google/seq2seq

Prepare WMT'17 Datasets

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#21 opened on Mar 11, 2017

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 (3 comments) (0 reactions) (0 assignees)Python (5,587 stars) (1,329 forks)batch import
datahelp wanted

Description

We should prepare datasets for All WMT'17 language pairs. This is also a change to try out google/sentencepiece as a preprocessor.

Each dataset should come in different configurations, i.e. different vocabulary sizes and also have a character-level version.

Together with the raw data files we also need the script that was used for the process.

Contributor guide

Tech stack
pythontensorflow
Domain
datamachine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
PythonTensorFlowData preprocessingSentencePiece
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40
Research direction
Examine the existing data preparation scripts in the repository to understand the expected format. For each WMT'17 language pair, download the raw data, then apply sentencepiece tokenization with varying vocabulary sizes (e.g., 8k, 16k, 32k) and also create a character level version. The script should be reusable and saved alongside the processed data. Refer to the WMT17 task page for exact language pairs and data sources.