Neural machine translation between the writings of Shakespeare and modern English using TensorFlow

Related tags

Deep Learningtensorflowseq2seqneural-machine-translationshakespeare
Overview

Shakespeare translations using TensorFlow

This is an example of using the new Google's TensorFlow library on monolingual translation going from modern English to Shakespeare based on research from Wei Xu.

Prepare

First download the TensorFlow library depending on your platform:

pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl # for mac
pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl # for ubuntu
  1. Grabs parallel data.
  2. Gets train, dev split.
  3. Builds vocabulary
  4. Converts parallel data into ids

From the root directory:

python -m tensorshake.get_data
python -m tensorshake.prepare_corpus

Delete /cache to start anew.

Train

Use the example BASH script to train the model. This saves the check points in the --train_dir directory. If you run it again, the training process continues from the check point. To restart with fresh parameters, simply delete/rename the check points.

./run.sh

Results

Benchmarks from original paper. (Shakespeare -> Modern English)

Input Output
i will bite thee by the ear for that jest . i ’ ll bite you by the ear for that joke .
what further woe conspires against mine age ? what ’ s true despair conspires against my old age ?
how doth my lady ? how is my lady ?
hast thou slain tybalt ? have you killed tybalt ?
an i might live to see thee married once , i have my wish . if i could live to see you married, i ’ ve my wish .
benvolio , who began this bloody fray ? benvolio , who started this bloody fight itself ?
what is your will ? what do you want ?
call her forth to me . bring her out to me .

Cherrypicked examples from this repo (Modern English -> Shakespeare)

Input Output
but you’re not listening to me. but you do not hear me .
Gregory, on my word, we will not be humiliated, like carrying coal. regory , we 'll not carry coals .
but he got the promotion. he is the friend .
i can hit quickly, if i'm motivated. i strike , i am moved .
Did you just give us the finger, sir? have you leave the thumb , sir ?
You don’t know what you’re doing! you do not what you know you .
have you killed Tybalt? hast thou slain tybalt ?
Why, Romeo, are you crazy? why , art thou mad , mad ?

Pre-Trained Models

Here is a link for an example model: https://s3-us-west-2.amazonaws.com/foxtype-nlp/tensorshake/model_cache.zip

Possible improvements

  • word embeddings
  • beam search
  • language model reranking
Owner
Motoki Wu
AI @cresta. Formerly @chegg, @writelab, @foxtype, @lingonautics
Motoki Wu
GitHub Repository
Autoregressive Models in PyTorch.

Autoregressive This repository contains all the necessary PyTorch code, tailored to my presentation, to train and generate data from WaveNet-like auto

Christoph Heindl 41 Oct 09, 2022
Rotation Robust Descriptors

RoRD Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching Project Page | Paper link Evaluation and Datasets MMA : Training on

Udit Singh Parihar 25 Nov 15, 2022
DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut

JugLab 33 Dec 30, 2022
OOD Dataset Curator and Benchmark for AI-aided Drug Discovery

🔥 DrugOOD 🔥 : OOD Dataset Curator and Benchmark for AI Aided Drug Discovery This is the official implementation of the DrugOOD project, this is the

108 Dec 17, 2022
This is an official implementation of the High-Resolution Transformer for Dense Prediction.

High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H

HRNet 403 Dec 13, 2022
PyTorch code of my ICDAR 2021 paper Vision Transformer for Fast and Efficient Scene Text Recognition (ViTSTR)

Vision Transformer for Fast and Efficient Scene Text Recognition (ICDAR 2021) ViTSTR is a simple single-stage model that uses a pre-trained Vision Tra

Rowel Atienza 198 Dec 27, 2022
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model

Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model

Yihong Sun 12 Nov 15, 2022
Scaling Vision with Sparse Mixture of Experts

Scaling Vision with Sparse Mixture of Experts This repository contains the code for training and fine-tuning Sparse MoE models for vision (V-MoE) on I

Google Research 290 Dec 25, 2022
Code for Emergent Translation in Multi-Agent Communication

Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm

Facebook Research 75 Jul 15, 2022
The FIRST GANs-based omics-to-omics translation framework

OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi

Xiaoyu Zhang 6 Dec 14, 2022
Exploring Machine Learning Models for detecting anomalous behavior in credit-card transactions. It's crucial that credit-card companies are able to recognize fraudulent activity so that customers are not charged for items they didn't purchase.

Credit Card Fraud Detection Came across this mocked-up dataset of customer transactions at [Capital One Recruitment Challenge](https://github.com/Capi

Vikrant Deshpande 1 Nov 17, 2022
Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

14 Nov 06, 2022
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

Yasunori Shimura 7 Oct 31, 2022
A PyTorch implementation of QANet.

QANet-pytorch NOTICE I'm very busy these months. I'll return to this repo in about 10 days. Introduction An implementation of QANet with PyTorch. Any

H. Z. 343 Nov 03, 2022
How to use TensorLayer

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

zhangrui 349 Dec 07, 2022
Code release for ConvNeXt model

A ConvNet for the 2020s Official PyTorch implementation of ConvNeXt, from the following paper: A ConvNet for the 2020s. arXiv 2022. Zhuang Liu, Hanzi

Meta Research 4.6k Jan 08, 2023
This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021

Deep-Detail-Enhancement-for-Any-Garment Introduction This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in

40 Dec 13, 2022
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'

HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea

Computer Vision Group, Albert-Ludwigs-Universität Freiburg 38 Dec 13, 2022
Reproduce partial features of DeePMD-kit using PyTorch.

DeePMD-kit on PyTorch For better understand DeePMD-kit, we implement its partial features using PyTorch and expose interface consuing descriptors. Tec

Shaochen Shi 8 Dec 17, 2022
An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance"

Lidar-Segementation An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from

Wangxu1996 135 Jan 06, 2023