code: def __init__(self, dim):
      super().__init__()
      self.alpha = nn.Parameter(torch.ones((1, 1, dim)))
      self.beta = nn.Parameter(torch.zeros((1, 1, dim)))
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, GluMlp, GatedMlp, DropPath, lecun_normal_, to_2tuple
  from ._builder import build_model_with_cfg
  from ._manipulate import named_apply, checkpoint_seq
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
label_desc: Use image node_id 1 to create a new Affine object from inherited base classes: nn with example: obj = Affine(dim)