code: def Normalize(in_channels, num_groups=32, act=""):
      return GroupNorm(
          num_groups=num_groups,
          num_channels=in_channels,
          eps=1e-6,
          affine=True,
          act=act,
      )
  
imports: import math
  from inspect import isfunction
  import torch
  import torch.nn.functional
  from apex.contrib.group_norm import GroupNorm
  from einops import rearrange
  from torch import einsum, nn
  from torch._dynamo import disable
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import checkpoint
label_desc: Use image node_id 8 for calling a global function with example usage: Normalize(in_channels, num_groups, act) and returns: GroupNorm