Nn Python Packages

nn

A neural network library built on top of TensorFlow for quickly building deep learning models.

funcnotify

Get notified when your functions finish running

yann

yet another neural network library

atiny

Atiny is a gradient based PyTorch optimizer. Atiny uses half of Adam’s memory to achieve results that are not inferior to Adam.

fwu

FWU is a series of PyTorch-based neural network units.It has higher information utilization, prevents neuronal necrosis, and eliminates the need to add additionall activation functions.

cost2fitness

PyPI package for 1) conversion cost values (less is better) to fitness values (more is better) and vice versa, 2) using fast neural networks for forward propagation

flexible-neural-network

A simple and flexible python library that allows you to build custom Neural Networks where you can easily tweak parameters to change how your network behaves

torchcolor

Torchcolor is a lightweight Python package to enhance readability of printing and logging information into the terminal with Pytorch module coloring support.

aiinpy

neural network building, training, testing, (and inference!!)

orientloss

orientLoss is a classification loss function @pytorch. It less prone to overfitting compared to crossEntropy. Compatible with random vector/embeddings with direction-indicating categories、probabilistic、oneHot as target.

glassinit

glassInit is a way to initialize the parameters of a neural network layer @PyTorch. It is suitable for shortcut connections where tensor sizes need to be adjusted. The flow of information between forward and backward propagation is maximized while adjusting the tensor size.

numpynet

Convolutional Neural Network written from scratch using numpy with API similar to tensorflow.

picograd

A lightweight neural network framework implementation in Python

neat-python-gicminos

Fork of neat-python for small changes and maintentance. Feedback and PRs are welcome!

rrpad

ReplicationReflectionPad @Pytorch combines ReplicationPad and ReflectionPad to prevent errors from being reported due to small input sizes when using non-constant padding types.

fftloss

The fftLoss @PyTorch is a frequency domain loss function that prevents the problem of weak frequency components being suppressed by strong frequency components when using a regular loss function.