Change library name to ampligraph

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+.DS_Store
+._.DS_Store
+docs/.DS_Store
+docs/._.DS_Store
+
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+.static_storage/
+.media/
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# pycharm
+.idea/
+
+#chan-hdt
+model
+.pytest_cache
+output.txt
+unittest_save_and_restore_models

README.md

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+# Knowledge Graph Embedding Models
+
+
+## About
+
+Explainable Link Prediction (`ampligraph`) is a machine learning library for Relational Learning, a branch of machine learning
+that deals with supervised learning on knowledge graphs.
+
+The library includes Relational Learning models, i.e. supervised learning models designed to predict
+links in knowledge graphs.
+
+The tool also includes the required evaluation protocol, metrics, knowledge graph preprocessing,
+and negative statements generator strategies.
+
+
+# Installation
+
+### Provision a Virtual Environment
+
+**Installation using Anaconda is highly recommended.**
+
+Create & activate Virtual Environment (conda)
+
+```
+conda create --name ampligraph python=3.6
+source activate ampligraph
+```
+
+### Install TensorFlow
+
+**CPU version**
+
+```
+pip install tensorflow
+```
+
+or you could install the version packaged with conda:
+
+```
+conda install tensorflow
+```
+
+**GPU version**
+
+```
+pip install tensorflow-gpu
+```
+
+or you could install the version packaged with conda:
+
+```
+conda install tensorflow-gpu
+```
+
+
+## Install the library
+
+
+You can install the latest stable release of `ampligraph` with pip, using the latest wheel (0.3.0) published by Dublin Labs:
+*Note this work only from within the Dublin Labs network*
+
+```
+pip install http://dubaldeweb001.techlabs.accenture.com/wheels/ampligraph/ampligraph-0.3.dev0-py3-none-any.whl
+```
+
+If instead you want the most recent development version, you can clone the repository
+and install from source (this will pull the latest commit on `develop` branch).
+The code snippet below will install the library in editable mode (`-e`):
+
+```
+git clone ssh://git@innersource.accenture.com/dl/ampligraph.git
+cd ampligraph
+pip install -e .
+
+```
+
+
+## Download the Datasets
+
+Datasets can be downloaded from [SharePoint](https://ts.accenture.com/sites/TechLabs-Dublin/_layouts/15/guestaccess.aspx?guestaccesstoken=Uz28P2m4hWp2TEgbvFrD%2b4BiURBHVTAw0NbPBRLzWWA%3d&folderid=2_012fd581718e74e4a9305c845a1224ee1&rev=1).
+Once downloaded, decompress the archives.
+
+**You must also set the following environment variable:**
+
+```
+export AMPLIGRAPH_DATA_HOME=/YOUR/PATH/TO/datasets
+```
+
+## Sanity Check
+
+```python
+>> import ampligraph
+>> ampligraph.__version__
+'0.3-dev'
+```
+
+## Installing with HDT Support
+[HDT](http://www.rdfhdt.org/) is a compressed type of RDF graph data. By default, the installed ampligraph library does not support loading this data type. To enable it, you must have **`gcc` with C++11 support** installed in your Linux box.
+
+**Ubuntu**
+
+```
+sudo add-apt-repository ppa:jonathonf/gcc-7.3
+sudo apt-get update
+sudo apt-get install gcc-7
+```
+
+**CentOS**
+
+Below are commands we used to install gcc 7.3.1 on CentOS 7.5:
+
+```
+sudo yum install centos-release-scl
+sudo yum install devtoolset-7-gcc*
+scl enable devtoolset-7 bash
+```
+
+Once finished installing gcc, you can install the ampligraph library with hdt support by:
+
+```
+pip install .[hdt]
+```
+
+##  Documentation
+
+**[Latest documentation available here](http://10.106.43.211/docs/ampligraph/dev/index.html)**
+
+
+The project documentation can be built with Sphinx:
+
+```
+cd docs
+make clean autogen html
+```
+
+## Tests
+
+
+```
+pytest -s tests
+```
+

ampligraph/__init__.py

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+"""Explainable Link Prediction is a library for relational learning on knowledge graphs."""
+
+__version__ = '0.3-dev'
+
+
+__all__ = ['datasets', 'latent_features', 'evaluation']

ampligraph/datasets/__init__.py

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+"""Helper functions to load knowledge graphs from disk."""
+
+from .datasets import load_from_csv, load_from_rdf, load_fb15k, load_wn18, load_fb15k_237, load_from_ntriples\
+    , AMPLIGRAPH_DATA_HOME, load_from_hdt, load_ICEWS, \
+    load_wn11, load_fb13
+
+__all__ = ['load_from_csv', 'load_from_rdf', 'load_from_ntriples', 'load_wn11', 'load_wn18', 'load_fb15k',
+           'load_fb13', 'load_fb15k_237', 'load_from_hdt',
+           'load_wn11', 'load_fb13', 'AMPLIGRAPH_DATA_HOME']
+