Spaces:
Build error
Build error
# Copyright (c) Meta Platforms, Inc. and affiliates. | |
# All rights reserved. | |
# | |
# This source code is licensed under the license found in the | |
# LICENSE file in the root directory of this source tree. | |
from collections import defaultdict | |
import logging | |
import typing as tp | |
import flashy | |
import torch | |
from ..optim import ModuleDictEMA | |
from .utils import copy_state | |
logger = logging.getLogger(__name__) | |
class BestStateDictManager(flashy.state.StateDictSource): | |
"""BestStateDictManager maintains a copy of best state_dict() for registered sources. | |
BestStateDictManager has two main attributes: | |
states (dict): State dict of the registered StateDictSource. | |
param_ids (dict): Dict of parameter ids for registered states from ModuleDictEMA and other sources. | |
When registering new sources, the BestStateDictManager will ensure two conflicting sources between | |
ModuleDictEMA and original modules are not both registered as it would otherwise create ambiguity about | |
what to consider for best state. | |
Args: | |
device (torch.device or str): Device on which we keep the copy. | |
dtype (torch.dtype): Data type for the state parameters. | |
""" | |
def __init__(self, device: tp.Union[torch.device, str] = 'cpu', | |
dtype: tp.Optional[torch.dtype] = None): | |
self.device = device | |
self.states: dict = {} | |
self.param_ids: dict = defaultdict(dict) | |
self.dtype = dtype | |
def _get_parameter_ids(self, state_dict): | |
return {id(p): name for name, p in state_dict.items() if isinstance(p, torch.Tensor)} | |
def _validate_no_parameter_ids_overlap(self, name: str, param_ids: dict): | |
for registered_name, registered_param_ids in self.param_ids.items(): | |
if registered_name != name: | |
overlap = set.intersection(registered_param_ids.keys(), param_ids.keys()) | |
assert len(overlap) == 0, f"Found {len(overlap)} / {len(param_ids.keys())} overlapping parameters" | |
f" in {name} and already registered {registered_name}: {' '.join(overlap)}" | |
def update(self, name: str, source: flashy.state.StateDictSource): | |
if name not in self.states: | |
raise ValueError(f"{name} missing from registered states.") | |
self.states[name] = copy_state(source.state_dict(), device=self.device, dtype=self.dtype) | |
def register(self, name: str, source: flashy.state.StateDictSource): | |
if name in self.states: | |
raise ValueError(f"{name} already present in states.") | |
# Registering parameter ids for EMA and non-EMA states allows us to check that | |
# there is no overlap that would create ambiguity about how to handle the best state | |
param_ids = self._get_parameter_ids(source.state_dict()) | |
if isinstance(source, ModuleDictEMA): | |
logger.debug(f"Registering to best state: ModuleDictEMA '{name}' with {len(param_ids)} params") | |
self._validate_no_parameter_ids_overlap(name, param_ids) | |
self.param_ids[name] = param_ids | |
else: | |
logger.debug(f"Registering to best state: StateDictSource '{name}' with {len(param_ids)} params") | |
self._validate_no_parameter_ids_overlap('base', param_ids) | |
self.param_ids['base'].update(param_ids) | |
# Register state | |
self.states[name] = copy_state(source.state_dict(), device=self.device, dtype=self.dtype) | |
def state_dict(self) -> flashy.state.StateDict: | |
return self.states | |
def load_state_dict(self, state: flashy.state.StateDict): | |
for name, sub_state in state.items(): | |
for k, v in sub_state.items(): | |
self.states[name][k].copy_(v) | |