class_docstr: A single linear layer which does a 1x1 conv
class_docstr_tok: ["A","single","linear","layer","which","does","a","1x1","conv"]
code: def __init__(self, chn_in, chn_out=1, use_dropout=False):
      super(NetLinLayer, self).__init__()
      layers = (
          [
              nn.Dropout(),
          ]
          if (use_dropout)
          else []
      )
      layers += [
          nn.Conv2d(
              chn_in, chn_out, 1, stride=1, padding=0, bias=False
          ),
      ]
      self.model = nn.Sequential(*layers)
  
imports: from collections import namedtuple
  import torch
  import torch.nn
  from torchvision import models
  from ..util import get_ckpt_path
label_desc: Use image node_id 1 to create a new NetLinLayer object from inherited base classes: nn with example: obj = NetLinLayer(chn_in, chn_out, use_dropout)