Hard limiting / threshold activation function in TensorFlow

Question

I\'m trying to implement a basic, binary Hopfield Network in TensorFlow 0.9. Unfortunately I\'m having a very hard time getting the activation function working. I\'m looking

Answer 1

a bit late, but if anyone needs it, I used this definition

def binary_activation(x):

    cond = tf.less(x, tf.zeros(tf.shape(x)))
    out = tf.where(cond, tf.zeros(tf.shape(x)), tf.ones(tf.shape(x)))

    return out

with x being a tensor

Answer 2

Just for the record, one can get the sign function via tf.sign. It outputs a float or integer (depending on the input) indicating the sign with -1 or 1. However, note that tf.sign(0) == 0!

For a hard limiting activation function, binary threshold activation function, Heaviside step function, see the other answer.