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Loaders and savers for different implentations of word embedding.

Project Description
.. -*- coding: utf-8; -*-

Loaders and savers for different implentations of `word embedding <>`_. The motivation of this project is that it is cumbersome to write loaders for different pretrained word embedding files. This project provides a simple interface for loading pretrained word embedding files in different formats.

.. code:: python

from word_embedding_loader import WordEmbedding

# it will automatically determine format from content
wv = WordEmbedding.load('path/to/embedding.bin')

# This project provides minimum interface for word embedding
print wv.vectors[wv.vocab['is']]

# Modify and save word embedding file with arbitrary format'path/to/save.txt', 'word2vec', binary=False)

This project currently supports following formats:

* `GloVe <>`_, Global Vectors for Word Representation, by Jeffrey Pennington, Richard Socher, Christopher D. Manning from Stanford NLP group.
* `word2vec <>`_, by Mikolov.
- text (create with ``-binary 0`` option (the default))
- binary (create with ``-binary 1`` option)
* `gensim <>`_ 's ``models.word2vec`` module (coming)
* original HDFS format: a performance centric option for loading and saving word embedding (coming)

Sometimes, you want combine an external program with word embedding file of your own choice. This project also provides a simple executable to convert a word embedding format to another.

.. code:: bash

# it will automatically determine the format from the content
word-embedding-loader convert -t glove test/word_embedding_loader/word2vec.bin test.bin

# Get help for command/subcommand
word-embedding-loader --help
word-embedding-loader convert --help

Issues with encoding

This project does decode vocab. It is up to users to determine and decode bytes.

.. code:: python

decoded_vocab = {k.decode('latin-1'): v for k, v in wv.vocab.iteritems()}

.. notes::

Encoding of pretrained word2vec is latin-1. Encoding of pretrained
glove is utf-8


This project us Cython to build some modules, so you need Cython for development.

pip install -r requirements.txt

If environment variable ``DEVELOP_WE`` is set, it will try to rebuild ``.pyx`` modules.

DEVELOP_WE=1 python test
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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
WordEmbeddingLoader-0.2.0.tar.gz (117.8 kB) Copy SHA256 Checksum SHA256 Source Aug 14, 2017

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