State of the Art Neural Networks for Deep Learning

Related tags

Deep Learningdeep-neural-networksdeep-learningpython3recurrent-neural-networksneural-networksartificial-neural-networksfeedforward-neural-networkconvolutional-neural-networkstensorflow2
Overview

pyradox

This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2

Installation

pip install git+https://github.com/Ritvik19/pyradox.git

Usage

Modules

Module Description Input Shape Output Shape Usage
Rescale A layer that rescales the input: x_out = (x_in -mu) / sigma Arbitrary Same shape as input check here
Convolution 2D Applies 2D Convolution followed by Batch Normalization (optional) and Dropout (optional) 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Densely Connected Densely Connected Layer followed by Batch Normalization (optional) and Dropout (optional) 2D tensor with shape (batch_size, input_dim) 2D tensor with shape (batch_size, n_units) check here
DenseNet Convolution Block A Convolution block for DenseNets 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
DenseNet Convolution Block A Convolution block for DenseNets 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
DenseNet Transition Block A Transition block for DenseNets 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Dense Skip Connection Implementation of a skip connection for densely connected layer 2D tensor with shape (batch_size, input_dim) 2D tensor with shape (batch_size, n_units) check here
VGG Module Implementation of VGG Modules with slight modifications, Applies multiple 2D Convolution followed by Batch Normalization (optional), Dropout (optional) and MaxPooling 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inception Conv Implementation of 2D Convolution Layer for Inception Net, Convolution Layer followed by Batch Normalization, Activation and optional Dropout 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inception Block Implementation on Inception Mixing Block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Xception Block A customised implementation of Xception Block (Depthwise Separable Convolutions) 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net Block Implementation of Efficient Net Block (Depthwise Separable Convolutions) 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Conv Skip Connection Implementation of Skip Connection for Convolution Layer 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net Block Customized Implementation of ResNet Block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net V2 Block Customized Implementation of ResNetV2 Block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res NeXt Block Customized Implementation of ResNeXt Block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inception Res Net Conv 2D Implementation of Convolution Layer for Inception Res Net: Convolution2d followed by Batch Norm 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inception Res Net Block Implementation of Inception-ResNet block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) block 8 Block 17 Block 35
NAS Net Separable Conv Block Adds 2 blocks of Separable Conv Batch Norm 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
NAS Net Adjust Block Adjusts the input previous path to match the shape of the input
NAS Net Normal A Cell Normal cell for NASNet-A
NAS Net Reduction A Cell Reduction cell for NASNet-A
Mobile Net Conv Block Adds an initial convolution layer with batch normalization and activation 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Mobile Net Depth Wise Conv Block Adds a depthwise convolution block. A depthwise convolution block consists of a depthwise conv, batch normalization, activation, pointwise convolution, batch normalization and activation 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inverted Res Block Adds an Inverted ResNet block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
SEBlock Adds a Squeeze Excite Block 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here

ConvNets

Module Description Input Shape Output Shape Usage
Generalized Dense Nets A generalization of Densely Connected Convolutional Networks (Dense Nets) 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Densely Connected Convolutional Network 121 A modified implementation of Densely Connected Convolutional Network 121 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Densely Connected Convolutional Network 169 A modified implementation of Densely Connected Convolutional Network 169 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Densely Connected Convolutional Network 201 A modified implementation of Densely Connected Convolutional Network 201 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Generalized VGG A generalization of VGG network 4D tensor with shape (batch_shape, rows, cols, channels) 4D or 2D tensor usage 1 usage 2
VGG 16 A modified implementation of VGG16 network 4D tensor with shape (batch_shape, rows, cols, channels) 2D tensor with shape (batch_shape, new_dim) usage 1 usage 2
VGG 19 A modified implementation of VGG19 network 4D tensor with shape (batch_shape, rows, cols, channels) 2D tensor with shape (batch_shape, new_dim) usage 1 usage 2
Inception V3 Customized Implementation of Inception Net 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Generalized Xception Generalized Implementation of XceptionNet (Depthwise Separable Convolutions) 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Xception Net A Customised Implementation of XceptionNet 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net Generalized Implementation of Effiecient Net 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B0 Customized Implementation of Efficient Net B0 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B1 Customized Implementation of Efficient Net B1 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B2 Customized Implementation of Efficient Net B2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B3 Customized Implementation of Efficient Net B3 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B4 Customized Implementation of Efficient Net B4 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B5 Customized Implementation of Efficient Net B5 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B6 Customized Implementation of Efficient Net B6 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Efficient Net B7 Customized Implementation of Efficient Net B7 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net Customized Implementation of Res Net 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 50 Customized Implementation of Res Net 50 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 101 Customized Implementation of Res Net 101 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 152 Customized Implementation of Res Net 152 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net V2 Customized Implementation of Res Net V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 50 V2 Customized Implementation of Res Net 50 V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 101 V2 Customized Implementation of Res Net 101 V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res Net 152 V2 Customized Implementation of Res Net 152 V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res NeXt Customized Implementation of Res NeXt 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res NeXt 50 Customized Implementation of Res NeXt 50 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res NeXt 101 Customized Implementation of Res NeXt 101 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Res NeXt 152 Customized Implementation of Res NeXt 152 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
Inception Res Net V2 Customized Implementation of Inception Res Net V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
NAS Net Generalised Implementation of NAS Net 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
NAS Net Mobile Customized Implementation of NAS Net Mobile 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
NAS Net Large Customized Implementation of NAS Net Large 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) check here
MobileNet Customized Implementation of MobileNet 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) usage 1 usage 2
Mobile Net V2 Customized Implementation of Mobile Net V2 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) usage 1 usage 2
Mobile Net V3 Customized Implementation of Mobile Net V3 4D tensor with shape (batch_shape, rows, cols, channels) 4D tensor with shape (batch_shape, new_rows, new_cols, new_channels) usage 1 usage 2

DenseNets

Module Description Input Shape Output Shape Usage
Densely Connected Network Network of Densely Connected Layers followed by Batch Normalization (optional) and Dropout (optional) 2D tensor with shape (batch_size, input_dim) 2D tensor with shape (batch_size, new_dim) check here
Densely Connected Resnet Network of skip connections for densely connected layer 2D tensor with shape (batch_size, input_dim) 2D tensor with shape (batch_size, new_dim) check here
You might also like...
State-of-the-art data augmentation search algorithms in PyTorch
State-of-the-art data augmentation search algorithms in PyTorch

MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal

null 43 Dec 12, 2022
A selection of State Of The Art research papers (and code) on human locomotion (pose + trajectory) prediction (forecasting)

A selection of State Of The Art research papers (and code) on human trajectory prediction (forecasting). Papers marked with [W] are workshop papers.

Karttikeya Manglam 40 Nov 18, 2022
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

Miles Zhang 54 Dec 21, 2022
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

Nikola Zubić 213 Dec 27, 2022
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.

FastReID is a research platform that implements state-of-the-art re-identification algorithms.

JDAI-CV 2.8k Jan 7, 2023
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

Summary Explorer Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multipl

Webis 42 Aug 14, 2022
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or

null 1k Dec 28, 2022
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo

Hugging Face 77.2k Jan 2, 2023
Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-art fuzzing techniques

About Fuzzification Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-

gts3.org (SSLab@Gatech) 55 Oct 25, 2022
Comments
Releases(v1.0.1)
Owner
Ritvik Rastogi
I have been writing code since 2016, and taught myself a handful of skills and programming languages. I love solving problems by writing code
Ritvik Rastogi
GitHub Repository
Soomvaar is the repo which 🏩 contains different collection of 👨‍💻🚀code in Python and 💫✨Machine 👬🏼 learning algorithms📗📕 that is made during 📃 my practice and learning of ML and Python✨💥

Soomvaar 📌 Introduction Soomvaar is the collection of various codes implement in machine learning and machine learning algorithms with python on coll

Felix-Ayush 42 Dec 30, 2022
Domain Generalization with MixStyle, ICLR'21.

MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?

Kaiyang 208 Dec 28, 2022
Classification Modeling: Probability of Default

Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information

Aktham Momani 2 Nov 07, 2022
Intro-to-dl - Resources for "Introduction to Deep Learning" course.

Introduction to Deep Learning course resources https://www.coursera.org/learn/intro-to-deep-learning Running on Google Colab (tested for all weeks) Go

Advanced Machine Learning specialisation by HSE 761 Dec 24, 2022
Deeprl - Standard DQN and dueling network for simple games

DeepRL This code implements the standard deep Q-learning and dueling network with experience replay (memory buffer) for playing simple games. DQN algo

Yao Zhou 6 Apr 12, 2020
TAug :: Time Series Data Augmentation using Deep Generative Models

TAug :: Time Series Data Augmentation using Deep Generative Models Note!!! The package is under development so be careful for using in production! Fea

35 Dec 06, 2022
Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight

Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification Implementation of "Learning From Multiple Experts: Se

27 Nov 05, 2022
PerfFuzz: Automatically Generate Pathological Inputs for C/C++ programs

PerfFuzz Performance problems in software can arise unexpectedly when programs are provided with inputs that exhibit pathological behavior. But how ca

Caroline Lemieux 125 Nov 18, 2022
Reproducible research and reusable acyclic workflows in Python. Execute code on HPC systems as if you executed them on your personal computer!

Reproducible research and reusable acyclic workflows in Python. Execute code on HPC systems as if you executed them on your machine! Motivation Would

Joeri Hermans 15 Sep 11, 2022
Imaginaire - NVIDIA's Deep Imagination Team's PyTorch Library

Imaginaire Docs | License | Installation | Model Zoo Imaginaire is a pytorch library that contains optimized implementation of several image and video

NVIDIA Research Projects 3.6k Dec 29, 2022
Conversational text Analysis using various NLP techniques

PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb

Rita Anjana 158 Dec 25, 2022
Geometric Algebra package for JAX

JAXGA - JAX Geometric Algebra GitHub | Docs JAXGA is a Geometric Algebra package on top of JAX. It can handle high dimensional algebras by storing onl

Robin Kahlow 36 Dec 22, 2022
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

Sriram Ravula 26 Dec 10, 2022
A set of tools for converting a darknet dataset to COCO format working with YOLOX

darknet格式数据→COCO darknet训练数据目录结构（详情参见dataset/darknet）： darknet ├── class.names ├── gen_config.data ├── gen_train.txt ├── gen_valid.txt └── images

RapidAI-NG 148 Jan 03, 2023
Referring Video Object Segmentation

Awesome-Referring-Video-Object-Segmentation Welcome to starts ⭐ & comments 💹 & sharing 😀 !! - 2021.12.12: Recent papers (from 2021) - welcome to ad

Explorer 57 Dec 11, 2022
A trashy useless Latin programming language written in python.

Codigum! The first programming langage in latin! (please keep your eyes closed when if you read the source code) It is pretty useless though. Document

Bic 2 Oct 25, 2021
3D detection and tracking viewer (visualization) for kitti & waymo dataset

3D detection and tracking viewer (visualization) for kitti & waymo dataset

222 Jan 08, 2023
Code for "My(o) Armband Leaks Passwords: An EMG and IMU Based Keylogging Side-Channel Attack" paper

Myo Keylogging This is the source code for our paper My(o) Armband Leaks Passwords: An EMG and IMU Based Keylogging Side-Channel Attack by Matthias Ga

Secure Mobile Networking Lab 7 Jan 03, 2023
A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squares.

W.I.P-Aim-Memory-Game A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squar

dE_soot 1 Dec 08, 2021
A deep learning based semantic search platform that computes similarity scores between provided query and documents

semanticsearch This is a deep learning based semantic search platform that computes similarity scores between provided query and documents. Documents

1 Nov 30, 2021