  We study the problem of fairly allocating a set of indivisible goods among
agents with {\em bivalued submodular valuations} -- each good provides a
marginal gain of either $a$ or $b$ ($a < b$) and goods have decreasing marginal
gains. This is a natural generalization of two well-studied valuation classes
-- bivalued additive valuations and binary submodular valuations. We present a
simple sequential algorithmic framework, based on the recently introduced
Yankee Swap mechanism, that can be adapted to compute a variety of solution
concepts, including max Nash welfare (MNW), leximin and $p$-mean welfare
maximizing allocations when $a$ divides $b$. This result is complemented by an
existing result on the computational intractability of MNW and leximin
allocations when $a$ does not divide $b$. We show that MNW and leximin
allocations guarantee each agent at least $\frac25$ and $\frac{a}{b+2a}$ of
their maximin share, respectively, when $a$ divides $b$. We also show that
neither the leximin nor the MNW allocation is guaranteed to be envy free up to
one good (EF1). This is surprising since for the simpler classes of bivalued
additive valuations and binary submodular valuations, MNW allocations are known
to be envy free up to any good (EFX).
