This is an attempt of mimicking the python torch.distributions module.

Rust has a very good wrapper around libtorch: https://github.com/LaurentMazare/tch-rs. However, the torch.distributions module only exists in python and therefor needs to be implemented in rust which is a lot of work. Also, the python module is very well tested.

To ease the work for porting the distributions tch-distr-rs's output is tested against the python implementations.

If you want to help out and implement a missing distribution feel free to add it, implement the Distribution trait and include some tests in tests/against_python.rs.

Currently, the Distribution trait is not stable and it will most likely change (Suggestions welcome!).

The tests require nightly, because of the python wrapper pyo3 and also the python torch library.

On arch linux the tests segfaulted for me when I used the aur/libtorch together with tch, which seems to have been a conflict between the python torch and libtorch.

Using community/python-pytorch instead worked for me.

• bernoulli
• beta
• binomial
• categorical
• cauchy
• chi2
• continuous_bernoulli
• dirichlet
• exponential
• fishersnedecor
• gamma
• geometric
• gumbel
• half_cauchy
• half_normal
• independent
• kl
• laplace
• log_normal
• logistic_normal
• lowrank_multivariate_normal
• mixture_same_family
• multinomial
• multivariate_normal
• negative_binomial
• normal
• one_hot_categorical
• pareto
• poisson
• relaxed_bernoulli
• relaxed_categorical
• studentT
• transformed_distribution
• uniform
• von_mises
• weibull