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Group_Normalization_pytorch

Statement

  • Class GroupNorm1D(in_channels, G, channels_per_group, eps=1e-5) for 1D features.
  • Class GroupNorm2D, GroupNorm3D for 2D and 3D features.
  • If you want to group normalization to process higher dimension features, you can Class GroupNormND(ND, in_channels, G, channels_per_group, eps=1e-5). For example, **GroupNormND(4, ...) for 4D features.
  • Parameter G means group number.
  • Parameter channels_per_group means channel number in each group.
  • Only can assign a integer to one parameter and assign None to another.
  • You can find the the code of group normalization in lib/group_normalization.py.
  • If there is something wrong in my code, please contact me, thanks!

Environment

  • python 3.6
  • pytorch 0.4.0

Visualization of Loss

  • Train loss of batch size 128.

  • Test loss of batch size 128.

  • Test loss of batch size 2.