lineflow 0.4.2

Framework-Agnostic NLP Data Loader in Python

Lineflow: Framework-Agnostic NLP Data Loader in Python

Lineflow is a simple text dataset loader for NLP deep learning tasks.

• Lineflow was designed to use in all deep learning frameworks.
• Lineflow enables you to build pipelines.
• Lineflow supports functional API and lazy evaluation.

Lineflow is heavily inspired by tensorflow.data.Dataset and chainer.dataset.

Installation

To install Lineflow:

pip install lineflow

Basic Usage

lineflow.TextDataset expects line-oriented text files:

import lineflow as lf


'''/path/to/text will be expected as follows:
i 'm a line 1 .
i 'm a line 2 .
i 'm a line 3 .
'''
ds = lf.TextDataset('/path/to/text')

ds.first()  # "i 'm a line 1 ."
ds.all() # ["i 'm a line 1 .", "i 'm a line 2 .", "i 'm a line 3 ."]
len(ds)  # 3
ds.map(lambda x: x.split()).first()  # ["i", "'m", "a", "line", "1", "."]

Example

• Please check out the examples/small_parallel_enja_pytorch.py to see how to tokenize a sentence, build vocabulary, and do indexing.
• Also check out the other examples to see how to use Lineflow.

Load the predefined dataset:

>>> import lineflow.datasets as lfds
>>> train = lfds.SmallParallelEnJa('train')
>>> train.first()
("i can 't tell who will arrive first .", '誰 が 一番 に 着 く か 私 に は 分か り ま せ ん 。')

Split the sentence to the words:

>>> # continuing from above
>>> train = train.map(lambda x: (x[0].split(), x[1].split()))
>>> train.first()
(['i', 'can', "'t", 'tell', 'who', 'will', 'arrive', 'first', '.'],
 ['誰', 'が', '一番', 'に', '着', 'く', 'か', '私', 'に', 'は', '分か', 'り', 'ま', 'せ', 'ん', '。'])

Obtain words in dataset:

>>> # continuing from above
>>> import lineflow as lf
>>> en_tokens = lf.flat_map(lambda x: x[0], train)
>>> en_tokens[:5] # This is useful to build vocabulary.
['i', 'can', "'t", 'tell', 'who']

Datasets

CNN / Daily Mail:

import lineflow.datasets as lfds

train = lfds.CnnDailymail('train')
dev = lfds.CnnDailymail('dev')
test = lfds.CnnDailymail('test')

IMDB:

import lineflow.datasets as lfds

train = lfds.Imdb('train')
test = lfds.Imdb('test')

Microsoft Research Paraphrase Corpus:

import lineflow.datasets as lfds

train = lfds.MsrParaphrase('train')
test = lfds.MsrParaphrase('test')

small_parallel_enja:

import lineflow.datasets as lfds

train = lfds.SmallParallelEnJa('train')
dev = lfds.SmallParallelEnJa('dev')
test = lfd.SmallParallelEnJa('test')

SQuAD:

import lineflow.datasets as lfds

train = lfds.Squad('train')
dev = lfds.Squad('dev')

WikiText-2 (Added by @sobamchan, thanks.)

import lineflow.datasets as lfds

train = lfds.WikiText2('train')
dev = lfds.WikiText2('dev')
test = lfds.WikiText2('test')