MDL-67040 Regularization for the loss function

moodlehq · Jan 10, 2020 · 91db1e9 · 91db1e9
1 parent 608cac3
commit 91db1e9
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diff --git a/moodlemlbackend/VERSION b/moodlemlbackend/VERSION
@@ -1 +1 @@
-2.3.1
+2.4.0
diff --git a/moodlemlbackend/model/tensor.py b/moodlemlbackend/model/tensor.py
@@ -144,6 +144,11 @@ def build_graph(self, initial_weights=False):
 
             loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(
                 logits=self.probs, labels=self.y_))
+
+            regularizer = (tf.nn.l2_loss(W['input-hidden']) * 0.01) + \
+                (tf.nn.l2_loss(W['hidden-output']) * 0.01)
+            loss = tf.reduce_mean(loss + regularizer)
+
             tf.summary.scalar("loss", loss)
 
         with tf.name_scope('accuracy'):