gldrelu 1.1

Golden Ratio ReLU activation for Neural Networks

GldReLU

Golden Ratio ReLU (GldReLU) is a custom activation function for TensorFlow

Golden Ratio ReLU (GldReLU) is a custom activation function for TensorFlow based on the Golden Ratio constant. It can be used in deep learning models just like other activation, and is especially useful for deep networks in medical imaging and research applications.

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$$ GldReLU(x) = \max(0, (\phi - 1))\cdot x $$

where:

$$ \phi = \frac{1 + \sqrt{5}}{2} \approx 1.618 $$

so that:

$$ \phi - 1 \approx 0.618 $$

$$ \text{GldReLU}(x) = \begin{cases} 0.618 , x, & \text{if } x > 0 \[2mm] 0, & \text{if } x \leq 0 \end{cases} $$

Installation

pip install gldrelu

Usage Example

1️ Using "GldReLU" as a string (no function import needed)

import tensorflow as tf
import GldReLU  # registers GldReLU automatically

model = tf.keras.Sequential([
    tf.keras.layers.Dense(128, activation="GldReLU"),
    tf.keras.layers.Dense(10, activation="softmax")
])

model.summary()


###  Using the function directly

from GldReLU import GldReLU
import tensorflow as tf

model = tf.keras.Sequential([
    tf.keras.layers.Dense(128, activation=GldReLU),
    tf.keras.layers.Dense(10, activation="softmax")
])

model.summary()



If you use GldReLU in your research,  cite:

@article{lakshmi2025novel,
  title={A novel GldReLU activation function with enhanced RESNET50 for classification of X-ray images},
  author={Lakshmi, P Pankaja and Sivagami, M},
  journal={Neural Computing and Applications},
  volume={37},
  number={26},
  pages={21997--22028},
  year={2025},
  publisher={Springer}
}