Harmonized return value of model inference method

model_server/ilastik.py

@@ -71,7 +71,7 @@ class IlastikPixelClassifierModel(IlastikImageToImageModel):
             [2, 1, 3, 0],
             [0, 1, 2, 3]
         )
-        return InMemoryDataAccessor(data=xycz)
+        return InMemoryDataAccessor(data=xycz), {'success': True}
 
 
 

model_server/model.py

@@ -47,9 +47,8 @@ class Model(ABC):
         pass
 
     @abstractmethod
-    def infer(self, img: GenericImageDataAccessor) -> (np.ndarray, dict): # return json describing inference result
-        if self.autoload:
-            self.load()
+    def infer(self, img: GenericImageDataAccessor) -> (object, dict): # return json describing inference result
+        pass
 
     def reload(self):
         self.load()
@@ -61,8 +60,8 @@ class ImageToImageModel(Model):
     """
 
     @abstractmethod
-    def infer(self, img) -> (GenericImageDataAccessor, dict):
-        super().infer(img)
+    def infer(self, img: GenericImageDataAccessor) -> (GenericImageDataAccessor, dict):
+        pass
 
 class DummyImageToImageModel(ImageToImageModel):
 
@@ -71,13 +70,13 @@ class DummyImageToImageModel(ImageToImageModel):
     def load(self):
         return True
 
-    def infer(self, img: GenericImageDataAccessor) -> GenericImageDataAccessor:
+    def infer(self, img: GenericImageDataAccessor) -> (GenericImageDataAccessor, dict):
         super().infer(img)
         w = img.shape_dict['X']
         h = img.shape_dict['Y']
         result = np.zeros([h, w], dtype='uint8')
         result[floor(0.25 * h) : floor(0.75 * h), floor(0.25 * w) : floor(0.75 * w)] = 255
-        return InMemoryDataAccessor(data=result)
+        return InMemoryDataAccessor(data=result), {'success': True}
 
 class Error(Exception):
     pass

model_server/workflow.py

@@ -28,7 +28,7 @@ def infer_image_to_image(fpi, model, where_output, **kwargs) -> dict:
 
     # run model inference
     # TODO: call this async / await and report out infer status to optional callback
-    outdata = model.infer(img)
+    outdata, _ = model.infer(img)
     dt_inf = time() - t0
 
     # TODO: assert outdata format

tests/test_ilastik.py

@@ -30,7 +30,7 @@ class TestIlastikPixelClassification(unittest.TestCase):
         input_img = InMemoryDataAccessor(data=np.random.rand(w, h, 1, 1))
 
         with self.assertRaises(AttributeError):
-            pxmap = model.infer(input_img)
+            pxmap , _= model.infer(input_img)
 
     def test_run_pixel_classifier_on_random_data(self):
         model = IlastikPixelClassifierModel({'project_file': ilastik['pixel_classifier']})
@@ -39,7 +39,7 @@ class TestIlastikPixelClassification(unittest.TestCase):
 
         input_img = InMemoryDataAccessor(data=np.random.rand(w, h, 1, 1))
 
-        pxmap = model.infer(input_img)
+        pxmap, _ = model.infer(input_img)
         self.assertEqual(pxmap.shape, (w, h, 2, 1))
 
     def test_run_pixel_classifier(self):
@@ -53,7 +53,7 @@ class TestIlastikPixelClassification(unittest.TestCase):
         self.assertEqual(mono_image.shape_dict['C'], 1)
         self.assertEqual(mono_image.shape_dict['Z'], 1)
 
-        pxmap = model.infer(mono_image)
+        pxmap, _ = model.infer(mono_image)
 
         self.assertEqual(pxmap.shape[0:2], cf.shape[0:2])
         self.assertEqual(pxmap.shape_dict['C'], 2)

tests/test_model.py

@@ -25,7 +25,7 @@ class TestCziImageFileAccess(unittest.TestCase):
 
     def test_czifile_is_correct_shape(self):
         model = DummyImageToImageModel()
-        img = model.infer(self.cf)
+        img, _ = model.infer(self.cf)
 
         w = czifile['w']
         h = czifile['h']