fixup device sel

src/eynollah/model_zoo/model_zoo.py

@@ -139,11 +139,21 @@ class EynollahModelZoo:
                 else:
                     assert device.startswith('GPU')
                     gpus = [gpus[int(device[3:])]]
+            else:
+                gpus = gpus[:1] # TF will always use first allowable
             tf.config.set_visible_devices(gpus, 'GPU')
             for device in gpus:
                 tf.config.experimental.set_memory_growth(device, True)
+                vendor_name = (
+                    tf.config.experimental.get_device_details(device)
+                    .get('device_name', 'unknown'))
                 cuda = True
-                self.logger.info("using GPU %s for model %s", device.name, model_category)
+                self.logger.info("using GPU %s (%s) for model %s",
+                                 device.name,
+                                 vendor_name,
+                                 model_category + (
+                                     "_patched" if patched else
+                                     "_resized" if resized else ""))
         except RuntimeError:
             self.logger.exception("cannot configure GPU devices")
         if not cuda:
@@ -166,12 +176,14 @@ class EynollahModelZoo:
             model = TrOCRProcessor.from_pretrained(model_path)
         else:
             try:
+                # avoid wasting VRAM on non-transformer models
                 model = load_model(model_path, compile=False)
             except Exception as e:
-                self.logger.exception(e)
+                self.logger.error(e)
                 model = load_model(
-                    model_path, compile=False, custom_objects={"PatchEncoder": PatchEncoder, "Patches": Patches}
-                )
+                    model_path, compile=False,
+                    custom_objects=dict(PatchEncoder=PatchEncoder,
+                                        Patches=Patches))
             model._name = model_category
             if resized:
                 model = wrap_layout_model_resized(model)

src/eynollah/predictor.py

@@ -170,7 +170,9 @@ class Predictor(mp.context.SpawnProcess):
 
     def load_model(self, *load_args, **load_kwargs):
         assert len(load_args)
-        self.name = '_'.join(list(load_args[:1]) + list(load_kwargs))
+        self.name = '_'.join(list(load_args[:1]) +
+                             list(key for key in load_kwargs
+                                  if key != 'device'))
         self.load_args = load_args
         self.load_kwargs = load_kwargs
         self.start() # call run() in subprocess