Add two new algorithms to solve Gromov Wasserstein: Sampled Gromov Wasserstein and Pointwise Gromov Wasserstein. Based on Sampled Gromov Wasserstein (Machine Learning Journal 2021) (https://hal.archives-ouvertes.fr/hal-03232509/document).

Types of changes

• Docs change / refactoring / dependency upgrade
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

Motivation and context / Related issue

How has this been tested (if it applies)

It has been tested on some GW problems, with various values of hyper-parameters.

Checklist

• The documentation is up-to-date with the changes I made. (I change few lines in README.md, comment the code and document it and provide some examples in examples/gromov/plot_gromov.py.)
• I have read the CONTRIBUTING document.
• All tests passed, and additional code has been covered with new tests. (I do not have changed the other tests, the deletions are only a typo correction: "constratints" to "constraints")