[MRG] Tensorflow backend & Benchmarker & Myst_parser (#316)

* First batch of tf methods (to be continued)

* Second batch of method (yet to debug)

* tensorflow for cpu

* add tf requirement

* pep8 + bug

* small changes

* attempt to solve pymanopt bug with tf2

* attempt #2

* attempt #3

* attempt 4

* docstring

* correct pep8 violation introduced in merge conflicts resolution

* attempt 5

* attempt 6

* just a random try

* Revert "just a random try"

This reverts commit 8223e768bfe33635549fb66cca2267514a60ebbf.

* GPU tests for tensorflow

* pep8

* attempt to solve issue with m2r2

* Remove transpose backend method

* first draft of benchmarker (need to correct time measurement)

* prettier bench table

* Bitsize and prettier device methods

* prettified table bench

* Bug corrected (results were mixed up in the final table)

* Better perf counter (for GPU support)

* pep8

* EMD bench

* solve bug if no GPU available

* pep8

* warning about tensorflow numpy api being required in the backend.py docstring

* Bug solve in backend docstring

* not covering code which requires a GPU

* Tensorflow gradients manipulation tested

* Number of warmup runs is now customizable

* typo

* Remove some warnings while building docs

* Change prettier_device to device_type in backend

* Correct JAX mistakes preventing to see the CPU if a GPU is present

* Attempt to solve JAX bug in case no GPU is found

* Reworked benchmarks order and results storage & clear GPU after usage by benchmark

* Add bench to backend docstring

* better benchs

* remove useless stuff

* Better device_type

* Now using MYST_PARSER and solving links issue in the README.md / online docs

1 files changed, 4 insertions, 4 deletions

diff --git a/README.md b/README.md
index 18064a3..17fbe81 100644
--- a/README.md
+++ b/README.md
@@ -35,7 +35,7 @@ POT provides the following generic OT solvers (links to examples):
 * [Partial Wasserstein and Gromov-Wasserstein](https://pythonot.github.io/auto_examples/unbalanced-partial/plot_partial_wass_and_gromov.html) (exact [29] and entropic [3]
   formulations).
 * [Sliced Wasserstein](https://pythonot.github.io/auto_examples/sliced-wasserstein/plot_variance.html) [31, 32] and Max-sliced Wasserstein [35] that can be used for gradient flows [36].
-* [Several backends](https://pythonot.github.io/quickstart.html#solving-ot-with-multiple-backends) for easy use of POT with  [Pytorch](https://pytorch.org/)/[jax](https://github.com/google/jax)/[Numpy](https://numpy.org/) arrays.
+* [Several backends](https://pythonot.github.io/quickstart.html#solving-ot-with-multiple-backends) for easy use of POT with  [Pytorch](https://pytorch.org/)/[jax](https://github.com/google/jax)/[Numpy](https://numpy.org/)/[Cupy](https://cupy.dev/)/[Tensorflow](https://www.tensorflow.org/) arrays.
 
 POT provides the following Machine Learning related solvers:
 
@@ -202,12 +202,12 @@ This toolbox benefit a lot from open source research and we would like to thank
 
 * [Gabriel Peyré](http://gpeyre.github.io/) (Wasserstein Barycenters in Matlab)
 * [Mathieu Blondel](https://mblondel.org/) (original implementation smooth OT)
-* [Nicolas Bonneel](http://liris.cnrs.fr/~nbonneel/) ( C++ code for EMD)
+* [Nicolas Bonneel](http://liris.cnrs.fr/~nbonneel/) (C++ code for EMD)
 * [Marco Cuturi](http://marcocuturi.net/) (Sinkhorn Knopp in Matlab/Cuda)
 
 ## Contributions and code of conduct
 
-Every contribution is welcome and should respect the [contribution guidelines](https://pythonot.github.io/contributing.html). Each member of the project is expected to follow the [code of conduct](https://pythonot.github.io/code_of_conduct.html).
+Every contribution is welcome and should respect the [contribution guidelines](.github/CONTRIBUTING.md). Each member of the project is expected to follow the [code of conduct](.github/CODE_OF_CONDUCT.md).
 
 ## Support
 
@@ -217,7 +217,7 @@ You can ask questions and join the development discussion:
 * On the POT [gitter channel](https://gitter.im/PythonOT/community)
 * On the POT [mailing list](https://mail.python.org/mm3/mailman3/lists/pot.python.org/)
 
-You can also post bug reports and feature requests in Github issues. Make sure to read our [guidelines](https://pythonot.github.io/contributing.html) first.
+You can also post bug reports and feature requests in Github issues. Make sure to read our [guidelines](.github/CONTRIBUTING.md) first.
 
 ## References