token2index 0.9.2

A lightweight but powerful library for token indexing.

:zap: :card_index: token2index: A lightweight but powerful library for token indexing

token2index is a small yet powerful library facilitating the fast and easy creation of a data structure mapping tokens to indices, primarily aimed at applications for Natural Language Processing. The library is fully tested, and does not require any additional requirements. The documentation can be found here, some feature highlights are shown below.

:sparkles: Feature Highlights

• Building and extending vocab

  One way to build the index from a corpus is using the build() function:

  >>> from t2i import T2I
  >>> t2i = T2I.build(["colorless green ideas dream furiously", "the horse raced past the barn fell"])
  >>> t2i
  T2I(Size: 13, unk_token: <unk>, eos_token: <eos>, {'colorless': 0, 'green': 1, 'ideas': 2, 'dream': 3, 'furiously': 4, 'the': 5, 'horse': 6, 'raced': 7, 'past': 8, 'parn': 9, 'fell': 10, '<unk>': 11, '<eos>': 12})
  

  The index can always be extended again later using extend():

  >>> t2i = t2i.extend("completely new words")
  T2I(Size: 16, unk_token: <unk>, eos_token: <eos>, {'colorless': 0, 'green': 1, 'ideas': 2, 'dream': 3, 'furiously': 4, 'the': 5, 'horse': 6, 'raced': 7, 'past': 8, 'barn': 9, 'fell': 10, 'completely': 13, 'new': 14, 'words': 15, '<unk>': 16, '<eos>': 17})
  

• Easy indexing (of batches)

  Index multiple sentences at once in a single function call!

  >>> t2i.index(["the green horse raced <eos>", "ideas are a dream <eos>"])
  [[5, 1, 6, 7, 12], [2, 11, 11, 3, 12]]
  

  where unknown tokens are always mapped to unk_token.

• Easy conversion back to strings

  Reverting indices back to strings is equally as easy:

  >>> t2i.unindex([5, 14, 16, 3, 6])
  'the new <unk> dream horse'
  

• Vocab from file

  Using T2I.from_file(), the index can be created directly by reading from an existing vocab file. Refer to its documentation here for more info.

• Fixed memory size

  Although the defaultdict class from Python's collections package also posses the functionality to map unknown keys to a certain value, it grows in size for every new key. T2I memory size stays fixed after the index is built.

• Support for special tokens

  To enable flexibility in modern NLP applications, T2I allows for an arbitrary number of special tokens (like a masking or a padding token) during init!

  >>> t2i = T2I(special_tokens=["<mask>"])
  >>> t2i
  T2I(Size: 3, unk_token: <unk>, eos_token: <eos>, {'<unk>': 0, '<eos>': 1, '<mask>': 2})
  

:electric_plug: Compatibility with other frameworks (Numpy, PyTorch, Tensorflow)

It is also ensured that T2I is easily compatible with frameworks like Numpy, PyTorch and Tensorflow, without needing them as requirements:

Numpy

>>> import numpy as np
>>> t = np.array(t2i.index(["the new words are ideas <eos>", "the green horse <eos> <pad> <pad>"]))
>>> t
array([[ 5, 15, 16, 17,  2, 18],
   [ 5,  1,  6, 18, 19, 19]])
>>> t2i.unindex(t)
['the new words <unk> ideas <eos>', 'the green horse <eos> <pad> <pad>']

PyTorch

>>> import torch
>>> t = torch.LongTensor(t2i.index(["the new words are ideas <eos>", "the green horse <eos> <pad> <pad>"]))
>>> t
tensor([[ 5, 15, 16, 17,  2, 18],
    [ 5,  1,  6, 18, 19, 19]])
>>> t2i.unindex(t)
['the new words <unk> ideas <eos>', 'the green horse <eos> <pad> <pad>']

Tensorflow

>>> import tensorflow as tf
>>> t = tf.convert_to_tensor(t2i.index(["the new words are ideas <eos>", "the green horse <eos> <pad> <pad>"]), dtype=tf.int32)
>>> t
tensor([[ 5, 15, 16, 17,  2, 18],
    [ 5,  1,  6, 18, 19, 19]])
>>> t2i.unindex(t)
['the new words <unk> ideas <eos>', 'the green horse <eos> <pad> <pad>']

:inbox_tray: Installation

Installation can simply be done using pip:

pip3 install token2index

:mortar_board: Citing

If you use token2index for research purposes, please cite the library using the following citation info:

@article{token2index,
    title={token2index: A lightweight but powerful library for token indexing},
    author={Dennis Ulmer},
    year={2020},
}