Jupyter Notebook Example

Example Data

To get the data for the following examples:

$ git clone https://github.com/facebookresearch/vizseq
$ cd vizseq
$ bash get_example_data.sh

The data will be available in examples/data.

Data Sources

VizSeq accepts data from various types of sources: plain text file paths, ZIP file paths and Python dictionaries. (See also the data inputs section for more details.)

Here is an example for plain text file paths as inputs:

from glob import glob
root = 'examples/data/translation_wmt14_en_de_test'
src, ref, hypo = glob(f'{root}/src_*.txt'), glob(f'{root}/ref_*.txt'), glob(f'{root}/pred_*.txt')

An example for Python dictionaries as inputs:

from typing import List, Dict
import os.path as op
from glob import glob
def reader(paths: List[str]) -> Dict[str, List[str]]:
    data = {}
    for path in paths:
        name = str(op.splitext(op.basename(path))[0]).split('_', 1)[1]
        with open(path) as f:
            data[name] = [l.strip() for l in f]
    return data
root = 'examples/data/translation_wmt14_en_de_test'
src = reader(glob(f'{root}/src_*.txt'))
ref = reader(glob(f'{root}/ref_*.txt'))
hypo = reader(glob(f'{root}/pred_*.txt'))

Viewing Examples and Statistics

Please see the Jupyter Notebook APIs section for full references.

First, load the vizseq package:

import vizseq

To view dataset statistics:

%matplotlib inline
vizseq.view_stats(src, ref)

View Statistics

To view source-side n-grams:

vizseq.view_n_grams(src)

View N Grams

To view corpus-level scores (BLEU and METEOR):

vizseq.view_scores(ref, hypo, ['bleu', 'meteor'])

View Scores

To check the IDs of available scorers in VizSeq:

vizseq.available_scorers()
Available scorers: bert_score, bleu, bp, chrf, cider, gleu, laser, meteor, nist, ribes, rouge_1, rouge_2, rouge_l, ter, wer, wer_del, wer_ins, wer_sub

We can view examples in pages with sorting:

import vizseq.VizSeqSortingType
vizseq.view_examples(src, ref, hypo, ['bleu'], page_sz=2, page_no=12, sorting=VizSeqSortingType.src_len)

View Examples

Google Translate Integration

VizSeq integrates Google Translate using Google Cloud API, to use which you need a Google Cloud credential and let VizSeq know the credential JSON file path:

vizseq.set_google_credential_path('path to google credential json file')

Then in example viewing API, simply switch the need_g_translate argument on:

vizseq.view_examples(src, ref, hypo, ['bleu'], need_g_translate=True)

Fairseq Integration

More Examples