# mypy: allow-untyped-defs # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the BSD license found in the # LICENSE file in the root directory of this source tree. import contextlib import copy from abc import ABC, abstractmethod from typing import ( Any, Callable, cast, Dict, Generator, Iterable, Optional, Sequence, Set, Tuple, Type, Union, ) import torch.nn as nn __all__ = [ "always_wrap_policy", "lambda_auto_wrap_policy", "transformer_auto_wrap_policy", "size_based_auto_wrap_policy", "enable_wrap", "wrap", "CustomPolicy", "ModuleWrapPolicy", ] # NOTE: We intentionally keep this function simple and isolate the complexity # to `fn` to enable using this function generically. We may move this to a # non-FSDP-specific folder and/or make it public in the future. def _post_order_apply( root_module: nn.Module, fn: Callable[[nn.Module], Optional[nn.Module]], ): """ This applies ``fn`` to every module in the module tree of ``root_module`` following a post-order traversal. If ``fn`` returns an :class:`nn.Module`, then this replaces the original module with the newly returned one in the tree. Otherwise, ``fn`` should return ``None``, in which case the module is not changed. """ # Track visited modules to avoid visiting shared modules multiple times visited_modules: Set[nn.Module] = {root_module} def _post_order_apply_inner( module: nn.Module, module_name: str, parent_module: Optional[nn.Module], ): for child_module_name, child_module in module.named_children(): if child_module not in visited_modules: visited_modules.add(child_module) _post_order_apply_inner(child_module, child_module_name, module) optional_module = fn(module) if optional_module is not None: assert isinstance(parent_module, nn.Module), ( "Non-root modules should have their parent module set but got " f"{parent_module} for {module}" ) assert module_name, ( "Non-root modules should have their module name set but got " f"an empty module name for {module}" ) assert isinstance( optional_module, nn.Module ), f"fn should return None or an nn.Module but got {optional_module}" setattr(parent_module, module_name, optional_module) _post_order_apply_inner(root_module, "", None) def _construct_wrap_fn( root_module: nn.Module, target_module_to_kwargs: Dict[nn.Module, Dict[str, Any]], fsdp_fn: Callable, ) -> Callable[[nn.Module], Optional[nn.Module]]: """ This constructs the "wrap" function to pass to :func:`_post_order_apply` based on ``target_module_to_kwargs``, which should be constructed from the wrapping policy. """ def fn(module: nn.Module) -> Optional[nn.Module]: # Explicitly avoid wrapping the root module since for FSDP, it is # handled by the caller if module in target_module_to_kwargs and module is not root_module: kwargs = target_module_to_kwargs[module] return fsdp_fn(module, **kwargs) return None return fn def _run_mixed_precision_override_policy( root_module: nn.Module, module_classes: Iterable[Type[nn.Module]], ignored_modules: Set[nn.Module], root_kwargs: Dict[str, Any], target_module_to_kwargs: Dict[nn.Module, Dict[str, Any]], ): module_classes_tuple = tuple(set(module_classes)) for module in root_module.modules(): if module in ignored_modules: continue elif isinstance(module, module_classes_tuple): # This policy overrides any existing policy if module not in target_module_to_kwargs: # Only inherit from the root kwargs if not already specified target_module_to_kwargs[module] = root_kwargs target_module_to_kwargs[module]["mixed_precision"] = None return target_module_to_kwargs def always_wrap_policy(*args, **kwargs) -> bool: """ A simple recursive wrap policy that always returns ``True``. This means that every submodule is wrapped by the wrapper class in :func:`_recursive_wrap`. """ return True class _Policy(ABC): """ This defines an abstract base class that represents a policy for applying a module-level API. """ @abstractmethod def _run_policy( self, root_module: nn.Module, ignored_modules: Set[nn.Module], root_kwargs: Dict[str, Any], ) -> Dict[nn.Module, Dict[str, Any]]: """ This should return a dict ``target_module_to_kwargs`` that maps from each target module to wrap to its kwargs. """ ... def _module_wrap_policy( module: nn.Module, recurse: bool, nonwrapped_numel: int, module_classes: Set[Type[nn.Module]], ) -> bool: """ This auto wrap policy wraps every module that is an instance of any type in ``module_classes`` as its own FSDP instance. The root module given by ``module`` is always wrapped as an FSDP instance regardless. Since the wrapping proceeds bottom up, each FSDP instance manages the parameters in its subtree excluding any already managed by a child FSDP instance. Args: module (nn.Module): Current module being considered. recurse (bool): If ``False``, then this function must decide whether ``module`` should be wrapped as an FSDP instance or not. If ``True``, then the function is still recursing down the module tree as a part of the DFS. nonwrapped_numel (int): Parameter numel not yet wrapped. module_classes (Set[Type[nn.Module]]): Set of module classes that are wrapped as FSDP instances. Returns: ``True`` if ``recurse=True``, and whether ``module`` should be wrapped if ``recurse=False``. """ if recurse: return True # always recurse return isinstance(module, tuple(module_classes)) class ModuleWrapPolicy(_Policy): """ This policy applies to every module of the specified module classes, passing in the kwargs given to the root. """ def __init__(self, module_classes: Iterable[Type[nn.Module]]): module_classes_set = set(module_classes) self._module_classes = module_classes_set self._module_classes_str = str(module_classes_set) def _run_policy( self, root_module: nn.Module, ignored_modules: Set[nn.Module], root_kwargs: Dict[str, Any], ) -> Dict[nn.Module, Dict[str, Any]]: module_classes = tuple(self._module_classes) target_module_to_kwargs: Dict[nn.Module, Dict[str, Any]] = {} for module in root_module.modules(): if module in ignored_modules: continue elif isinstance(module, module_classes): # Shallow copy to avoid coupling changes across modules target_module_to_kwargs[module] = copy.copy(root_kwargs) return target_module_to_kwargs def __call__(self, module, recurse, *args, **kwargs): # nonwrapped_numel is not used. return _module_wrap_policy( module, recurse, nonwrapped_numel=-1, module_classes=self._module_classes ) def __repr__(self) -> str: return super().__repr__() + f"({self._module_classes_str})" class CustomPolicy(_Policy): """ This policy takes in a lambda function that maps a given ``nn.Module`` to either ``False``, ``True``, or a kwarg dictionary. - If the function returns ``False`` or an empty dictionary, then the module does not have the API applied. - If the function returns ``True``, then the module has the API applied with the root's kwargs. - If the function returns a non-empty dictionary, then the module has the API applied, and the dictionary overrides the root's kwargs. Example:: >>> # xdoctest: +SKIP("undefined variables") >>> model = init_transformer_model(...) >>> def lambda_fn(module: nn.Module): >>> if module is model.lm_head: >>> return {"sharding_strategy": ShardingStrategy.SHARD_GRAD_OP} >>> elif isinstance(module, TransformerBlock): >>> return True >>> return False >>> policy = CustomPolicy(lambda_fn) >>> fsdp_model = FSDP(model, auto_wrap_policy=policy) """ def __init__(self, lambda_fn: Callable[[nn.Module], Union[bool, Dict[str, Any]]]): self._lambda_fn = lambda_fn def _run_policy( self, root_module: nn.Module, ignored_modules: Set[nn.Module], root_kwargs: Dict[str, Any], ) -> Dict[nn.Module, Dict[str, Any]]: target_module_to_kwargs: Dict[nn.Module, Dict[str, Any]] = {} for module in root_module.modules(): if module in ignored_modules: continue res = self._lambda_fn(module) if not isinstance(res, (dict, bool)): raise ValueError( "The lambda_fn passed to CustomPolicy should return " f"False/True or a kwarg dict, but it returned {res}" ) if not res: continue kwargs = copy.copy(root_kwargs) if isinstance(res, dict): # Override the root kwargs with the ones specified by the # lambda function kwargs.update(res) target_module_to_kwargs[module] = kwargs return target_module_to_kwargs def lambda_auto_wrap_policy( module: nn.Module, recurse: bool, nonwrapped_numel: int, lambda_fn: Callable ) -> bool: """ A convenient auto wrap policy to wrap submodules based on an arbitrary user function. If `lambda_fn(submodule) == True``, the submodule will be wrapped as a `wrapper_cls` unit. Return if a module should be wrapped during auto wrapping. The first three parameters are required by :func:`_recursive_wrap`. Args: module (nn.Module): Current module being considered. recurse (bool): If ``False``, then this function must decide whether ``module`` should be wrapped as an FSDP instance or not. If ``True``, then the function is still recursing down the module tree as a part of the DFS. nonwrapped_numel (int): Parameter numel not yet wrapped. lambda_fn (Callable[[nn.Module], bool]): If this returns ``True``, then this module will be wrapped. """ if recurse: return True # always recurse return lambda_fn(module) def transformer_auto_wrap_policy( module: nn.Module, recurse: bool, nonwrapped_numel: int, transformer_layer_cls: Set[Type[nn.Module]], ) -> bool: """ See :func:`_module_wrap_policy`, where ``transformer_layer_cls`` is the same as ``module_classes``. Note that shared parameters must be wrapped in the same FSDP instance, so this auto wrap policy can help wrap shared embeddings into the same FSDP instance for transformer models. """ return _module_wrap_policy(module, recurse, nonwrapped_numel, transformer_layer_cls) def _wrap_module_cls_individually( module: nn.Module, module_classes: Sequence[type], recurse: bool, *args, **kwargs ): if recurse: # always recurse return True else: # if not recursing, decide whether we should wrap based on whether the type of module # is in `module_classes`. return isinstance(module, tuple(module_classes)) def _or_policy( module: nn.Module, recurse: bool, nonwrapped_numel: int, policies, ) -> bool: """ A policy that wraps ``module`` if any policy in the passed in iterable of ``policies`` returns ``True``. """ return any( policy(module=module, recurse=recurse, nonwrapped_numel=nonwrapped_numel) for policy in policies ) def size_based_auto_wrap_policy( module: nn.Module, recurse: bool, nonwrapped_numel: int, # Additional custom arguments min_num_params: int = int(1e8), force_leaf_modules: Optional[Set[Type[nn.Module]]] = None, exclude_wrap_modules: Optional[Set[Type[nn.Module]]] = None, ) -> bool: """ A size-based auto wrap policy. Args: module (nn.Module): Current module being considered. recurse (bool): If ``False``, then this function must decide whether ``module`` should be wrapped as an FSDP instance or not. If ``True``, then the function is still recursing down the module tree as a part of the DFS. nonwrapped_numel (int): Parameter numel not yet wrapped. min_num_params (int): Customizable policy input that controls the size threshold over which a module is ready to be wrapped. This is in units of numel. force_leaf_modules (Set[Type[nn.Module]]): Set of module types to keep as leaves, i.e. their children will never be wrapped. exclude_wrap_modules (Set[Type[nn.Module]]): Set of module types to be excluded in wrapping. Returns: Whether ``module`` should be wrapped. """ force_leaf_modules = ( size_based_auto_wrap_policy.FORCE_LEAF_MODULES # type: ignore[attr-defined] if force_leaf_modules is None else force_leaf_modules ) exclude_wrap_modules = ( size_based_auto_wrap_policy.EXCLUDE_WRAP_MODULES # type: ignore[attr-defined] if exclude_wrap_modules is None else exclude_wrap_modules ) # Keep the argument `min_num_params` for BC for now, but it represents the # minimum non-wrapped *numel* before triggering a wrapping min_nonwrapped_numel = min_num_params is_large = nonwrapped_numel >= min_nonwrapped_numel if recurse: # We should recurse if the module is big enough but not in force_leaf_modules list. return is_large and not isinstance(module, tuple(force_leaf_modules)) else: # If we are not recursing, determine if we should wrap. return is_large and not isinstance(module, tuple(exclude_wrap_modules)) # Set those defaults to the size_based_auto_wrap_policy function. Make them easy to be imported. size_based_auto_wrap_policy.EXCLUDE_WRAP_MODULES = {nn.ModuleList, nn.ModuleDict} # type: ignore[attr-defined] size_based_auto_wrap_policy.FORCE_LEAF_MODULES = {nn.MultiheadAttention} # type: ignore[attr-defined] @contextlib.contextmanager def enable_wrap( *, wrapper_cls: Any, **wrapper_kwargs: Any ) -> Generator[None, None, None]: """ Context manager to wrap modules using a wrapper. Useful for when you'd like to apply the same configuration arguments to all child modules that you wrap. A particularly important use case is wrapping large layers so that they get sharded (in-place) during initialization, to avoid running out of system memory. Large layers can indicate that they should be sharded via the ``wrap`` annotation and this context manager can provide the exact configuration for these nested instances. Usage:: with enable_wrap(wrapper_cls, **params): # Wraps layer in FSDP by default if within context self.l1 = wrap(torch.nn.Linear(5, 5)) Args: wrapper_cls: Class that `wrap` annotation will `wrap` modules with, such as `FullyShardedDataParallel`. **wrapper_kwargs: Configuration settings that will be passed to all ``wrap`` instances inside the context """ kwargs = { "wrapper_cls": wrapper_cls, **wrapper_kwargs, } with _ConfigAutoWrap(**kwargs): yield def wrap(module: nn.Module, **wrap_overrides: Any) -> nn.Module: """ Annotate that a module should be wrapped. Annotated modules will only be wrapped if inside of an :func:`enable_wrap` context manager. This allows a module to be initialized both with and without a wrapper without code change. The class that this function wraps the passed in ``nn.Module`` with is the passed in ``wrapper_cls`` argument into ``enable_wrap``. Both ``enable_wrap`` and ``wrap`` can take in kwargs specifying how to construct the ``wrapper_cls`` instance. In the case of duplicate kwargs in ``enable_wrap`` and ``wrap``, the argument passed into ``wrap`` will be respected. Usage:: with enable_wrap(wrapper_cls=FSDP, **fsdp_config): # Wraps layer in FSDP by default if within context self.l1 = wrap(torch.nn.Linear(5, 5)) Args: module (nn.Module): module to wrap (if in :func:`enable_wrap` context) **wrap_overrides: configuration overrides that will take priority over the values provided by the :func:`enable_wrap` context """ if _ConfigAutoWrap.in_autowrap_context: assert _ConfigAutoWrap.wrapper_cls is not None wrap_overrides = {**_ConfigAutoWrap.kwargs, **wrap_overrides} return _wrap( module, _ConfigAutoWrap.wrapper_cls, **wrap_overrides, ) return module def _wrap(module: nn.Module, wrapper_cls: Callable, **kwargs) -> nn.Module: assert wrapper_cls is not None if hasattr(module, "_wrap_overrides"): # If module has a _wrap_overrides attribute, we force overriding the # FSDP config with these attributes for this module. Currently this # is only used to disable mixed precision for BatchNorm when # auto_wrapping. overrides = {**kwargs, **module._wrap_overrides} # type: ignore[arg-type] return wrapper_cls(module, **overrides) return wrapper_cls(module, **kwargs) def _recursive_wrap( module: nn.Module, auto_wrap_policy: Callable, wrapper_cls: Callable, ignored_modules: Set[nn.Module], ignored_params: Set[nn.Parameter], only_wrap_children: bool = False, **kwargs: Any, ) -> Tuple[nn.Module, int]: """ Wraps submodules of ``module`` for which ``auto_wrap_policy`` returns ``True`` with ``wrapper_cls``. Args: module (nn.Module): Module to recursively wrap. auto_wrap_policy (Callable): A callable representing a policy that determines which modules to recursively wrap with ``wrapper_cls``. ignored_modules (Set[torch.nn.Module]): Modules to ignore when wrapping. ignored_params (Set[torch.nn.Parameter]): Parameters to ignore when wrapping; these should be the parameters contained in the modules in ``ignored_modules``. Returns: (nn.Module, int): ``module`` after wrapping and the numel recursively wrapped. """ assert auto_wrap_policy is not None, "Must specify auto_wrap_policy." assert wrapper_cls is not None, "Must specify wrapper_cls" # Make sure no child is already wrapped. for _, child in module.named_modules(): if child in ignored_modules: continue try: assert not isinstance(child, cast(type, wrapper_cls)) except TypeError: # wrapper_cls is a function as opposed to a class type, just bypass above check. pass # We count all params, assuming none of them are already wrapped. nonwrapped_numel = sum( p.numel() for p in module.parameters() if p not in ignored_params ) assert auto_wrap_policy is not None if auto_wrap_policy(module=module, recurse=True, nonwrapped_numel=nonwrapped_numel): total_wrapped_numel = 0 # Iterate through the children, recursively wrap if necessary for name, child in module.named_children(): if child in ignored_modules: continue wrapped_child, num_wrapped_params = _recursive_wrap( module=child, auto_wrap_policy=auto_wrap_policy, wrapper_cls=wrapper_cls, ignored_modules=ignored_modules, ignored_params=ignored_params, **kwargs, ) setattr(module, name, wrapped_child) # Keep track of how many parameters have been wrapped total_wrapped_numel += num_wrapped_params # decide if we need to wrap the current module, # since the left over parameters exceed the number of params to wrap remainder = nonwrapped_numel - total_wrapped_numel if not only_wrap_children and auto_wrap_policy( module=module, recurse=False, nonwrapped_numel=remainder ): # Leaf node or final wrapping of the remainder both happen here. return _wrap(module, wrapper_cls, **kwargs), nonwrapped_numel else: return module, total_wrapped_numel return module, 0 class _ConfigAutoWrap: """ Helper class to wrap modules based on default config args via a context manager. See :func:`enable_wrap` for more information. """ in_autowrap_context: bool = False # Context flag wrapper_cls: Optional[Callable] = None # The wrapper class kwargs: Dict[str, Any] = {} # Wrapper's args def __init__(self, **kwargs: Dict[str, Any]): self.kwargs = kwargs @staticmethod def enable_autowrap_context(kwargs: Any) -> None: if _ConfigAutoWrap.in_autowrap_context: raise NotImplementedError( "You are already within an autowrap context and we currently do not supported nested autowrap." ) _ConfigAutoWrap.in_autowrap_context = True # Get and save the wrapper cls for the context. assert ( "wrapper_cls" in kwargs.keys() ), "Expected to pass in wrapper_cls arg into _ConfigAutoWrap." _ConfigAutoWrap.wrapper_cls = cast(Callable, kwargs["wrapper_cls"]) del kwargs["wrapper_cls"] # Save the rest. _ConfigAutoWrap.kwargs = kwargs @staticmethod def disable_autowrap_context() -> None: _ConfigAutoWrap.in_autowrap_context = False _ConfigAutoWrap.wrapper_cls = None _ConfigAutoWrap.kwargs = {} def __enter__(self) -> None: self.enable_autowrap_context(self.kwargs) def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None: self.disable_autowrap_context()