rocm_jax/tests/tree_util_test.py
Markus Kunesch f030e70e82 xla: improvement to string representation of PyTreeDef
The string representation of PyTreeDef was different to how the underlying
containers are represented in python. This sometimes made it harder to read
error messages. This commit modifies the representation of tuples, lists,
dicts, and None so that it matches the pythonic representation.

The representation of custom nodes and NamedTuples is left unchanged since
their structure is not easily accessible in C++. However, to avoid confusion
they are now labelled "CustomNode" instead of "PyTreeDef". The latter is now
only used to wrap the whole representation. See below for examples.

Tests that relied on a specific string representation of PyTreeDef in error
messages are modified to be agnostic to the representation. Instead, this
commit adds a separate test of the string representation in tree_util_test.

Examples:

```
OLD: PyTreeDef(dict[['a', 'b']], [*,*])
NEW: PyTreeDef({'a': *, 'b': *})

OLD: PyTreeDef(tuple, [PyTreeDef(tuple, [*,*]),PyTreeDef(list, [*,PyTreeDef(tuple, [*,PyTreeDef(None, []),*])])])
NEW: PyTreeDef(((*, *), [*, (*, None, *)]))

OLD: PyTreeDef(list, [PyTreeDef(<class '__main__.AnObject'>[[4, 'foo']], [*,PyTreeDef(None, [])])])
NEW: PyTreeDef([CustomNode(<class '__main__.AnObject'>[[4, 'foo']], [*, None])])
```
PiperOrigin-RevId: 369298267
2021-04-19 14:06:36 -07:00

362 lines
12 KiB
Python

# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import collections
import unittest
from absl.testing import absltest
from absl.testing import parameterized
from jax import test_util as jtu
from jax import tree_util
from jax._src.tree_util import _process_pytree
from jax import flatten_util
import jax.numpy as jnp
from jax import lib
def _dummy_func(*args, **kwargs):
return
ATuple = collections.namedtuple("ATuple", ("foo", "bar"))
class ANamedTupleSubclass(ATuple):
pass
class AnObject(object):
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
def __eq__(self, other):
return self.x == other.x and self.y == other.y and self.z == other.z
def __hash__(self):
return hash((self.x, self.y, self.z))
def __repr__(self):
return "AnObject({},{},{})".format(self.x, self.y, self.z)
tree_util.register_pytree_node(AnObject, lambda o: ((o.x, o.y), o.z),
lambda z, xy: AnObject(xy[0], xy[1], z))
@tree_util.register_pytree_node_class
class Special:
def __init__(self, x, y):
self.x = x
self.y = y
def __repr__(self):
return "Special(x={}, y={})".format(self.x, self.y)
def tree_flatten(self):
return ((self.x, self.y), None)
@classmethod
def tree_unflatten(cls, aux_data, children):
return cls(*children)
def __eq__(self, other):
return type(self) is type(other) and (self.x, self.y) == (other.x, other.y)
@tree_util.register_pytree_node_class
class FlatCache:
def __init__(self, structured, *, leaves=None, treedef=None):
if treedef is None:
leaves, treedef = tree_util.tree_flatten(structured)
self._structured = structured
self.treedef = treedef
self.leaves = leaves
def __hash__(self):
return hash(self.structured)
def __eq__(self, other):
return self.structured == other.structured
def __repr__(self):
return f"FlatCache({self.structured!r})"
@property
def structured(self):
if self._structured is None:
self._structured = tree_util.tree_unflatten(self.treedef, self.leaves)
return self._structured
def tree_flatten(self):
return self.leaves, self.treedef
@classmethod
def tree_unflatten(cls, meta, data):
if not tree_util.all_leaves(data):
data, meta = tree_util.tree_flatten(tree_util.tree_unflatten(meta, data))
return FlatCache(None, leaves=data, treedef=meta)
TREES = (
(None,),
((None,),),
((),),
(([()]),),
((1, 2),),
(((1, "foo"), ["bar", (3, None, 7)]),),
([3],),
([3, ATuple(foo=(3, ATuple(foo=3, bar=None)), bar={"baz": 34})],),
([AnObject(3, None, [4, "foo"])],),
(Special(2, 3.),),
({"a": 1, "b": 2},),
(collections.OrderedDict([("foo", 34), ("baz", 101), ("something", -42)]),),
(collections.defaultdict(dict,
[("foo", 34), ("baz", 101), ("something", -42)]),),
(ANamedTupleSubclass(foo="hello", bar=3.5),),
(FlatCache(None),),
(FlatCache(1),),
(FlatCache({"a": [1, 2]}),),
)
TREE_STRINGS = (
"PyTreeDef(None)",
"PyTreeDef((None,))",
"PyTreeDef(())",
"PyTreeDef([()])",
"PyTreeDef((*, *))",
"PyTreeDef(((*, *), [*, (*, None, *)]))",
"PyTreeDef([*])",
"PyTreeDef([*, CustomNode(namedtuple[<class '__main__.ATuple'>], [(*, "
"CustomNode(namedtuple[<class '__main__.ATuple'>], [*, None])), {'baz': "
"*}])])",
"PyTreeDef([CustomNode(<class '__main__.AnObject'>[[4, 'foo']], [*, None])])",
"PyTreeDef(CustomNode(<class '__main__.Special'>[None], [*, *]))",
"PyTreeDef({'a': *, 'b': *})",
)
LEAVES = (
("foo",),
(0.1,),
(1,),
(object(),),
)
class TreeTest(jtu.JaxTestCase):
@parameterized.parameters(*(TREES + LEAVES))
def testRoundtrip(self, inputs):
xs, tree = tree_util.tree_flatten(inputs)
actual = tree_util.tree_unflatten(tree, xs)
self.assertEqual(actual, inputs)
@parameterized.parameters(*(TREES + LEAVES))
def testRoundtripWithFlattenUpTo(self, inputs):
_, tree = tree_util.tree_flatten(inputs)
xs = tree.flatten_up_to(inputs)
actual = tree_util.tree_unflatten(tree, xs)
self.assertEqual(actual, inputs)
@parameterized.parameters(
(tree_util.Partial(_dummy_func),),
(tree_util.Partial(_dummy_func, 1, 2),),
(tree_util.Partial(_dummy_func, x="a"),),
(tree_util.Partial(_dummy_func, 1, 2, 3, x=4, y=5),),
)
def testRoundtripPartial(self, inputs):
xs, tree = tree_util.tree_flatten(inputs)
actual = tree_util.tree_unflatten(tree, xs)
# functools.partial does not support equality comparisons:
# https://stackoverflow.com/a/32786109/809705
self.assertEqual(actual.func, inputs.func)
self.assertEqual(actual.args, inputs.args)
self.assertEqual(actual.keywords, inputs.keywords)
@parameterized.parameters(*(TREES + LEAVES))
def testRoundtripViaBuild(self, inputs):
xs, tree = _process_pytree(tuple, inputs)
actual = tree_util.build_tree(tree, xs)
self.assertEqual(actual, inputs)
def testChildren(self):
_, tree = tree_util.tree_flatten(((1, 2, 3), (4,)))
_, c0 = tree_util.tree_flatten((0, 0, 0))
_, c1 = tree_util.tree_flatten((7,))
self.assertEqual([c0, c1], tree.children())
def testFlattenUpTo(self):
_, tree = tree_util.tree_flatten([(1, 2), None, ATuple(foo=3, bar=7)])
out = tree.flatten_up_to([({
"foo": 7
}, (3, 4)), None, ATuple(foo=(11, 9), bar=None)])
self.assertEqual(out, [{"foo": 7}, (3, 4), (11, 9), None])
def testTreeMultimap(self):
x = ((1, 2), (3, 4, 5))
y = (([3], None), ({"foo": "bar"}, 7, [5, 6]))
out = tree_util.tree_multimap(lambda *xs: tuple(xs), x, y)
self.assertEqual(out, (((1, [3]), (2, None)),
((3, {"foo": "bar"}), (4, 7), (5, [5, 6]))))
def testTreeMultimapWithIsLeafArgument(self):
x = ((1, 2), [3, 4, 5])
y = (([3], None), ({"foo": "bar"}, 7, [5, 6]))
out = tree_util.tree_multimap(lambda *xs: tuple(xs), x, y,
is_leaf=lambda n: isinstance(n, list))
self.assertEqual(out, (((1, [3]), (2, None)),
(([3, 4, 5], ({"foo": "bar"}, 7, [5, 6])))))
def testFlattenIsLeaf(self):
x = [(1, 2), (3, 4), (5, 6)]
leaves, _ = tree_util.tree_flatten(x, is_leaf=lambda t: False)
self.assertEqual(leaves, [1, 2, 3, 4, 5, 6])
leaves, _ = tree_util.tree_flatten(
x, is_leaf=lambda t: isinstance(t, tuple))
self.assertEqual(leaves, x)
leaves, _ = tree_util.tree_flatten(x, is_leaf=lambda t: isinstance(t, list))
self.assertEqual(leaves, [x])
leaves, _ = tree_util.tree_flatten(x, is_leaf=lambda t: True)
self.assertEqual(leaves, [x])
y = [[[(1,)], [[(2,)], {"a": (3,)}]]]
leaves, _ = tree_util.tree_flatten(
y, is_leaf=lambda t: isinstance(t, tuple))
self.assertEqual(leaves, [(1,), (2,), (3,)])
@parameterized.parameters(*TREES)
def testRoundtripIsLeaf(self, tree):
xs, treedef = tree_util.tree_flatten(
tree, is_leaf=lambda t: isinstance(t, tuple))
recon_tree = tree_util.tree_unflatten(treedef, xs)
self.assertEqual(recon_tree, tree)
@parameterized.parameters(*TREES)
def testAllLeavesWithTrees(self, tree):
leaves = tree_util.tree_leaves(tree)
self.assertTrue(tree_util.all_leaves(leaves))
self.assertFalse(tree_util.all_leaves([tree]))
@parameterized.parameters(*LEAVES)
def testAllLeavesWithLeaves(self, leaf):
self.assertTrue(tree_util.all_leaves([leaf]))
@parameterized.parameters(*TREES)
def testCompose(self, tree):
treedef = tree_util.tree_structure(tree)
inner_treedef = tree_util.tree_structure(["*", "*", "*"])
composed_treedef = treedef.compose(inner_treedef)
expected_leaves = treedef.num_leaves * inner_treedef.num_leaves
self.assertEqual(composed_treedef.num_leaves, expected_leaves)
expected_nodes = ((treedef.num_nodes - treedef.num_leaves) +
(inner_treedef.num_nodes * treedef.num_leaves))
self.assertEqual(composed_treedef.num_nodes, expected_nodes)
leaves = [1] * expected_leaves
composed = tree_util.tree_unflatten(composed_treedef, leaves)
self.assertEqual(leaves, tree_util.tree_leaves(composed))
@parameterized.parameters(*TREES)
def testTranspose(self, tree):
outer_treedef = tree_util.tree_structure(tree)
if not outer_treedef.num_leaves:
self.skipTest("Skipping empty tree")
inner_treedef = tree_util.tree_structure([1, 1, 1])
nested = tree_util.tree_map(lambda x: [x, x, x], tree)
actual = tree_util.tree_transpose(outer_treedef, inner_treedef, nested)
self.assertEqual(actual, [tree, tree, tree])
def testTransposeMismatchOuter(self):
tree = {"a": [1, 2], "b": [3, 4]}
outer_treedef = tree_util.tree_structure({"a": 1, "b": 2, "c": 3})
inner_treedef = tree_util.tree_structure([1, 2])
with self.assertRaisesRegex(TypeError, "Mismatch"):
tree_util.tree_transpose(outer_treedef, inner_treedef, tree)
def testTransposeMismatchInner(self):
tree = {"a": [1, 2], "b": [3, 4]}
outer_treedef = tree_util.tree_structure({"a": 1, "b": 2})
inner_treedef = tree_util.tree_structure([1, 2, 3])
with self.assertRaisesRegex(TypeError, "Mismatch"):
tree_util.tree_transpose(outer_treedef, inner_treedef, tree)
def testTransposeWithCustomObject(self):
outer_treedef = tree_util.tree_structure(FlatCache({"a": 1, "b": 2}))
inner_treedef = tree_util.tree_structure([1, 2])
expected = [FlatCache({"a": 3, "b": 5}), FlatCache({"a": 4, "b": 6})]
actual = tree_util.tree_transpose(outer_treedef, inner_treedef,
FlatCache({"a": [3, 4], "b": [5, 6]}))
self.assertEqual(expected, actual)
@unittest.skipIf(lib._xla_extension_version < 17,
"Test requires jaxlib 0.1.66.")
@parameterized.parameters([(*t, s) for t, s in zip(TREES, TREE_STRINGS)])
def testStringRepresentation(self, tree, correct_string):
"""Checks that the string representation of a tree works."""
treedef = tree_util.tree_structure(tree)
self.assertEqual(str(treedef), correct_string)
class RavelUtilTest(jtu.JaxTestCase):
def testFloats(self):
tree = [jnp.array([3.], jnp.float32),
jnp.array([[1., 2.], [3., 4.]], jnp.float32)]
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.float32)
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
def testInts(self):
tree = [jnp.array([3], jnp.int32),
jnp.array([[1, 2], [3, 4]], jnp.int32)]
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.int32)
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
def testMixedFloatInt(self):
tree = [jnp.array([3], jnp.int32),
jnp.array([[1., 2.], [3., 4.]], jnp.float32)]
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.promote_types(jnp.float32, jnp.int32))
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
def testMixedIntBool(self):
tree = [jnp.array([0], jnp.bool_),
jnp.array([[1, 2], [3, 4]], jnp.int32)]
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.promote_types(jnp.bool_, jnp.int32))
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
def testMixedFloatComplex(self):
tree = [jnp.array([1.], jnp.float32),
jnp.array([[1, 2 + 3j], [3, 4]], jnp.complex64)]
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.promote_types(jnp.float32, jnp.complex64))
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
def testEmpty(self):
tree = []
raveled, unravel = flatten_util.ravel_pytree(tree)
self.assertEqual(raveled.dtype, jnp.float32) # convention
tree_ = unravel(raveled)
self.assertAllClose(tree, tree_, atol=0., rtol=0.)
if __name__ == "__main__":
absltest.main(testLoader=jtu.JaxTestLoader())