code: def AGN(
      num_features: int,
      num_groups: int,
      eps=1e-5,
      affine=True,
      activation=ACT_RELU,
      slope=0.01,
      inplace=True,
  ):
      gn = nn.GroupNorm(
          num_channels=num_features,
          num_groups=num_groups,
          eps=eps,
          affine=affine,
      )
      act = instantiate_activation_block(
          activation, inplace=inplace, slope=slope
      )
      return nn.Sequential(OrderedDict([("gn", gn), (activation, act)]))
  
imports: from collections import OrderedDict
  import torch
  from torch import nn
  from torch.nn import functional
  from .identity import Identity
label_desc: Use image node_id 15 for calling a global function with example usage: AGN(num_features, num_groups, eps, affine, activation, slope, inplace) and returns: nn