Minimalistic PyTorch training loop

Related tags

Deep Learningdeep-learningpytorch
Overview

Backbone for PyTorch training loop

Will try to keep it minimalistic.

pip install back

from back import Bone

Features

  • Progress bar
  • Checkpoints saving/loading
  • Schedulers
  • Tensorboard logging
  • Early stopping
  • Multiple GPUs

TODO

  • Learning Rate Finder
  • Notebook example
  • Docs/tests

Docker

docker build -t backbone_pytorch .

or

sudo docker pull digitman/backbone_pytorch:latest

Examples

SRM

https://github.com/EvgenyKashin/SRMnet

You might also like...
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

ORB-SLAM2 Authors: Raul Mur-Artal, Juan D. Tardos, J. M. M. Montiel and Dorian Galvez-Lopez (DBoW2) 13 Jan 2017: OpenCV 3 and Eigen 3.3 are now suppor

Raul Mur-Artal 7.8k Dec 30, 2022
duralava is a neural network which can simulate a lava lamp in an infinite loop.

duralava duralava is a neural network which can simulate a lava lamp in an infinite loop. Example This is not a real lava lamp but a "fake" one genera

Maximilian Bachl 87 Dec 20, 2022
Super-Fast-Adversarial-Training - A PyTorch Implementation code for developing super fast adversarial training

Super-Fast-Adversarial-Training This is a PyTorch Implementation code for develo

LBK 26 Dec 2, 2022
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

VITA 77 Oct 5, 2022
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

null 78 Dec 27, 2022
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training

ActNN : Activation Compressed Training This is the official project repository for ActNN: Reducing Training Memory Footprint via 2-Bit Activation Comp

UC Berkeley RISE 178 Jan 5, 2023
This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code for training a DPR model then continuing training with RAG.

KGI (Knowledge Graph Induction) for slot filling This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code fo

International Business Machines 72 Jan 6, 2023
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar

Katsuya Hyodo 2.4k Jan 5, 2023
BERT model training impelmentation using 1024 A100 GPUs for MLPerf Training v1.1

Pre-trained checkpoint and bert config json file Location of checkpoint and bert config json file This MLCommons members Google Drive location contain

SAIT (Samsung Advanced Institute of Technology) 12 Apr 27, 2022
Comments
  • Bump pillow from 5.4.1 to 6.2.0

    Bump pillow from 5.4.1 to 6.2.0

    Bumps pillow from 5.4.1 to 6.2.0.

    Release notes

    Sourced from pillow's releases.

    6.2.0

    https://pillow.readthedocs.io/en/stable/releasenotes/6.2.0.html

    6.1.0

    https://pillow.readthedocs.io/en/stable/releasenotes/6.1.0.html

    6.0.0

    No release notes provided.

    Changelog

    Sourced from pillow's changelog.

    6.2.0 (2019-10-01)

    • Catch buffer overruns #4104 [radarhere]

    • Initialize rows_per_strip when RowsPerStrip tag is missing #4034 [cgohlke, radarhere]

    • Raise error if TIFF dimension is a string #4103 [radarhere]

    • Added decompression bomb checks #4102 [radarhere]

    • Fix ImageGrab.grab DPI scaling on Windows 10 version 1607+ #4000 [nulano, radarhere]

    • Corrected negative seeks #4101 [radarhere]

    • Added argument to capture all screens on Windows #3950 [nulano, radarhere]

    • Updated warning to specify when Image.frombuffer defaults will change #4086 [radarhere]

    • Changed WindowsViewer format to PNG #4080 [radarhere]

    • Use TIFF orientation #4063 [radarhere]

    • Raise the same error if a truncated image is loaded a second time #3965 [radarhere]

    • Lazily use ImageFileDirectory_v1 values from Exif #4031 [radarhere]

    • Improved HSV conversion #4004 [radarhere]

    • Added text stroking #3978 [radarhere, hugovk]

    • No more deprecated bdist_wininst .exe installers #4029 [hugovk]

    • Do not allow floodfill to extend into negative coordinates #4017 [radarhere]

    ... (truncated)
    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot ignore this [patch|minor|major] version will close this PR and stop Dependabot creating any more for this minor/major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
Releases(v0.1.3)
Owner
Kashin
MLE, Snap
Kashin
GitHub Repository
Deep Learning pipeline for motor-imagery classification.

BCI-ToolBox 1. Introduction BCI-ToolBox is deep learning pipeline for motor-imagery classification. This repo contains five models: ShallowConvNet, De

DongHee 18 Oct 31, 2022
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Hannes Stärk 355 Jan 03, 2023
Python framework for Stochastic Differential Equations modeling

SDElearn: a Python package for SDE modeling This package implements functionalities for working with Stochastic Differential Equations models (SDEs fo

4 May 10, 2022
Spectral Tensor Train Parameterization of Deep Learning Layers

Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

Anton Obukhov 12 Oct 23, 2022
SOFT: Softmax-free Transformer with Linear Complexity, NeurIPS 2021 Spotlight

SOFT: Softmax-free Transformer with Linear Complexity SOFT: Softmax-free Transformer with Linear Complexity, Jiachen Lu, Jinghan Yao, Junge Zhang, Xia

Fudan Zhang Vision Group 272 Dec 25, 2022
learning and feeling SLAM together with hands-on-experiments

modern-slam-tutorial-python Learning and feeling SLAM together with hands-on-experiments 😀 😃 😆 Dependencies Most of the examples are based on GTSAM

Giseop Kim 59 Dec 22, 2022
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

HipGraph: High-Performance Graph Analytics and Learning 6 Sep 23, 2022
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101

A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101

jedibobo 3 Dec 28, 2022
Implementation of the Swin Transformer in PyTorch.

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

597 Jan 03, 2023
Hunt down social media accounts by username across social networks

Hunt down social media accounts by username across social networks Installation | Usage | Docker Notes | Contributing Installation # clone the repo $

1 Dec 14, 2021
Benchmark library for high-dimensional HPO of black-box models based on Weighted Lasso regression

LassoBench LassoBench is a library for high-dimensional hyperparameter optimization benchmarks based on Weighted Lasso regression. Note: LassoBench is

Kenan Šehić 5 Mar 15, 2022
Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

Complex-Valued Neural Networks (CVNN) Done by @NEGU93 - J. Agustin Barrachina Using this library, the only difference with a Tensorflow code is that y

youceF 1 Nov 12, 2021
This provides the R code and data to replicate results in "The USS Trustee’s risky strategy"

USSBriefs2021 This provides the R code and data to replicate results in "The USS Trustee’s risky strategy" by Neil M Davies, Jackie Grant and Chin Yan

1 Oct 30, 2021
9th place solution

AllDataAreExt-Galixir-Kaggle-HPA-2021-Solution Team Members Qishen Ha is Master of Engineering from the University of Tokyo. Machine Learning Engineer

daishu 5 Nov 18, 2021
PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluation of Visual Stories via Semantic Consistency"

Improving Generation and Evaluation of Visual Stories via Semantic Consistency PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluat

Adyasha Maharana 28 Dec 08, 2022
Small little script to scrape, parse and check for active tor nodes. Can be used as proxies.

TorScrape TorScrape is a small but useful script made in python that scrapes a website for active tor nodes, parse the html and then save the nodes in

5 Dec 04, 2022
3D-CariGAN: An End-to-End Solution to 3D Caricature Generation from Normal Face Photos

3D-CariGAN: An End-to-End Solution to 3D Caricature Generation from Normal Face Photos This repository contains the source code and dataset for the pa

54 Oct 09, 2022
MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network

MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S

Justin Sun 12 Dec 27, 2022
MvtecAD unsupervised Anomaly Detection

MvtecAD unsupervised Anomaly Detection This respository is the unofficial implementations of DFR: Deep Feature Reconstruction for Unsupervised Anomaly

0 Feb 25, 2022
IGCN : Image-to-graph convolutional network

IGCN : Image-to-graph convolutional network IGCN is a learning framework for 2D/3D deformable model registration and alignment, and shape reconstructi

Megumi Nakao 7 Oct 27, 2022