ai-content-maker/.venv/Lib/site-packages/torch/fx/experimental/unification/utils.py

106 lines
2.8 KiB
Python

__all__ = ["hashable", "transitive_get", "raises", "reverse_dict", "xfail", "freeze"]
def hashable(x):
try:
hash(x)
return True
except TypeError:
return False
def transitive_get(key, d):
""" Transitive dict.get
>>> d = {1: 2, 2: 3, 3: 4}
>>> d.get(1)
2
>>> transitive_get(1, d)
4
"""
while hashable(key) and key in d:
key = d[key]
return key
def raises(err, lamda):
try:
lamda()
return False
except err:
return True
# Taken from theano/theano/gof/sched.py
# Avoids licensing issues because this was written by Matthew Rocklin
def _toposort(edges):
""" Topological sort algorithm by Kahn [1] - O(nodes + vertices)
inputs:
edges - a dict of the form {a: {b, c}} where b and c depend on a
outputs:
L - an ordered list of nodes that satisfy the dependencies of edges
>>> # xdoctest: +SKIP
>>> _toposort({1: (2, 3), 2: (3, )})
[1, 2, 3]
Closely follows the wikipedia page [2]
[1] Kahn, Arthur B. (1962), "Topological sorting of large networks",
Communications of the ACM
[2] http://en.wikipedia.org/wiki/Toposort#Algorithms
"""
incoming_edges = reverse_dict(edges)
incoming_edges = {k: set(val) for k, val in incoming_edges.items()}
S = ({v for v in edges if v not in incoming_edges})
L = []
while S:
n = S.pop()
L.append(n)
for m in edges.get(n, ()):
assert n in incoming_edges[m]
incoming_edges[m].remove(n)
if not incoming_edges[m]:
S.add(m)
if any(incoming_edges.get(v, None) for v in edges):
raise ValueError("Input has cycles")
return L
def reverse_dict(d):
"""Reverses direction of dependence dict
>>> d = {'a': (1, 2), 'b': (2, 3), 'c':()}
>>> reverse_dict(d) # doctest: +SKIP
{1: ('a',), 2: ('a', 'b'), 3: ('b',)}
:note: dict order are not deterministic. As we iterate on the
input dict, it make the output of this function depend on the
dict order. So this function output order should be considered
as undeterministic.
"""
result = {} # type: ignore[var-annotated]
for key in d:
for val in d[key]:
result[val] = result.get(val, tuple()) + (key, )
return result
def xfail(func):
try:
func()
raise Exception("XFailed test passed") # pragma:nocover
except Exception:
pass
def freeze(d):
""" Freeze container to hashable form
>>> freeze(1)
1
>>> freeze([1, 2])
(1, 2)
>>> freeze({1: 2}) # doctest: +SKIP
frozenset([(1, 2)])
"""
if isinstance(d, dict):
return frozenset(map(freeze, d.items()))
if isinstance(d, set):
return frozenset(map(freeze, d))
if isinstance(d, (tuple, list)):
return tuple(map(freeze, d))
return d