The active function in my CNN has the form:
abs(X)< tou f = 1.716tanh(0.667x)
x >= tou f = 1.716[tanh(2tou/3)+tanh'(2tou/3)(x-tou)]
x <= -tou f = 1.716[tanh(-2tou/3)+tanh'(-2tou/3)(x+tou)]
tou is a constant.
So, in TensorFlow it is possible to make your own activation function. I don't want to write it in C++ and recompile the whole of TensorFlow.
How can I use the function available in TensorFlow to achieve it?
In tensorflow it is easy to write your own activation function if it's include already existed ops, for your case you can use tf.case
f = tf.case({tf.less(tf.abs(x), tou): lambda: 7.716 * tf.tanh(0.667 * x),
tf.greater_equal(x, tou): lambda: 1.716 * tf.tanh(2 * tou / 3) + 1.716 * tf.tanh(2 * tou / 3) * (x - tou)},
default=lambda: 1.716 * tf.tanh(-2 * tou / 3) + 1.716 * tf.tanh(-2 * tou / 3) * (x + tou), exclusive=True)
