  We present torchami, an advanced implementation of algorithmic Matsubara
integration (AMI) that utilizes pytorch as a backend to provide easy
parallelization and GPU support. AMI is a tool for analytically resolving the
sequence of nested Matsubara integrals that arise in virtually all Feynman
perturbative expansions. In this implementation we present a new AMI algorithm
that creates a more natural symbolic representation of the Feynman integrands.
In addition, we include peripheral tools that allow for import and labelling of
simple graph structures and conversion to torchami input. The code is written
in c++ with python bindings provided.
