def test_switch_traces_cases_with_same_id_once(self, n):
f_witness = []
g_witness = []
def f(x):
f_witness.append(None)
return x ** 2
def g(x):
g_witness.append(None)
return x ** 2
stateful.switch(0, [f, g] * n, 2)
f_hk_call_count = len(f_witness)
g_hk_call_count = len(g_witness)
self.assertEqual(f_hk_call_count, 1)
self.assertEqual(g_hk_call_count, 1)
# Ensure we are in sync with JAX.
del f_witness[:], g_witness[:]
jax.lax.switch(0, [f, g] * n, 2)
f_jax_call_count = len(f_witness)
g_jax_call_count = len(g_witness)
self.assertEqual(f_hk_call_count, f_jax_call_count)
self.assertEqual(f_hk_call_count, g_jax_call_count)
def test_stateful_switch_with_rng_use(self):
tmp_default = base.DEFAULT_PRNG_RESERVE_SIZE
base.DEFAULT_PRNG_RESERVE_SIZE = 64
# Test if using different amount of keys in different branches
# results in error
def branch_f(i):
for _ in range(i):
_ = base.next_rng_key()
return i
base.reserve_rng_keys(5)
branches = [lambda _, i=i: branch_f(i) for i in range(5)]
self.assertEqual(stateful.switch(3, branches, None), 3)
self.assertEqual(stateful.switch(0, branches, None), 0)
base.DEFAULT_PRNG_RESERVE_SIZE = tmp_default
def test_switch_no_transform(self):
i = jnp.array(2)
x = jnp.array(42.)
with self.assertRaises(ValueError, msg="Use jax.switch() instead"):
stateful.switch(i, [jnp.square] * 3, x)
def f(i, x): mod = SquareModule() branches = [mod, lambda x: mod(x + 1), lambda x: mod(x + 2)] return stateful.switch(i, branches, x)
# ("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
