def f(xs):
m = CountingModule()
def sf(c, x):
self.assertEqual(c, ())
return c, m(x)
_, ys = stateful.scan(sf, (), xs)
return ys
def test_stateful_scan_with_rng_use(self, iteration_count):
# TODO(lenamartens): remove when default changes to > 1.
tmp_default = base.DEFAULT_PRNG_RESERVE_SIZE
base.DEFAULT_PRNG_RESERVE_SIZE = 64
def body_fun(c, x):
for _ in range(10):
_ = base.next_rng_key()
return c, x
base.reserve_rng_keys(5)
_ = stateful.scan(body_fun, (), (), length=iteration_count)
base.DEFAULT_PRNG_RESERVE_SIZE = tmp_default
def test_scan_no_transform(self):
xs = jnp.arange(3)
with self.assertRaises(ValueError, msg="Use jax.scan() instead"):
stateful.scan(lambda c, x: (c, x), (), xs)
def model(x, *, allow_reuse):
return stateful.scan(Outer(allow_reuse), (), x)
# TODO(tomhennigan): Add missing features (e.g. pjit,xmap).
# ("pmap", lambda f: stateful.pmap(f, "i")),
# Vectorization.
("vmap", lambda f: stateful.vmap(f, split_rng=False)),
# Control flow.
# TODO(tomhennigan): Enable for associative_scan.
# ("associative_scan", lambda f:
# (lambda x: jax.lax.associative_scan(f, x))),
("cond", lambda f: (lambda x: stateful.cond(True, f, f, x))),
("fori_loop", lambda f:
(lambda x: stateful.fori_loop(0, 1, base_test.ignore_index(f), x))),
# ("map", lambda f: (lambda x: stateful.map(f, x))),
("scan", lambda f:
(lambda x: stateful.scan(base_test.identity_carry(f), None, x))),
("switch", lambda f: (lambda x: stateful.switch(0, [f, f], x))),
("while_loop", lambda f: toggle(
f, lambda x: stateful.while_loop(lambda xs: xs[0] == 0,
lambda xs: (1, f(xs[1])),
(0, x)))),
# Automatic differentiation.
# TODO(tomhennigan): Add missing features (e.g. custom_vjp, custom_jvp).
("grad", lambda f: stateful.grad(lambda x: f(x).sum())),
("value_and_grad", lambda f: stateful.value_and_grad(lambda x: f(x).sum())),
("checkpoint", stateful.remat),
)
# pylint: enable=g-long-lambda
