Large dataset storage format for Pytorch

Related tags

Deep Learningpytorchdatasethdf5hdf5-library
Overview

H5Record

Large dataset ( > 100G, <= 1T) storage format for Pytorch (wip)

Support python 3

pip install h5record

Why?

  • Writing large dataset is still a wild west in pytorch. Approaches seen in the wild include:

    • large directory with lots of small files : slow IO when complex file is fetched, deserialized frequently
    • database approach : depend on what kind of database engine used, usually multi-process read is not supported
    • the above method scale non linear in terms of data - storage size

  • TFRecord solved the above problems well ( multiprocess fetch, (de)compression ), fast serialization ( protobuf )

  • However TFRecord port does not support data size evaluation (used frequently by Dataloader ), no index level access available ( important for data evaluation or verification )

H5Record aim to tackle TFRecord problems by compressing the dataset into HDF5 file with an easy to use interface through predefined interfaces ( String, Image, Sequences, Integer).

Some advantage of using H5Record

  • Support multi-process read

  • Relatively simple to use and low technical debt

  • Support compression/de-compression on the fly

  • Quick load to memory if required

Simple usage

pip install h5record
  1. Sentence Similarity
from h5record import H5Dataset, Float, String

schema = (
    String(name='sentence1'),
    String(name='sentence2'),
    Float(name='label')
)
data = [
    ['Sent 1.', 'Sent 2', 0.1],
    ['Sent 3', 'Sent 4', 0.2],
]

def pair_iter():
    for row in data:
        yield {
            'sentence1': row[0],
            'sentence2': row[1],
            'label': row[2]
        }

dataset = H5Dataset(schema, './question_pair.h5', pair_iter())
for idx in range(len(dataset)):
    print(dataset[idx])

Note

Due to in progress development, this package should be use in care in storage with FAT, FAT-32 format

Comparison between different compression algorithm

No chunking is used

Compression Type File size Read speed row/second
no compression 2.0G 2084.55 it/s
lzf 1.7G 1496.14 it/s
gzip 1.1G 843.78 it/s

benchmarked in i7-9700, 1TB NVMe SSD

If you are interested to learn more feel free to checkout the note as well!

You might also like...
A large-scale video dataset for the training and evaluation of 3D human pose estimation models
A large-scale video dataset for the training and evaluation of 3D human pose estimation models

ASPset-510 ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation mode

Aiden Nibali 36 Oct 30, 2022
A large-scale video dataset for the training and evaluation of 3D human pose estimation models
A large-scale video dataset for the training and evaluation of 3D human pose estimation models

ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation models. It contains 17 different amateur subjects performing 30 sports-related actions each, for a total of 510 action clips.

Aiden Nibali 25 Jun 20, 2021
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

ICT.MIRACLE lab 75 Dec 26, 2022
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l

DongYoung Kim 33 Jan 4, 2023
LIVECell - A large-scale dataset for label-free live cell segmentation

LIVECell dataset This document contains instructions of how to access the data associated with the submitted manuscript "LIVECell - A large-scale data

Sartorius Corporate Research 112 Jan 7, 2023
A large-scale face dataset for face parsing, recognition, generation and editing.
A large-scale face dataset for face parsing, recognition, generation and editing.

CelebAMask-HQ [Paper] [Demo] CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA da

switchnorm 1.7k Dec 26, 2022
N-Omniglot is a large neuromorphic few-shot learning dataset
N-Omniglot is a large neuromorphic few-shot learning dataset

N-Omniglot [Paper] || [Dataset] N-Omniglot is a large neuromorphic few-shot learning dataset. It reconstructs strokes of Omniglot as videos and uses D

null 11 Dec 5, 2022
PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices.

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

Amin Rezaei 157 Dec 11, 2022
This is the dataset and code release of the OpenRooms Dataset.
This is the dataset and code release of the OpenRooms Dataset.

This is the dataset and code release of the OpenRooms Dataset.

Visual Intelligence Lab of UCSD 95 Jan 8, 2023
Comments
  • Example about Image dataset

    Example about Image dataset

    Thanks for your work. Do you have an end to end example about image dataset which includes creating h5records file similar to tfrecord files and then using it in dataloader mechanism just like tf dataset api loader mechanism?

    documentation question 
    opened by meet-minimalist 1
Releases(1.0.4)
Owner
theblackcat102
¯\_(ツ)_/¯
theblackcat102
GitHub Repository https://pypi.org/project/h5record
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"

[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"

mythbuster 27 Dec 23, 2022
Video Frame Interpolation without Temporal Priors (a general method for blurry video interpolation)

Video Frame Interpolation without Temporal Priors (NeurIPS2020) [Paper] [video] How to run Prerequisites NVIDIA GPU + CUDA 9.0 + CuDNN 7.6.5 Pytorch 1

YoujianZhang 31 Sep 04, 2022
Gauge equivariant mesh cnn

Geometric Mesh CNN The code in this repository is an implementation of the Gauge Equivariant Mesh CNN introduced in the paper Gauge Equivariant Mesh C

50 Dec 18, 2022
Music Generation using Neural Networks Streamlit App

Music_Gen_Streamlit "Music Generation using Neural Networks" Streamlit App TO DO: Make a run_app.sh Introduction [~5 min] (Sohaib) Team Member names/i

Muhammad Sohaib Arshid 6 Aug 09, 2022
The final project of "Applying AI to 2D Medical Imaging Data" of "AI for Healthcare" nanodegree - Udacity.

Pneumonia Detection from X-Rays Project Overview In this project, you will apply the skills that you have acquired in this 2D medical imaging course t

Omar Laham 1 Jan 14, 2022
Aggragrating Nested Transformer Official Jax Implementation

NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet bench

Google Research 169 Dec 20, 2022
Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

PARE: Part Attention Regressor for 3D Human Body Estimation [ICCV 2021] PARE: Part Attention Regressor for 3D Human Body Estimation, Muhammed Kocabas,

Muhammed Kocabas 277 Jan 03, 2023
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision

MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot

THUNLP 5 Jun 16, 2022
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Overview PyTorch 0.4.1 | Python 3.6.5 Annotated implementations with comparative introductions for minimax, non-saturating, wasserstein, wasserstein g

Shayne O'Brien 471 Dec 16, 2022
Continual learning with sketched Jacobian approximations

Continual learning with sketched Jacobian approximations This repository contains the code for reproducing figures and results in the paper ``Provable

Machine Learning and Information Processing Laboratory 1 Jun 30, 2022
A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.

The Top 10 Computer Vision Papers of 2021 The top 10 computer vision papers in 2021 with video demos, articles, code, and paper reference. While the w

Louis-François Bouchard 118 Dec 21, 2022
Improving Contrastive Learning by Visualizing Feature Transformation, ICCV 2021 Oral

Improving Contrastive Learning by Visualizing Feature Transformation This project hosts the codes, models and visualization tools for the paper: Impro

Bingchen Zhao 83 Dec 15, 2022
World Models with TensorFlow 2

World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand

Zac Wellmer 234 Nov 30, 2022
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.

Gautam Singh 66 Dec 26, 2022
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"

Text-AutoAugment (TAA) This repository contains the code for our paper Text AutoAugment: Learning Compositional Augmentation Policy for Text Classific

LancoPKU 105 Jan 03, 2023
Romanian Automatic Speech Recognition from the ROBIN project

RobinASR This repository contains Robin's Automatic Speech Recognition (RobinASR) for the Romanian language based on the DeepSpeech2 architecture, tog

RACAI 10 Jan 01, 2023
Calibrated Hyperspectral Image Reconstruction via Graph-based Self-Tuning Network.

mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v

JIAMIAN WANG 9 Dec 29, 2022
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.

Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.

Aviv Gabbay 41 Nov 29, 2022
[WWW 2022] Zero-Shot Stance Detection via Contrastive Learning

PT-HCL for Zero-Shot Stance Detection The code of this repository is constantly being updated... Please look forward to it! Introduction This reposito

Akuchi 12 Dec 21, 2022
Fairness Metrics: All you need to know

Fairness Metrics: All you need to know Testing machine learning software for ethical bias has become a pressing current concern. Recent research has p

Anonymous2020 1 Jan 17, 2022