ActTensor: Activation Functions for TensorFlow

license releases

What is it?

ActTensor is a Python package that provides state-of-the-art activation functions which facilitate using them in Deep Learning projects in an easy and fast manner.

Why not using tf.keras.activations?

As you may know, TensorFlow only has a few defined activation functions and most importantly it does not include newly-introduced activation functions. Wrting another one requires time and energy; however, this package has most of the widely-used, and even state-of-the-art activation functions that are ready to use in your models.

Requirements

Install the required dependencies by running the following command:

conda env create -f environment.yml

Where to get it?

The source code is currently hosted on GitHub at: https://github.com/pouyaardehkhani/ActTensor

Binary installers for the latest released version are available at the Python Package Index (PyPI)

# PyPI
pip install ActTensor-tf

License

MIT

How to use?

import tensorflow as tf
import numpy as np
from ActTensor_tf import ReLU # name of the layer

functional api

inputs = tf.keras.layers.Input(shape=(28,28))
x = tf.keras.layers.Flatten()(inputs)
x = tf.keras.layers.Dense(128)(x)
# wanted class name
x = ReLU()(x)
output = tf.keras.layers.Dense(10,activation='softmax')(x)

model = tf.keras.models.Model(inputs = inputs,outputs=output)

sequential api

model = tf.keras.models.Sequential([tf.keras.layers.Flatten(),
                                    tf.keras.layers.Dense(128),
                                    # wanted class name
                                    ReLU(),
                                    tf.keras.layers.Dense(10, activation = tf.nn.softmax)])

NOTE:

The main functions of the activation layers are also available, but they may be defined by different names. Check this for more information.

from ActTensor_tf import relu

Activations

Classes and Functions are available in ActTensor_tf

ActTensor

Install / Use

README