Custom Activation Functions with tensorflow 2.8.2 about cvnn HOT 1 OPEN

For me 'modrelu' became functional again when I replaced it's code in cvnn/activations.py

from :
"
def modrelu(z: Tensor, b: float = 1., c: float = 1e-3) -> Tensor:
abs_z = tf.math.abs(z)
return tf.cast(tf.keras.activations.relu(abs_z + b), dtype=z.dtype) * z / tf.cast(abs_z + c, dtype=z.dtype)
"

to:
"
def modrelu(z: Tensor, b: float = 1., c: float = 1e-3) -> Tensor:
abs_z = tf.math.abs(z)
r_relu = tf.keras.activations.relu(abs_z + b)
return tf.complex(r_relu * tf.math.real(z) / (abs_z + c), r_relu * tf.math.imag(z) / (abs_z + c))
"

It might be less efficient but it solved the bug for me.

from cvnn.