keras-multilabel-embedding 0.1.1
Training of multi-label embeddings for k-shingled input sequences. for Tensorflow2/Keras
License: Apache License 2.0
Requires Python: >=3.6

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keras-multilabel-embedding
==========================

The package contains a TensorFlow2/Keras class to train an Embedding
matrix for multi-label inputs, i.e. instead of 1 ID per token (one hot
encoding), N IDs per token can be provided as model input.

An PyTorch implementation can be found here:
https://github.com/ulf1/torch-multilabel-embedding
(``pip install torch-multilabel-embedding``)

Usage
-----

Multi-label embeddings with fixed number of labels
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: py

   import keras_multilabel_embedding as tml
   import tensorflow as tf

   # a sequence of multi-label data points
   x_ids = [[1, 2, 4], [0, 1, 2], [2, 1, 4], [3, 2, 1]]
   x_ids = tf.constant(x_ids)

   # initialize layer
   layer = tml.MultiLabelEmbedding(
       vocab_size=5, embed_size=300, random_state=42)

   # predict
   y = layer(x_ids)

Multi-label embeddings with variable number of labels
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: py

   import keras_multilabel_embedding as tml
   import tensorflow as tf

   # a sequence of multi-label data points
   x_ids = [[1, 2, 4], [0, 1, 2], [2, 1], [3]]

   # initialize layer
   layer = tml.MultiLabelEmbedding(
       vocab_size=5, embed_size=300, random_state=42)

   # predict
   y = layer(x_ids)

Appendix
--------

Installation
~~~~~~~~~~~~

The ``keras-multilabel-embedding`` `git
repo <http://github.com/ulf1/keras-multilabel-embedding>`__ is available
as `PyPi
package <https://pypi.org/project/keras-multilabel-embedding>`__

.. code:: sh

   pip install keras-multilabel-embedding
   pip install git+ssh://git@github.com/ulf1/keras-multilabel-embedding.git

Install a virtual environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: sh

   python3 -m venv .venv
   source .venv/bin/activate
   pip install --upgrade pip
   pip install -r requirements.txt --no-cache-dir
   pip install -r requirements-dev.txt --no-cache-dir
   pip install -r requirements-demo.txt --no-cache-dir

(If your git repo is stored in a folder with whitespaces, then don’t use
the subfolder ``.venv``. Use an absolute path without whitespaces.)

Python commands
~~~~~~~~~~~~~~~

-  Jupyter for the examples: ``jupyter lab``
-  Check syntax:
   ``flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')``
-  Run Unit Tests: ``PYTHONPATH=. pytest``

Publish

.. code:: sh

   pandoc README.md --from markdown --to rst -s -o README.rst
   python setup.py sdist 
   twine upload -r pypi dist/*

Clean up
~~~~~~~~

.. code:: sh

   find . -type f -name "*.pyc" | xargs rm
   find . -type d -name "__pycache__" | xargs rm -r
   rm -r .pytest_cache
   rm -r .venv

Support
~~~~~~~

Please `open an
issue <https://github.com/ulf1/keras-multilabel-embedding/issues/new>`__
for support.

Contributing
~~~~~~~~~~~~

Please contribute using `Github
Flow <https://guides.github.com/introduction/flow/>`__. Create a branch,
add commits, and `open a pull
request <https://github.com/ulf1/keras-multilabel-embedding/compare/>`__.

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