Increase UT code coverage to 76% (#1282)

* Increase UT code coverage to 74%

Signed-off-by: Sachidanand Alle <[email protected]>

* make test as parameterized

Signed-off-by: Sachidanand Alle <[email protected]>

* handle cpu/gpu

Signed-off-by: Sachidanand Alle <[email protected]>

* Add client api test

Signed-off-by: Sachidanand Alle <[email protected]>

---------

Signed-off-by: Sachidanand Alle <[email protected]>

Author: SachidanandAlle

monailabel/interfaces/app.py

@@ -30,8 +30,7 @@
 # added to support connecting to DICOM Store Google Cloud
 from dicomweb_client.ext.gcp.session_utils import create_session_from_gcp_credentials
 from dicomweb_client.session_utils import create_session_from_user_pass
-from monai.apps import download_and_extract, download_url
-from monai.data import partition_dataset
+from monai.apps import download_and_extract
 from timeloop import Timeloop
 
 from monailabel.config import settings
@@ -387,12 +386,6 @@ def scoring(self, request, datastore=None):
     def datastore(self) -> Datastore:
         return self._datastore
 
-    @staticmethod
-    def partition_datalist(datalist, val_split, shuffle=True):
-        if val_split > 0.0:
-            return partition_dataset(datalist, ratios=[(1 - val_split), val_split], shuffle=shuffle)
-        return datalist, []
-
     def train(self, request):
         """
         Run Training.  User APP has to implement this method to run training
@@ -595,18 +588,6 @@ def cleanup_sessions(self):
     def sessions(self):
         return self._sessions
 
-    @staticmethod
-    def download(resources):
-        if not resources:
-            return
-
-        for resource in resources:
-            if not os.path.exists(resource[0]):
-                os.makedirs(os.path.dirname(resource[0]), exist_ok=True)
-                logger.info(f"Downloading resource: {resource[0]} from {resource[1]}")
-                download_url(resource[1], resource[0])
-                time.sleep(1)
-
     def infer_wsi(self, request, datastore=None):
         model = request.get("model")
         if not model:

tests/unit/client/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

tests/unit/client/test_client.py

@@ -0,0 +1,113 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+from monailabel.client import MONAILabelClient
+
+
+# TODO:: Mock HTTP Server/Response
+class TestClient(unittest.TestCase):
+    def setUp(self) -> None:
+        pass
+
+    def tearDown(self) -> None:
+        pass
+
+    def test_info(self):
+        c = MONAILabelClient("http://127.0.0.1:8000/")
+        c.get_server_url()
+        c.set_server_url("http://127.0.0.1:8000")
+        try:
+            c.info()
+        except:
+            pass
+
+    def test_next_sample(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.next_sample("random")
+        except:
+            pass
+
+    def test_create_session(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.create_session("xyz", {"h": 1})
+        except:
+            pass
+
+    def test_get_session(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.get_session("xyzd")
+        except:
+            pass
+
+    def test_remove_session(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.remove_session("xyzd")
+        except:
+            pass
+
+    def test_upload_image(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.upload_image("xyzd", "1234")
+        except:
+            pass
+
+    def test_save_label(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.save_label("xyzd", "1234")
+        except:
+            pass
+
+    def test_infer(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.infer("model", "1234", {"xyz": 1})
+        except:
+            pass
+
+    def test_wsi_infer(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.wsi_infer("model", "1234", {"xyz": 1})
+        except:
+            pass
+
+    def test_train_start(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.train_start("model", {"xyz": 1})
+        except:
+            pass
+
+    def test_train_stop(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.train_stop()
+        except:
+            pass
+
+    def test_train_status(self):
+        try:
+            c = MONAILabelClient("http://127.0.0.1:8000/")
+            c.train_status()
+        except:
+            pass
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/unit/endpoints/test_batch_infer.py

@@ -17,7 +17,7 @@
 
 
 class EndPointScoring(BasicEndpointTestSuite):
-    def test_batch_infer(self):
+    def test_001_batch_infer(self):
         if not torch.cuda.is_available():
             return
 
@@ -26,12 +26,22 @@ def test_batch_infer(self):
         response = self.client.post(f"/batch/infer/{model}?images={images}&run_sync=true")
         assert response.status_code == 200
 
-    def test_status(self):
+    def test_002_status(self):
         self.client.get("/batch/infer/")
 
-    def test_stop(self):
+    def test_003_stop(self):
         self.client.delete("/batch/infer/")
 
+    def test_004_batch_infer(self):
+        if not torch.cuda.is_available():
+            return
+
+        model = "deepedit_seg"
+        images = "all"
+        params = {"max_workers": 2}
+        response = self.client.post(f"/batch/infer/{model}?images={images}&run_sync=true", json=params)
+        assert response.status_code == 200
+
 
 if __name__ == "__main__":
     unittest.main()

tests/unit/endpoints/test_infer_wsi.py

@@ -18,7 +18,7 @@
 
 
 class EndPointWSIInfer(BasicEndpointV4TestSuite):
-    def test_segmentation(self):
+    def test_segmentation_asap(self):
         if not torch.cuda.is_available():
             return
 
@@ -30,6 +30,30 @@ def test_segmentation(self):
         assert response.status_code == 200
         time.sleep(1)
 
+    def test_segmentation_dsa(self):
+        if not torch.cuda.is_available():
+            return
+
+        model = "segmentation_nuclei"
+        image = "JP2K-33003-1"
+        wsi = {"level": 0, "size": [2000, 2000], "pos": [2000, 4000], "max_workers": 1}
+
+        response = self.client.post(f"/infer/wsi/{model}?image={image}&output=dsa", json=wsi)
+        assert response.status_code == 200
+        time.sleep(1)
+
+    def test_segmentation_json(self):
+        if not torch.cuda.is_available():
+            return
+
+        model = "segmentation_nuclei"
+        image = "JP2K-33003-1"
+        wsi = {"level": 0, "size": [2000, 2000], "pos": [2000, 4000]}
+
+        response = self.client.post(f"/infer/wsi/{model}?image={image}&output=json", json=wsi)
+        assert response.status_code == 200
+        time.sleep(1)
+
 
 if __name__ == "__main__":
     unittest.main()

tests/unit/endpoints/test_train.py

@@ -17,7 +17,6 @@
 from .context import BasicBundleTestSuite, BasicDetectionBundleTestSuite, BasicEndpointV2TestSuite
 
 
-@unittest.skip
 class TestEndPointTrain(BasicEndpointV2TestSuite):
     def test_001_train(self):
         if not torch.cuda.is_available():
@@ -84,7 +83,6 @@ def test_005_stop(self):
         self.client.delete("/train/")
 
 
-@unittest.skip
 class TestBundleTrainTask(BasicBundleTestSuite):
     def test_spleen_bundle_train(self):
         if not torch.cuda.is_available():

tests/unit/interfaces/test_app.py

@@ -0,0 +1,109 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import unittest
+
+import torch
+from parameterized import parameterized
+
+from monailabel.config import settings
+from monailabel.interfaces.app import MONAILabelApp
+from monailabel.interfaces.tasks.batch_infer import BatchInferImageType
+from monailabel.interfaces.utils.app import app_instance
+
+
+class TestApp(unittest.TestCase):
+    app = None
+    base_dir = os.path.realpath(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))))
+    data_dir = os.path.join(base_dir, "tests", "data")
+
+    app_dir = os.path.join(base_dir, "sample-apps", "radiology")
+    studies = os.path.join(data_dir, "dataset", "local", "spleen")
+
+    @classmethod
+    def setUpClass(cls) -> None:
+        settings.MONAI_LABEL_APP_DIR = cls.app_dir
+        settings.MONAI_LABEL_STUDIES = cls.studies
+        settings.MONAI_LABEL_DATASTORE_AUTO_RELOAD = False
+
+        if torch.cuda.is_available():
+            cls.app: MONAILabelApp = app_instance(
+                app_dir=cls.app_dir,
+                studies=cls.studies,
+                conf={
+                    "preload": "true",
+                    "models": "segmentation_spleen",
+                },
+            )
+
+    @classmethod
+    def tearDownClass(cls) -> None:
+        pass
+
+    def test_app_init(self):
+        if not self.app:
+            return
+        self.app.on_init_complete()
+
+    def test_cleanup_sessions(self):
+        if not self.app:
+            return
+        self.app.cleanup_sessions()
+
+    def test_async_batch_infer(self):
+        if not self.app:
+            return
+
+        model = "segmentation_spleen"
+        params = {"max_workers": 2}
+
+        self.app.server_mode(True)
+        self.app.async_batch_infer(model, BatchInferImageType.IMAGES_ALL, params)
+
+        try:
+            self.app.server_mode(False)
+            self.app.async_batch_infer(model, BatchInferImageType.IMAGES_LABELED)
+        except:
+            pass
+
+    def test_async_train(self):
+        if not self.app:
+            return
+
+        model = "segmentation_spleen"
+        params = {"max_epochs": 1}
+
+        self.app.server_mode(True)
+        self.app.async_training(model, params)
+
+        try:
+            self.app.server_mode(False)
+            self.app.async_training(model, params)
+        except:
+            pass
+
+    @parameterized.expand(["xnat", "dsa", ""])
+    def test_init_datastores(self, r):
+        if not self.app:
+            return
+
+        try:
+            settings.MONAI_LABEL_DATASTORE = r
+            self.app.init_remote_datastore()
+        except:
+            pass
+        finally:
+            settings.MONAI_LABEL_DATASTORE = ""
+
+
+if __name__ == "__main__":
+    unittest.main()