Skip to main content

A toolkit for Relation Extraction and more...

Project description



Build Docs

A toolkit for Relation & Event eXtraction (REx) and more...

This project has not been finished yet, so be careful when using it, or wait until the first release comes out.

This project is suffering from the second-system effect. I would like to cut some features to make this going smoothly.

Accelerate seems to be a very sweet wrapper for multi-GPU, TPU training, we highly recommend you to use such frameworks, instead of adding hard codes on your own.

⚙️Installation

Make sure you have installed all the dependencies below.

  • Python>=3.6
    • torch>=1.2.0 : project is developed with torch==1.7.1, should be compatable with >=1.2.0 versions
    • numpy>=1.19.0
    • scikit-learn>=0.21.3
    • omegaconf>=2.0.6
    • loguru>=0.5.3
    • tqdm>=4.61.1
    • transformers>=4.8.2
$ git clone https://github.com/Spico197/REx.git
$ cd REx
$ pip install -e .

# or you can download and install from pypi, not recommend for now
$ pip install pytorch-rex -i https://pypi.org/simple

🚀QuickStart

Checkout the examples folder.

Name Model Dataset Task
SentRE-MCML PCNN IPRE Sentence-level Multi-class multi-label relation classification
BagRE PCNN+ONE NYT10 Bag-level relation classification (Multi-Instance Learning, MIL)
JointERE CasRel WebNLG Jointly entity relation extraction
  • To create new task for classification, try: rex new classification <task_name>
  • To create new task for tagging, try: rex new tagging <task_name>

✈️Abilities

Dataset

  • IPRE preprocess
  • NYT10

Tasks

  • Chinese sentence-level relation extraction
  • English bag-level relation extraction

Modules & Models

  • Piecewise CNN
  • PCNN + ONE
  • PCNN + ATT

✉️Update

  • v0.0.14: update vocab embedding loading to be compatible with other embedding files
  • v0.0.13: update vocab, label_encoder, fix bugs in cnn reshaping and crf importing
  • v0.0.12: fix crf module import issue
  • v0.0.11: fix templates data resources
  • v0.0.10: update utils.config module, StaticEmbedding decoupling, remove eps in metrics, add templates generation entrypoints, add more tests (coverage stat for the whole repo, lots of codes are not test case covered)
  • v0.0.9: use argparse instead of click, move loguru logger into rex.utils.logging, add hierarchical config setting
  • v0.0.8: fix config loading, change default of makedirs and dump_configfile to be True
  • v0.0.7: fix recursive import bug
  • v0.0.6: integrate omega conf loading into the inner task, add load_*_data option to data managers
  • v0.0.5: update ffn
  • v0.0.4: return detailed classification information in mc_prf1, support nested dict tensor movement
  • v0.0.3: fix packaging bug in setup.py
  • v0.0.2: add black formatter and pytest testing
  • v0.0.1: change LabelEncoder.to_binary_labels into convert_to_multi_hot or convert_to_one_hot

🔑LICENCE

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytorch-rex-0.0.14.tar.gz (44.6 kB view details)

Uploaded Source

Built Distribution

pytorch_rex-0.0.14-py3-none-any.whl (65.4 kB view details)

Uploaded Python 3

File details

Details for the file pytorch-rex-0.0.14.tar.gz.

File metadata

  • Download URL: pytorch-rex-0.0.14.tar.gz
  • Upload date:
  • Size: 44.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

File hashes

Hashes for pytorch-rex-0.0.14.tar.gz
Algorithm Hash digest
SHA256 985689b3fc1e4d55f751a0c38fe339c1c1594616d5d7a24d1fcf7bb354a83b50
MD5 d9c5e9c56ab185971cacb14726471b20
BLAKE2b-256 7f3dfa0e30bafffdf09e7de822adcd20f69c4a8eac8b64bd850e4f7ab9b12fa4

See more details on using hashes here.

File details

Details for the file pytorch_rex-0.0.14-py3-none-any.whl.

File metadata

  • Download URL: pytorch_rex-0.0.14-py3-none-any.whl
  • Upload date:
  • Size: 65.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

File hashes

Hashes for pytorch_rex-0.0.14-py3-none-any.whl
Algorithm Hash digest
SHA256 32226d1f45aa76d76ce9e2e426d20655ade44839bae80913da2958faa0115986
MD5 4ad2df08c4cb4d4e9e6857925dda419e
BLAKE2b-256 fe226cec1ce0556a3ae906207f150e935204fe64f866caaf2fa107e9ea528526

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page