naming works now for partial too

mlair/model_modules/branched_input_networks.py

@@ -74,10 +74,13 @@ class BranchedInputCNN(CNNfromConfig):  # pragma: no cover
 
     @staticmethod
     def _get_layer_name(layer: keras.layers, layer_kwargs: Union[dict, None], pos: int, branch: int = None):
+        if isinstance(layer, partial):
+            name = layer.args[0] if layer.func.__name__ == "Activation" else layer.func.__name__
+        else:
             name = layer.__name__
-        if "Conv" in layer.__name__ and isinstance(layer_kwargs, dict) and "kernel_size" in layer_kwargs:
+        if "Conv" in name and isinstance(layer_kwargs, dict) and "kernel_size" in layer_kwargs:
             name = name + "_" + "x".join(map(str, layer_kwargs["kernel_size"]))
-        if "Pooling" in layer.__name__ and isinstance(layer_kwargs, dict) and "pool_size" in layer_kwargs:
+        if "Pooling" in name and isinstance(layer_kwargs, dict) and "pool_size" in layer_kwargs:
             name = name + "_" + "x".join(map(str, layer_kwargs["pool_size"]))
         if branch is not None:
             name += f"_branch{branch + 1}"

mlair/model_modules/convolutional_networks.py

@@ -17,7 +17,7 @@ class CNNfromConfig(AbstractModelClass):
                    "sigmoid": partial(keras.layers.Activation, "sigmoid"),
                    "linear": partial(keras.layers.Activation, "linear"),
                    "prelu": partial(keras.layers.PReLU, alpha_initializer=keras.initializers.constant(value=0.25)),
-                   "leakyrelu": partial(keras.layers.LeakyReLU)}
+                   "leakyrelu": keras.layers.LeakyReLU}
     _initializer = {"tanh": "glorot_uniform", "sigmoid": "glorot_uniform", "linear": "glorot_uniform",
                     "relu": keras.initializers.he_normal(), "prelu": keras.initializers.he_normal()}
     _optimizer = {"adam": keras.optimizers.Adam, "sgd": keras.optimizers.SGD}
@@ -99,10 +99,13 @@ class CNNfromConfig(AbstractModelClass):
 
     @staticmethod
     def _get_layer_name(layer: keras.layers, layer_kwargs: Union[dict, None], pos: int, *args):
+        if isinstance(layer, partial):
+            name = layer.args[0] if layer.func.__name__ == "Activation" else layer.func.__name__
+        else:
             name = layer.__name__
-        if "Conv" in layer.__name__ and isinstance(layer_kwargs, dict) and "kernel_size" in layer_kwargs:
+        if "Conv" in name and isinstance(layer_kwargs, dict) and "kernel_size" in layer_kwargs:
             name = name + "_" + "x".join(map(str, layer_kwargs["kernel_size"]))
-        if "Pooling" in layer.__name__ and isinstance(layer_kwargs, dict) and "pool_size" in layer_kwargs:
+        if "Pooling" in name and isinstance(layer_kwargs, dict) and "pool_size" in layer_kwargs:
             name = name + "_" + "x".join(map(str, layer_kwargs["pool_size"]))
         name += f"_{pos + 1}"
         return name