SyncBatchNorm#

class SyncBatchNorm(num_features, eps=1e-5, momentum=0.9, affine=True, track_running_stats=True, freeze=False, group=WORLD, **kwargs)[source]#

Applies Synchronized Batch Normalization for distributed training.

Parameters:

  • num_features – usually \(C\) from an input of shape \((N, C, H, W)\) or the highest ranked dimension of an input less than 4D.

  • eps – a value added to the denominator for numerical stability. Default: 1e-5

  • momentum – the value used for the running_mean and running_var computation. Default: 0.9

  • affine – a boolean value that when set to True, this module has learnable affine parameters. Default: True

  • track_running_stats – when set to True, this module tracks the running mean and variance. When set to False, this module does not track such statistics and always uses batch statistics in both training and eval modes. Default: True

  • freeze – when set to True, this module does not update the running mean and variance, and uses the running mean and variance instead of the batch mean and batch variance to normalize the input. The parameter takes effect only when the module is initilized with track_running_stats as True. Default: False

  • group (Optional[Group]) – communication group, caculate mean and variance between this group. Default: WORLD