moscot.backends.ott.SinkhornSolver#

class moscot.backends.ott.SinkhornSolver(jit=True, rank=-1, epsilon=0.0, initializer=None, initializer_kwargs=mappingproxy({}), **kwargs)[source]#

Solver for the linear problem.

The (Kantorovich relaxed) OT problem is defined by two distributions in the same space. The aim is to obtain a probabilistic map from the source distribution to the target distribution such that the (weighted) sum of the distances between coupled data point in the source and the target distribution is minimized.

Parameters:

Methods

__call__([xy, x, y, tags, device])

Solve an optimal transport problem.

Attributes

is_low_rank

Whether the solver is low-rank.

problem_kind

Problem kind this solver handles.

rank

Rank of the solver.

solver

ott solver.

xy

Geometry defining the linear term.