  We present a trainable framework for efficiently generating gauge
configurations, and discuss ongoing work in this direction. In particular, we
consider the problem of sampling configurations from a 4D $SU(3)$ lattice gauge
theory, and consider a generalized leapfrog integrator in the molecular
dynamics update that can be trained to improve sampling efficiency. Code is
available online at https://github.com/saforem2/l2hmc-qcd.
