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from collections.abc import Iterable
from typing import Any, NoReturn, TypeVar
from typing_extensions import Self
from torch.utils._pytree import (
_dict_flatten,
_dict_flatten_with_keys,
_dict_unflatten,
_list_flatten,
_list_flatten_with_keys,
_list_unflatten,
Context,
register_pytree_node,
)
from ._compatibility import compatibility
__all__ = ["immutable_list", "immutable_dict"]
_help_mutation = """
If you are attempting to modify the kwargs or args of a torch.fx.Node object,
instead create a new copy of it and assign the copy to the node:
new_args = ... # copy and mutate args
node.args = new_args
""".strip()
_T = TypeVar("_T")
_KT = TypeVar("_KT")
_VT = TypeVar("_VT")
def _no_mutation(self: Any, *args: Any, **kwargs: Any) -> NoReturn:
raise TypeError(
f"{type(self).__name__!r} object does not support mutation. {_help_mutation}",
)
@compatibility(is_backward_compatible=True)
class immutable_list(list[_T]):
"""An immutable version of :class:`list`."""
__delitem__ = _no_mutation
__iadd__ = _no_mutation
__imul__ = _no_mutation
__setitem__ = _no_mutation
append = _no_mutation
clear = _no_mutation
extend = _no_mutation
insert = _no_mutation
pop = _no_mutation
remove = _no_mutation
reverse = _no_mutation
sort = _no_mutation
def __hash__(self) -> int: # type: ignore[override]
return hash(tuple(self))
def __reduce__(self) -> tuple[type[Self], tuple[tuple[_T, ...]]]:
return (type(self), (tuple(self),))
@compatibility(is_backward_compatible=True)
class immutable_dict(dict[_KT, _VT]):
"""An immutable version of :class:`dict`."""
__delitem__ = _no_mutation
__ior__ = _no_mutation
__setitem__ = _no_mutation
clear = _no_mutation
pop = _no_mutation
popitem = _no_mutation
setdefault = _no_mutation
update = _no_mutation # type: ignore[assignment]
def __hash__(self) -> int: # type: ignore[override]
return hash(frozenset(self.items()))
def __reduce__(self) -> tuple[type[Self], tuple[tuple[tuple[_KT, _VT], ...]]]:
return (type(self), (tuple(self.items()),))
# Register immutable collections for PyTree operations
def _immutable_list_flatten(d: immutable_list[_T]) -> tuple[list[_T], Context]:
return _list_flatten(d)
def _immutable_list_unflatten(
values: Iterable[_T],
context: Context,
) -> immutable_list[_T]:
return immutable_list(_list_unflatten(values, context))
def _immutable_dict_flatten(d: immutable_dict[Any, _VT]) -> tuple[list[_VT], Context]:
return _dict_flatten(d)
def _immutable_dict_unflatten(
values: Iterable[_VT],
context: Context,
) -> immutable_dict[Any, _VT]:
return immutable_dict(_dict_unflatten(values, context))
register_pytree_node(
immutable_list,
_immutable_list_flatten,
_immutable_list_unflatten,
serialized_type_name="torch.fx.immutable_collections.immutable_list",
flatten_with_keys_fn=_list_flatten_with_keys,
)
register_pytree_node(
immutable_dict,
_immutable_dict_flatten,
_immutable_dict_unflatten,
serialized_type_name="torch.fx.immutable_collections.immutable_dict",
flatten_with_keys_fn=_dict_flatten_with_keys,
)
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