def test_filter(self):
init_fn, _ = transform.transform(get_net)
params = init_fn(jax.random.PRNGKey(428), jnp.ones((1, 1)))
second_layer_params = filtering.filter(
lambda module_name, *_: module_name == "second_layer", params)
self.assertEqual(get_names(second_layer_params),
set(["second_layer/w", "second_layer/b"]))
biases = filtering.filter(lambda module_name, name, _: name == "b",
params) # pytype: disable=wrong-arg-types
self.assertEqual(get_names(biases),
set(["first_layer/b", "second_layer/b"]))
def assert_output_type(self, out_cls):
def assert_type_recursive(s):
self.assertEqual(type(s), out_cls)
for in_cls in (dict, data_structures.FlatMap):
with self.subTest(str(in_cls)):
structure_a = in_cls({"m1": in_cls({"w": None})})
structure_b = in_cls({"m2": in_cls({"w": None})})
structure_c = in_cls(
{f"{i}": in_cls({"w": None})
for i in range(5)})
assert_type_recursive(
filtering.filter(lambda m, n, v: True, structure_a))
assert_type_recursive(
filtering.map(lambda m, n, v: v, structure_a))
assert_type_recursive(filtering.merge(structure_a,
structure_b))
parts = filtering.partition(lambda m, n, v: int(m) > 1,
structure_c)
for part in parts:
assert_type_recursive(part)
parts = filtering.partition_n(lambda m, n, v: int(m),
structure_c, 5)
for part in parts:
assert_type_recursive(part)
