Fix redownloading issue (#54)

* Fix redownloading issue.

* Fix CI

kimm/__init__.py

@@ -13,4 +13,4 @@
 from kimm._src.utils.model_registry import list_models
 from kimm._src.version import version
 
-__version__ = "0.2.3"
+__version__ = "0.2.4"

kimm/_src/layers/learnable_affine.py

@@ -23,13 +23,13 @@ def __init__(self, scale_value=1.0, bias_value=0.0, **kwargs):
 
     def build(self, input_shape):
         self.scale = self.add_weight(
-            shape=(1,),
+            shape=(),
             initializer=lambda shape, dtype: ops.cast(self.scale_value, dtype),
             trainable=True,
             name="scale",
         )
         self.bias = self.add_weight(
-            shape=(1,),
+            shape=(),
             initializer=lambda shape, dtype: ops.cast(self.bias_value, dtype),
             trainable=True,
             name="bias",

kimm/_src/models/base_model.py

@@ -260,10 +260,11 @@ def get_config(self):
             "dropout_rate": self._dropout_rate,
             "classes": self._classes,
             "classifier_activation": self._classifier_activation,
-            "weights": self._weights,
             # feature extractor
             "feature_extractor": self._feature_extractor,
             "feature_keys": self._feature_keys,
+            # Set `self._weight` to `None` to avoid redownloading issue.
+            "weights": None,
         }
         return config
 

kimm/_src/models/models_test.py

@@ -159,6 +159,11 @@ def test_weights_invalid_string(self):
         ):
             SampleModel(weights="imagenet123")
 
+    def test_weights_none_in_config(self):
+        model = SampleModel()
+        config = model.get_config()
+        self.assertIsNone(config["weights"])
+
 
 # Test some small models
 

kimm/_src/version.py

@@ -1,6 +1,6 @@
 from kimm._src.kimm_export import kimm_export
 
-__version__ = "0.2.3"
+__version__ = "0.2.4"
 
 
 @kimm_export("kimm")