The Noise Contrastive Estimation for softmax output written in Pytorch

Faster CSV for Python

Faster recursive directory walk on Python 3

This repository is the official implementation of the paper Pruning via Iterative Ranking of Sensitivity Statistics and implements novel pruning / compression algorithms for deep learning / neural networks. Amongst others it implements structured pruning before training, its actual parameter shrinking and unstructured before/during training.

A library that lets you easily increase efficiency of your deep learning models with no loss of accuracy.

Implementation of the paper: Selective_Backpropagation from paper Accelerating Deep Learning by Focusing on the Biggest Losers

Code for paper "Locally Distributed Deep Learning Inference on Edge Device Clusters"

A plug-and-play JIT implementation for Marshmallow to speed up data serialization and deserialization

掘金量化数据API缓存加速库

Continuation methods of Deep Neural Networks optimization, deep-learning, homotopy, bifurcation-analysis, continuation

Re-ordering algorithm for structural sparsity in neural networks

Python realization of wavelet transform with Gabor-kernel (from matlab)

personal toolkits for daily code

A toolkit for HPC performance evaluation.

a local cache service to speedup your internet visit for some resources such as video/file etc.

A Pytorch Plug&Play implementation of the papers "Deep Networks with Stochastic Depth" and "Drop an Octave"

Infraestructuras Paralelas y Distribuidas - Parcial I - Parte Práctica

Using C and Cython to speedup your python

Improve start-up time for FastAPI apps with many nested routers