MartinThoma · April 7, 2017 14:39 · Apr 7, 2017
diff --git a/custreg.py b/custreg.py
@@ -0,0 +1,34 @@
+import numpy as np
+from keras import backend as K
+from keras.models import Sequential
+from keras.layers import Dense, Activation
+
+
+def fro_norm(w):
+    """Frobenius norm."""
+    return K.sqrt(K.sum(K.square(K.abs(w))))
+
+
+def ort_reg(w):
+    """Orthogonal regularization."""
+    m = K.dot(K.transpose(w), w) - K.eye(w.shape)
+    return fro_norm(m)
+
+
+X = np.random.randn(100, 100)
+y = np.random.randint(2, size=(100, 1))
+
+model = Sequential()
+
+# apply regularization here. applies regularization to the
+# output (activation) of the layer
+model.add(Dense(32, input_shape=(100,),
+                activity_regularizer=ort_reg))
+model.add(Dense(1))
+model.add(Activation('softmax'))
+
+model.compile(loss="binary_crossentropy",
+              optimizer='sgd',
+              metrics=['accuracy'])
+
+model.fit(X, y, epochs=1, batch_size=32)
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