Source code for mmselfsup.core.hooks.momentum_update_hook

# Copyright (c) OpenMMLab. All rights reserved.
from math import cos, pi

from mmcv.parallel import is_module_wrapper
from mmcv.runner import HOOKS, Hook


@HOOKS.register_module(name=['BYOLHook', 'MomentumUpdateHook'])
class MomentumUpdateHook(Hook):
    """Hook for updating momentum parameter, used by BYOL, MoCoV3, etc.

    This hook includes momentum adjustment following:

    .. math::
        m = 1 - (1 - m_0) * (cos(pi * k / K) + 1) / 2

    where :math:`k` is the current step, :math:`K` is the total steps.

    Args:
        end_momentum (float): The final momentum coefficient
            for the target network. Defaults to 1.
        update_interval (int, optional): The momentum update interval of the
            weights. Defaults to 1.
    """

    def __init__(self, end_momentum=1., update_interval=1, **kwargs):
        self.end_momentum = end_momentum
        self.update_interval = update_interval

    def before_train_iter(self, runner):
        assert hasattr(runner.model.module, 'momentum'), \
            "The runner must have attribute \"momentum\" in algorithms."
        assert hasattr(runner.model.module, 'base_momentum'), \
            "The runner must have attribute \"base_momentum\" in algorithms."
        if self.every_n_iters(runner, self.update_interval):
            cur_iter = runner.iter
            max_iter = runner.max_iters
            base_m = runner.model.module.base_momentum
            m = self.end_momentum - (self.end_momentum - base_m) * (
                cos(pi * cur_iter / float(max_iter)) + 1) / 2
            runner.model.module.momentum = m

    def after_train_iter(self, runner):
        if self.every_n_iters(runner, self.update_interval):
            if is_module_wrapper(runner.model):
                runner.model.module.momentum_update()
            else:
                runner.model.momentum_update()