# 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 from collections import namedtuple import itertools as it from six.moves import reduce from .util import unzip2, concatenate, partial, safe_map map = safe_map 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`. """ 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)) 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)) 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)) 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) 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)) def tree_structure(tree): _, spec = process_pytree(lambda _: None, tree) 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) 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)