[MRG] Fix instantiation of ValFunction (which raises a warning with PyTorch)

[Pseudomanifold]

ValFunction should not be instantiated since autograd functions are
supposed to only ever use static methods. This solves a warning message
raised by PyTorch.

The warning message of PyTorch indicates that this behaviour may raise
an error in future versions.

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

With PyTorch 1.10.1+cu102, using OT on a tensor with a gradient, the following warning message is raised:

[....] valfunction should not be instantiated. Methods on autograd functions are all static, so you should
invoke them on the class itself. Instantiating an autograd function will raise an error in a future version
of PyTorch.

This pull request fixes the instantiation, thus also fixing issue #337.

How has this been tested (if it applies)

Used my own code with the fork of POT. The warning is not raised any more; further behaviour remains exactly the same.

PR checklist

• I have read the CONTRIBUTING document.
• The documentation is up-to-date with the changes I made (check build artifacts).
• All tests passed, and additional code has been covered with new tests.
• I have added the PR and Issue fix to the RELEASES.md file.

[codecov]

Codecov Report

Merging #338 (59b6564) into master (5861209) will increase coverage by 0.03%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #338      +/-   ##
==========================================
+ Coverage   93.03%   93.07%   +0.03%     
==========================================
  Files          21       21              
  Lines        5198     5198              
==========================================
+ Hits         4836     4838       +2     
+ Misses        362      360       -2     

[rflamary]

Thank you very much @Pseudomanifold

[Pseudomanifold]

You are very welcome :-) Thanks for the quick response and for providing this package. It has been of tremendous help so far!