Resolve "release v1.4.0"

Closes #317 (closed)

mlair/model_modules/fully_connected_networks.py

@@ -5,6 +5,7 @@ from functools import reduce, partial
 
 from mlair.model_modules import AbstractModelClass
 from mlair.helpers import select_from_dict
+from mlair.model_modules.loss import var_loss, custom_loss
 
 import keras
 
@@ -64,7 +65,9 @@ class FCN(AbstractModelClass):
 
     _activation = {"relu": keras.layers.ReLU, "tanh": partial(keras.layers.Activation, "tanh"),
                    "sigmoid": partial(keras.layers.Activation, "sigmoid"),
-                   "linear": partial(keras.layers.Activation, "linear")}
+                   "linear": partial(keras.layers.Activation, "linear"),
+                   "selu": partial(keras.layers.Activation, "selu")}
+    _initializer = {"selu": keras.initializers.lecun_normal()}
     _optimizer = {"adam": keras.optimizers.adam, "sgd": keras.optimizers.SGD}
     _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad", "momentum", "nesterov"]
 
@@ -87,6 +90,7 @@ class FCN(AbstractModelClass):
         self.optimizer = self._set_optimizer(optimizer, **kwargs)
         self.layer_configuration = (n_layer, n_hidden)
         self._update_model_name()
+        self.kernel_initializer = self._initializer.get(activation, "glorot_uniform")
 
         # apply to model
         self.set_model()
@@ -126,11 +130,12 @@ class FCN(AbstractModelClass):
         x_in = keras.layers.Flatten()(x_input)
         n_layer, n_hidden = self.layer_configuration
         for layer in range(n_layer):
-            x_in = keras.layers.Dense(n_hidden)(x_in)
+            x_in = keras.layers.Dense(n_hidden, kernel_initializer=self.kernel_initializer)(x_in)
             x_in = self.activation()(x_in)
         x_in = keras.layers.Dense(self._output_shape)(x_in)
         out = self.activation_output()(x_in)
         self.model = keras.Model(inputs=x_input, outputs=[out])
 
     def set_compile_options(self):
-        self.compile_options = {"loss": [keras.losses.mean_squared_error], "metrics": ["mse", "mae"]}
+        self.compile_options = {"loss": [custom_loss([keras.losses.mean_squared_error, var_loss])],
+                                "metrics": ["mse", "mae", var_loss]}