ai-content-maker/.venv/Lib/site-packages/torch/utils/weak.py

322 lines
11 KiB
Python

from __future__ import annotations
import weakref
from weakref import ref
from _weakrefset import _IterationGuard # type: ignore[attr-defined]
from collections.abc import MutableMapping, Mapping
from torch import Tensor
import collections.abc as _collections_abc
WeakRef = ref
__all__ = ['TensorWeakRef', 'WeakIdRef', 'WeakIdKeyDictionary', 'WeakTensorKeyDictionary']
# This file defines a variant of WeakKeyDictionary that overrides the hashing
# behavior of the key to use object identity, rather than the builtin
# __eq__/__hash__ functions. This is useful for Tensor weak keys, as their
# __eq__ implementation return a Tensor (elementwise equality), which means
# you can't use them directly with the WeakKeyDictionary in standard library.
#
# Our implementation strategy is to create a wrapper weak key object, which we
# use as a key in a stock Python dictionary. This is similar to how weakref
# implements WeakKeyDictionary, but instead of using weakref.ref as the
# wrapper, we use a custom wrapper that has different __eq__ and __hash__
# behavior. Note that we subsequently store this weak key directly in an
# ORDINARY dictionary, since the newly constructed WeakIdKey's only use would
# be a dictionary so it would have no strong references. Ensuring that
# only live WeakIdKeys are in the map is handled by putting finalizers on the
# original key object.
# It is simpler to implement this with composition, but if we want to
# directly reuse the callback mechanism on weakref, we need the weakref
# and the key to be exactly the same object. Reusing the callback mechanism
# minimizes the divergence between our implementation and Lib/weakref.py
#
# NB: Prefer using this when working with weakrefs of Tensors; e.g., do
# WeakIdRef(tensor) rather than weakref.ref(tensor); it handles a number of
# easy to get wrong cases transparently for you.
class WeakIdRef(weakref.ref):
__slots__ = ['_id']
def __init__(self, key, callback=None):
# Unlike stock weakref, which preserves hash semantics of the
# original object but lazily defers hash calls until the first
# time the user attempts to hash the weakref, we can eagerly
# cache the id of the key as we know this is definitely the hash
# method
self._id = id(key)
super().__init__(key, callback) # type: ignore[call-arg]
def __call__(self):
r = super().__call__()
# Special logic for Tensor PyObject resurrection
if hasattr(r, '_fix_weakref'):
r._fix_weakref() # type: ignore[union-attr]
return r
def __hash__(self):
return self._id
def __eq__(self, other):
# An attractive but wrong alternate implementation is to only test if
# the stored _ids match. This can lead to an ABA problem if you have:
#
# a1 = A()
# w1 = WeakIdRef(a1)
# del a1
# a2 = A() # suppose it gets the same ID as a1
# w2 = WeakIdRef(a2)
# print(w1 == w2)
#
# This should be False, as a1 and a2 are unrelated (and a1 is
# dead anyway)
a = self()
b = other()
if a is not None and b is not None:
return a is b
return self is other
# This is the same as WeakIdRef but equality is checked using hash() rather than id.
# This will be equivalent to the one above except for classes where hash is not their id.
class _WeakHashRef(weakref.ref):
__slots__ = ['_id']
def __init__(self, key, callback=None):
# Unlike stock weakref, which preserves hash semantics of the
# original object but lazily defers hash calls until the first
# time the user attempts to hash the weakref, we can eagerly
# cache the id of the key as we know this is definitely the hash
# method
self._id = hash(key)
super().__init__(key, callback) # type: ignore[call-arg]
def __call__(self):
r = super().__call__()
# Special logic for Tensor PyObject resurrection
if hasattr(r, '_fix_weakref'):
r._fix_weakref() # type: ignore[union-attr]
return r
def __hash__(self):
return self._id
def __eq__(self, other):
# Use hash equality to determine ref equality.
# ScriptObject implements __hash__ to return the wrapped IValue's id, so
# this is equivalent to doing an identity comparison.
a = self()
b = other()
if a is not None and b is not None:
return hash(a) == hash(b)
return self is other
# This is directly adapted from cpython/Lib/weakref.py
class WeakIdKeyDictionary(MutableMapping):
def __init__(self, dict=None, ref_type=WeakIdRef): # CHANGED
self.data = {}
self.ref_type = ref_type # CHANGED
def remove(k, selfref=ref(self)):
self = selfref()
if self is not None:
if self._iterating:
self._pending_removals.append(k)
else:
try:
del self.data[k]
except KeyError:
pass
self._remove = remove
# A list of dead weakrefs (keys to be removed)
self._pending_removals = []
self._iterating = set()
self._dirty_len = False
if dict is not None:
self.update(dict)
def _commit_removals(self):
# NOTE: We don't need to call this method before mutating the dict,
# because a dead weakref never compares equal to a live weakref,
# even if they happened to refer to equal objects.
# However, it means keys may already have been removed.
pop = self._pending_removals.pop
d = self.data
while True:
try:
key = pop()
except IndexError:
return
try:
del d[key]
except KeyError:
pass
def _scrub_removals(self):
d = self.data
self._pending_removals = [k for k in self._pending_removals if k in d]
self._dirty_len = False
def __delitem__(self, key):
self._dirty_len = True
del self.data[self.ref_type(key)] # CHANGED
def __getitem__(self, key):
return self.data[self.ref_type(key)] # CHANGED
def __len__(self):
if self._dirty_len and self._pending_removals:
# self._pending_removals may still contain keys which were
# explicitly removed, we have to scrub them (see issue #21173).
self._scrub_removals()
return len(self.data) - len(self._pending_removals)
def __repr__(self):
return f"<{self.__class__.__name__} at {id(self):#x}>"
def __setitem__(self, key, value):
self.data[self.ref_type(key, self._remove)] = value # CHANGED
def copy(self):
new = WeakIdKeyDictionary()
with _IterationGuard(self):
for key, value in self.data.items():
o = key()
if o is not None:
new[o] = value
return new
__copy__ = copy
def __deepcopy__(self, memo):
from copy import deepcopy
new = self.__class__()
with _IterationGuard(self):
for key, value in self.data.items():
o = key()
if o is not None:
new[o] = deepcopy(value, memo)
return new
def get(self, key, default=None):
return self.data.get(self.ref_type(key), default) # CHANGED
def __contains__(self, key):
try:
wr = self.ref_type(key) # CHANGED
except TypeError:
return False
return wr in self.data
def items(self):
with _IterationGuard(self):
for wr, value in self.data.items():
key = wr()
if key is not None:
yield key, value
def keys(self):
with _IterationGuard(self):
for wr in self.data:
obj = wr()
if obj is not None:
yield obj
__iter__ = keys
def values(self):
with _IterationGuard(self):
for wr, value in self.data.items():
if wr() is not None:
yield value
def keyrefs(self):
"""Return a list of weak references to the keys.
The references are not guaranteed to be 'live' at the time
they are used, so the result of calling the references needs
to be checked before being used. This can be used to avoid
creating references that will cause the garbage collector to
keep the keys around longer than needed.
"""
return list(self.data)
def popitem(self):
self._dirty_len = True
while True:
key, value = self.data.popitem()
o = key()
if o is not None:
return o, value
def pop(self, key, *args):
self._dirty_len = True
return self.data.pop(self.ref_type(key), *args) # CHANGED
def setdefault(self, key, default=None):
return self.data.setdefault(self.ref_type(key, self._remove), default) # CHANGED
def update(self, dict=None, **kwargs):
d = self.data
if dict is not None:
if not hasattr(dict, "items"):
dict = type({})(dict)
for key, value in dict.items():
d[self.ref_type(key, self._remove)] = value # CHANGED
if len(kwargs):
self.update(kwargs)
def __ior__(self, other):
self.update(other)
return self
def __or__(self, other):
if isinstance(other, _collections_abc.Mapping):
c = self.copy()
c.update(other)
return c
return NotImplemented
def __ror__(self, other):
if isinstance(other, _collections_abc.Mapping):
c = self.__class__()
c.update(other)
c.update(self)
return c
return NotImplemented
# Default Mapping equality will tests keys for equality, but
# we want to test ids for equality
def __eq__(self, other):
if not isinstance(other, Mapping):
return NotImplemented
return {id(k): v for k, v in self.items()} == {id(k): v for k, v in other.items()}
# Convenience alias
WeakTensorKeyDictionary = WeakIdKeyDictionary
class TensorWeakRef:
"""Wrapper around a weak ref of a Tensor that handles the _fix_weakref() call required when unwrapping a Tensor weakref."""
ref: WeakRef[Tensor]
def __init__(self, tensor: Tensor):
assert isinstance(tensor, Tensor)
self.ref = weakref.ref(tensor)
def __call__(self):
out = self.ref()
if out is None:
return out
assert isinstance(out, Tensor)
# TODO, add _fix_weakref type binding
out._fix_weakref() # type: ignore[attr-defined]
return out