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To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.

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Citations

This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
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.. image:: https://badge.fury.io/py/tensorly.svg
    :target: https://badge.fury.io/py/tensorly

.. image:: https://travis-ci.org/tensorly/tensorly.svg?branch=master
    :target: https://travis-ci.org/tensorly/tensorly

.. image:: https://coveralls.io/repos/github/tensorly/tensorly/badge.svg?branch=master
    :target: https://coveralls.io/github/tensorly/tensorly?branch=master

TensorLy
========

TensorLy is a fast and simple Python library for tensor learning. It builds on top of NumPy, SciPy and MXNet and allows for fast and straightforward tensor decomposition, tensor learning and tensor algebra.

- **Website:** http://tensorly.github.io
- **Source:**  https://github.com/tensorly/tensorly
- **Jupyter Notebooks:** https://github.com/JeanKossaifi/tensorly_notebooks


How to install
--------------
 
Easy option: install with pip
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Simply run::

   pip install -U tensorly

That's it!

Alternatively, you can pip install from the git repository::

   pip install git+https://github.com/tensorly/tensorly

Development: install from git
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The library is still very new and under heavy developement. To install the last version:

Clone the repository and cd there::

   git clone https://github.com/tensorly/tensorly
   cd tensorly

Then install the package (here in editable mode with `-e` or equivalently `--editable`)::

   pip install -e .

Running the tests
~~~~~~~~~~~~~~~~~

Testing and documentation are an essential part of this package and all functions come with uni-tests and documentation.

You can run all the tests using the `nose` package::

   nosetests -v tensorly

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The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Contact— JavaScript license information— Web API

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