)
+        self.assertIsInstance(s, str)
+        self.assertIsInstance(param, int)

tests/test_transforms.py

@@ -5,8 +5,9 @@
 
 import numpy
 import PIL.Image
-import torchvision.transforms.functional as F  # noqa: N812
-from mednet.data.augmentations import ElasticDeformation
+import torchvision.transforms.functional as F # noqa: N812
+
+from medbase.data.augmentations import ElasticDeformation
 
 
 def test_elastic_deformation(datadir):