MomentumAnnealingEMA¶
- class mmengine.model.MomentumAnnealingEMA(model, momentum=0.0002, gamma=100, interval=1, device=None, update_buffers=False)[source]¶
Exponential moving average (EMA) with momentum annealing strategy.
- Parameters
model (nn.Module) – The model to be averaged.
momentum (float) – The momentum used for updating ema parameter. Defaults to 0.0002. Ema’s parameter are updated with the formula \(averaged\_param = (1-momentum) * averaged\_param + momentum * source\_param\).
gamma (int) – Use a larger momentum early in training and gradually annealing to a smaller value to update the ema model smoothly. The momentum is calculated as max(momentum, gamma / (gamma + steps)) Defaults to 100.
interval (int) – Interval between two updates. Defaults to 1.
device (torch.device, optional) – If provided, the averaged model will be stored on the
device
. Defaults to None.update_buffers (bool) – if True, it will compute running averages for both the parameters and the buffers of the model. Defaults to False.
- Return type