mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
51 lines
2.6 KiB
51 lines
2.6 KiB
import torch.nn as nn
|
|
from typing import List
|
|
from colossalai.engine import BaseGradientHandler
|
|
from typing import Iterable
|
|
from torch.optim import Optimizer
|
|
from torch.optim.lr_scheduler import _LRScheduler
|
|
from ._gradient_accumulation import GradAccumDataloader, GradAccumOptimizer, GradAccumLrSchedulerByStep, GradAccumGradientHandler
|
|
|
|
__all__ = [
|
|
'accumulate_gradient', 'GradAccumDataloader', 'GradAccumOptimizer', 'GradAccumLrSchedulerByStep',
|
|
'GradAccumGradientHandler'
|
|
]
|
|
|
|
|
|
def accumulate_gradient(model: nn.Module,
|
|
optimizer: Optimizer,
|
|
dataloader: Iterable,
|
|
accumulate_size: int,
|
|
gradient_handlers: List[BaseGradientHandler] = None,
|
|
lr_scheduler: _LRScheduler = None):
|
|
r"""Turning model, optimizer, dataloader into corresponding object for gradient accumulation.
|
|
|
|
Args:
|
|
model (:class:`torch.nn.Module`): your model object for gradient accumulation.
|
|
optimizer (:class:`torch.optim.Optimizer`): your optimizer object for gradient accumulation.
|
|
dataloader (:class:`torch.utils.data.DataLoader` or iterable objects):
|
|
your dataloader object, would be called like iter(dataloader)
|
|
accumulate_size (int): the number of steps to accumulate gradients
|
|
gradient_handlers (List[:class:`colossalai.engine.BaseGradientHandler`]):
|
|
list of gradient handler objects. Default is None.
|
|
lr_scheduler (`torch.optim.lr_scheduler` or `colossalai.nn.lr_scheduler`):
|
|
your ``lr_scheduler`` object for gradient accumulation. Defaults to None.
|
|
|
|
More details about `gradient_handlers` could be found in
|
|
`Gradient_handler <https://github.com/hpcaitech/ColossalAI/tree/main/colossalai/engine/gradient_handler>`_.
|
|
|
|
More details about `lr_scheduler` could be found
|
|
`lr_scheduler <https://github.com/hpcaitech/ColossalAI/tree/main/colossalai/nn/lr_scheduler>`_. and
|
|
`how to adjust learning rate <https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate>`_.
|
|
"""
|
|
optimizer = GradAccumOptimizer(optimizer, accumulate_size=accumulate_size, model=model)
|
|
dataloader = GradAccumDataloader(dataloader, accumulate_size=accumulate_size)
|
|
|
|
if gradient_handlers is not None:
|
|
gradient_handlers = [GradAccumGradientHandler(handler, accumulate_size) for handler in gradient_handlers]
|
|
|
|
if lr_scheduler is not None:
|
|
lr_scheduler = GradAccumLrSchedulerByStep(lr_scheduler, accumulate_size=accumulate_size)
|
|
|
|
return optimizer, dataloader, gradient_handlers, lr_scheduler
|