rocm_jax/jax/tree_util.py

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# Copyright 2018 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.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
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from collections import namedtuple
import itertools as it
from six.moves import reduce
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from .util import unzip2, concatenate, partial, safe_map
map = safe_map
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def tree_map(f, tree):
"""Map a function over a pytree to produce a new pytree.
Args:
f: function to be applied at each leaf.
tree: a pytree to be mapped over.
Returns:
A new pytree with the same structure as `tree` but with the value at each
leaf given by `f(x)` where `x` is the value at the corresponding leaf in
`tree`.
"""
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node_type = node_types.get(type(tree))
if node_type:
children, node_spec = node_type.to_iterable(tree)
new_children = [tree_map(f, child) for child in children]
return node_type.from_iterable(node_spec, new_children)
else:
return f(tree)
def tree_multimap(f, tree, *rest):
"""Map a multi-input function over pytree args to produce a new pytree.
Args:
f: function that takes `1 + len(rest)` arguments, to be applied at the
corresponding leaves of the pytrees.
tree: a pytree to be mapped over, with each leaf providing the first
positional argument to `f`.
*rest: a tuple of pytrees, each with the same structure as `tree`.
Returns:
A new pytree with the same structure as `tree` but with the value at each
leaf given by `f(x, *xs)` where `x` is the value at the corresponding leaf
in `tree` and `xs` is the tuple of values at corresponding leaves in `rest`.
"""
# equivalent to prefix_multimap(f, tree_structure(tree), tree, *rest)
node_type = node_types.get(type(tree))
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if node_type:
children, node_spec = node_type.to_iterable(tree)
all_children = [children]
for other_tree in rest:
other_node_type = node_types.get(type(other_tree))
# TODO(mattjj): enable this check
# if node_type != other_node_type:
# raise TypeError('Mismatch: {} != {}'.format(other_node_type, node_type))
other_children, other_node_data = node_type.to_iterable(other_tree)
if other_node_data != node_spec:
raise TypeError('Mismatch: {} != {}'.format(other_node_data, node_spec))
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all_children.append(other_children)
new_children = [tree_multimap(f, *xs) for xs in zip(*all_children)]
return node_type.from_iterable(node_spec, new_children)
else:
return f(tree, *rest)
def prefix_multimap(f, treedef, tree, *rest):
"""Like tree_multimap but only maps down through a tree prefix."""
if treedef is leaf:
return f(tree, *rest)
else:
node_type = node_types.get(type(tree))
if node_type != treedef.node_type:
raise TypeError('Mismatch: {} != {}'.format(treedef.node_type, node_type))
children, node_data = node_type.to_iterable(tree)
if node_data != treedef.node_data:
raise TypeError('Mismatch: {} != {}'.format(treedef.node_data, node_data))
all_children = [children]
for other_tree in rest:
other_children, other_node_data = node_type.to_iterable(other_tree)
if other_node_data != node_data:
raise TypeError('Mismatch: {} != {}'.format(other_node_data, node_data))
all_children.append(other_children)
all_children = zip(*all_children)
new_children = [prefix_multimap(f, td, *xs)
for td, xs in zip(treedef.children, all_children)]
return node_type.from_iterable(node_data, new_children)
def tree_mimomap(f, tree, *rest):
"""Map a multi-input tuple-output over pytree args to form a tuple of pytrees.
Args:
f: function that takes `1 + len(rest)` arguments and returns a tuple, to be
applied at the corresponding leaves of the pytrees.
tree: a pytree to be mapped over, with each leaf providing the first
positional argument to `f`.
*rest: a tuple of pytrees, each with the same structure as `tree`.
Returns:
A tuple of pytrees with length given by the length of the output of `f` and
with each pytree element having the same structure as `tree`.
"""
flat, treedef = tree_flatten(tree)
rest_flat, treedefs = unzip2(map(tree_flatten, rest))
if not all(td == treedef for td in treedefs):
td = next(td for td in treedefs if td != treedef)
raise TypeError('Mismatch: {} != {}'.format(treedef, td))
out_flat = zip(*map(f, flat, *rest_flat))
return tuple(map(partial(tree_unflatten, treedef), out_flat))
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def tree_reduce(f, tree):
flat, _ = tree_flatten(tree)
return reduce(f, flat)
def tree_all(tree):
flat, _ = tree_flatten(tree)
return all(flat)
def process_pytree(process_node, tree):
return walk_pytree(process_node, lambda x: x, tree)
def walk_pytree(f_node, f_leaf, tree):
node_type = node_types.get(type(tree))
if node_type:
children, node_spec = node_type.to_iterable(tree)
proc_children, child_specs = unzip2([walk_pytree(f_node, f_leaf, child)
for child in children])
tree_def = PyTreeDef(node_type, node_spec, child_specs)
return f_node(proc_children), tree_def
else:
return f_leaf(tree), leaf
def build_tree(treedef, xs):
if treedef is leaf:
return xs
else:
# We use 'iter' for clearer error messages
children = map(build_tree, iter(treedef.children), iter(xs))
return treedef.node_type.from_iterable(treedef.node_data, children)
tree_flatten = partial(walk_pytree, concatenate, lambda x: [x])
def tree_unflatten(treedef, xs):
return _tree_unflatten(iter(xs), treedef)
def _tree_unflatten(xs, treedef):
if treedef is leaf:
return next(xs)
else:
children = map(partial(_tree_unflatten, xs), treedef.children)
return treedef.node_type.from_iterable(treedef.node_data, children)
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def tree_transpose(outer_treedef, inner_treedef, pytree_to_transpose):
flat, treedef = tree_flatten(pytree_to_transpose)
expected_treedef = _nested_treedef(inner_treedef, outer_treedef)
if treedef != expected_treedef:
raise TypeError("Mismatch\n{}\n != \n{}".format(treedef, expected_treedef))
inner_size = _num_leaves(inner_treedef)
outer_size = _num_leaves(outer_treedef)
flat = iter(flat)
lol = [[next(flat) for _ in range(inner_size)] for __ in range(outer_size)]
transposed_lol = zip(*lol)
subtrees = map(partial(tree_unflatten, outer_treedef), transposed_lol)
return tree_unflatten(inner_treedef, subtrees)
def _num_leaves(treedef):
return 1 if treedef is leaf else sum(map(_num_leaves, treedef.children))
def _nested_treedef(inner, outer):
# just used in tree_transpose error checking
if outer is leaf:
return inner
else:
children = map(partial(_nested_treedef, inner), outer.children)
return PyTreeDef(outer.node_type, outer.node_data, tuple(children))
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def tree_structure(tree):
_, spec = process_pytree(lambda _: None, tree)
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return spec
class PyTreeDef(object):
def __init__(self, node_type, node_data, children):
self.node_type = node_type
self.node_data = node_data
self.children = children
def __repr__(self):
if self.node_data is None:
data_repr = ""
else:
data_repr = "[{}]".format(self.node_data)
return "PyTree({}{}, [{}])".format(self.node_type.name, data_repr,
','.join(map(repr, self.children)))
def __hash__(self):
return hash((self.node_type, self.node_data, tuple(self.children)))
def __eq__(self, other):
if other is leaf:
return False
else:
return (self.node_type == other.node_type and
self.node_data == other.node_data and
self.children == other.children)
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def __ne__(self, other):
return not self == other
class PyLeaf(object):
def __repr__(self):
return '*'
leaf = PyLeaf()
def dict_to_iterable(xs):
keys = tuple(sorted(xs.keys()))
return tuple(map(xs.get, keys)), keys
class NodeType(object):
def __init__(self, name, to_iterable, from_iterable):
self.name = name
self.to_iterable = to_iterable
self.from_iterable = from_iterable
node_types = {}
def register_pytree_node(py_type, to_iterable, from_iterable):
assert py_type not in node_types
node_types[py_type] = NodeType(str(py_type), to_iterable, from_iterable)
register_pytree_node(tuple, lambda xs: (xs, None), lambda _, xs: tuple(xs))
register_pytree_node(list, lambda xs: (tuple(xs), None), lambda _, xs: list(xs))
register_pytree_node(dict, dict_to_iterable, lambda keys, xs: dict(zip(keys, xs)))
register_pytree_node(type(None), lambda z: ((), None), lambda _, xs: None)