nejyeah

google-research

Google Research

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

DeepLearningExamples

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

librosa

Python library for audio and music analysis

FasterTransformer

Transformer related optimization, including BERT, GPT

MMdnn

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

astropy

Astronomy and astrophysics core library

mindspore

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

x-deeplearning

An industrial deep learning framework for high-dimension sparse data

tensorflow-internals

It is open source ebook about TensorFlow kernel and implementation mechanism.

micronet

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

DeepRec

DeepRec is a high-performance recommendation deep learning framework based on TensorFlow. It is hosted in incubation in LF AI & Data Foundation.

AdderNet

Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

HugeCTR

HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training

Distributed-TensorFlow-Guide

Distributed TensorFlow basics and examples of training algorithms

nn_tools

Neural Network Tools: Converter and Analyzer. For caffe, pytorch, draknet and so on.

Taylor_pruning

Pruning Neural Networks with Taylor criterion in Pytorch

sparsehash-c11

Experimental C++11 version of sparsehash

DFQ

PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.

Co-Action-Network

Implementation of CAN: Revisiting Feature Co-Action for Click-Through RatePrediction

TDNN

Time delay neural network (TDNN) implementation in Pytorch using unfold method

IR-Net

[CVPR 2020] This project is the PyTorch implementation of our accepted CVPR 2020 paper : forward and backward information retention for accurate binary neural networks.

Maix-EMC

Maix-EMC: Embedded Model Convertor, convert NN model for embedded systems

QuanTorch

PyTorch implementation of "Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference"

bigcomputing

bigcomputing

pmf

Proximal Mean-field for Neural Network Quantization

awd-lstm-tensorflow

AWD-LSTM from "Regularizing and Optimizing LSTM Language Models" with training-award quantization support for tensorflow.

Q-MANN

Quantized Memory-Augmented Neural Networks (AAAI-18)

hgai-open

hgai-open

quantized_distillation