bug-fix for l2_regularization not in use (#230)

* bug-fix for l2_regularization not in use
* removing not in use TF REGULARIZATION_LOSSES collection

rl_coach/architectures/tensorflow_components/general_network.py

@@ -222,7 +222,7 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
             'agent_parameters': self.ap, 'spaces': self.spaces, 'network_name': self.network_wrapper_name,
             'head_idx': head_idx, 'is_local': self.network_is_local})
 
-    def get_model(self):
+    def get_model(self) -> List:
         # validate the configuration
         if len(self.network_parameters.input_embedders_parameters) == 0:
             raise ValueError("At least one input type should be defined")
@@ -338,9 +338,18 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
 
                         head_count += 1
 
+        # model weights
+        self.weights = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=self.full_name)
+
         # Losses
         self.losses = tf.losses.get_losses(self.full_name)
-        self.losses += tf.losses.get_regularization_losses(self.full_name)
+
+        # L2 regularization
+        if self.network_parameters.l2_regularization != 0:
+            self.l2_regularization = tf.add_n([tf.nn.l2_loss(v) for v in self.weights]) \
+                                     * self.network_parameters.l2_regularization
+            self.losses += self.l2_regularization
+
         self.total_loss = tf.reduce_sum(self.losses)
         # tf.summary.scalar('total_loss', self.total_loss)
 
@@ -386,6 +395,8 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
             else:
                 raise Exception("{} is not a valid optimizer type".format(self.network_parameters.optimizer_type))
 
+        return self.weights
+
     def __str__(self):
         result = []