tensorflowkerasneural-networkactivation-function

How to create a custom conditional activation function

I want to create custom activation function in TF2. The math is like this:

def sqrt_activation(x):
    if x >= 0:
        return tf.math.sqrt(x)
    else:
        return -tf.math.sqrt(-x)

The problem is that I can't compare x with 0 since x is a tensor. How to achieve this functionality?

Solution

  • You can skip the comparison by doing,

    def sqrt_activation(x):
    return tf.math.sign(x)*tf.math.sqrt(tf.abs(x))