| from typing import Callable, Any, Tuple, List, Dict, Type, NamedTuple | |
| from torch.utils._pytree import PyTree, TreeSpec, LeafSpec | |
| from collections import namedtuple | |
| FlattenFuncSpec = Callable[[PyTree, TreeSpec], List] | |
| SUPPORTED_NODES: Dict[Type[Any], Any] = {} | |
| def register_pytree_flatten_spec(typ: Any, flatten_fn_spec: FlattenFuncSpec) -> None: | |
| SUPPORTED_NODES[typ] = flatten_fn_spec | |
| def tree_flatten_spec(pytree: PyTree, spec: TreeSpec) -> List[Any]: | |
| if isinstance(spec, LeafSpec): | |
| return [pytree] | |
| if spec.type not in SUPPORTED_NODES: | |
| raise RuntimeError( | |
| f"{type(pytree)} does not have a flatten_fn_spec associated with it. Please register one with" | |
| "torch.fx._pytree.register_pytree_flatten_spec. If you have serialized your model, make" | |
| "sure that any custom pytrees have been registered before loading it.") | |
| flatten_fn_spec = SUPPORTED_NODES[spec.type] | |
| child_pytrees = flatten_fn_spec(pytree, spec) | |
| result = [] | |
| for child, child_spec in zip(child_pytrees, spec.children_specs): | |
| flat = tree_flatten_spec(child, child_spec) | |
| result += flat | |
| return result | |
| def _dict_flatten_spec(d: Dict[Any, Any], spec: TreeSpec) -> List[Any]: | |
| return list([d[k] for k in spec.context]) | |
| def _list_flatten_spec(d: List[Any], spec: TreeSpec) -> List[Any]: | |
| return [d[i] for i in range(len(spec.children_specs))] | |
| def _tuple_flatten_spec(d: Tuple[Any], spec: TreeSpec) -> List[Any]: | |
| return [d[i] for i in range(len(spec.children_specs))] | |
| def _namedtuple_flatten_spec(d: NamedTuple, spec: TreeSpec) -> List[Any]: | |
| return [d[i] for i in range(len(spec.children_specs))] | |
| register_pytree_flatten_spec(dict, _dict_flatten_spec) | |
| register_pytree_flatten_spec(list, _list_flatten_spec) | |
| register_pytree_flatten_spec(tuple, _tuple_flatten_spec) | |
| register_pytree_flatten_spec(namedtuple, _tuple_flatten_spec) | |