Metric-learn

Constraints are now managed with a unified interface (`metric_learn.Constraints`), which makes it easy to generate various input formats from (possibly) partial label information.

All classes inheriting from `BaseMetricLearner` now support sklearn-style `get_params` and `set_params`.

We now support Python 3 alongside Python 2 in the same codebase.

This minor release adds two new methods:
- Local Fisher Discriminant Analysis (LFDA)
- Relative Components Analysis (RCA)

The performance of the non-Shogun LMNN implementation has also been improved, and it should now consume less memory.

This release also includes the new Sphinx documentation and improved docstrings for many of the classes and methods,

This is the first release on PyPI, thanks to terrytangyuan.