code: def _make_scratch(in_shape, out_shape, groups=1, expand=False):
      scratch = nn.Module()
  
      out_shape1 = out_shape
      out_shape2 = out_shape
      out_shape3 = out_shape
      out_shape4 = out_shape
      if expand == True:
          out_shape1 = out_shape
          out_shape2 = out_shape * 2
          out_shape3 = out_shape * 4
          out_shape4 = out_shape * 8
  
      scratch.layer1_rn = nn.Conv2d(
          in_shape[0],
          out_shape1,
          kernel_size=3,
          stride=1,
          padding=1,
          bias=False,
          groups=groups,
      )
      scratch.layer2_rn = nn.Conv2d(
          in_shape[1],
          out_shape2,
          kernel_size=3,
          stride=1,
          padding=1,
          bias=False,
          groups=groups,
      )
      scratch.layer3_rn = nn.Conv2d(
          in_shape[2],
          out_shape3,
          kernel_size=3,
          stride=1,
          padding=1,
          bias=False,
          groups=groups,
      )
      scratch.layer4_rn = nn.Conv2d(
          in_shape[3],
          out_shape4,
          kernel_size=3,
          stride=1,
          padding=1,
          bias=False,
          groups=groups,
      )
  
      return scratch
  
imports: import torch
  import torch.nn
  from .vit import _make_pretrained_vitb16_384, _make_pretrained_vitb_rn50_384, _make_pretrained_vitl16_384
label_desc: Use image node_id 2 for calling a global function with example usage: _make_scratch(in_shape, out_shape, groups, expand) and returns: scratch