torch/fx/immutable_collections.py

from typing import Any, Dict, Iterable, List, Tuple

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
"""


def _no_mutation(self, *args, **kwargs):
    raise NotImplementedError(
        f"'{type(self).__name__}' object does not support mutation. {_help_mutation}",
    )


def _create_immutable_container(base, mutable_functions):
    container = type("immutable_" + base.__name__, (base,), {})
    for attr in mutable_functions:
        setattr(container, attr, _no_mutation)
    return container


immutable_list = _create_immutable_container(
    list,
    (
        "__delitem__",
        "__iadd__",
        "__imul__",
        "__setitem__",
        "append",
        "clear",
        "extend",
        "insert",
        "pop",
        "remove",
        "reverse",
        "sort",
    ),
)
immutable_list.__reduce__ = lambda self: (immutable_list, (tuple(iter(self)),))
immutable_list.__hash__ = lambda self: hash(tuple(self))

compatibility(is_backward_compatible=True)(immutable_list)

immutable_dict = _create_immutable_container(
    dict,
    (
        "__delitem__",
        "__ior__",
        "__setitem__",
        "clear",
        "pop",
        "popitem",
        "setdefault",
        "update",
    ),
)
immutable_dict.__reduce__ = lambda self: (immutable_dict, (iter(self.items()),))
immutable_dict.__hash__ = lambda self: hash(tuple(self.items()))
compatibility(is_backward_compatible=True)(immutable_dict)


# Register immutable collections for PyTree operations
def _immutable_dict_flatten(d: Dict[Any, Any]) -> Tuple[List[Any], Context]:
    return _dict_flatten(d)


def _immutable_dict_unflatten(
    values: Iterable[Any],
    context: Context,
) -> Dict[Any, Any]:
    return immutable_dict(_dict_unflatten(values, context))


def _immutable_list_flatten(d: List[Any]) -> Tuple[List[Any], Context]:
    return _list_flatten(d)


def _immutable_list_unflatten(
    values: Iterable[Any],
    context: Context,
) -> List[Any]:
    return immutable_list(_list_unflatten(values, context))


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,
)
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,
)