code: def base_forward(self, x):
      # print("in BaseNet.base_forward(), input_size: ", x.size())
      x = self.pretrained.conv1(x)
      x = self.pretrained.bn1(x)
      x = self.pretrained.relu(x)
      x = self.pretrained.maxpool(x)
      c1 = self.pretrained.layer1(x)
      c2 = self.pretrained.layer2(c1)
      c3 = self.pretrained.layer3(c2)
      c4 = self.pretrained.layer4(c3)
      return c1, c2, c3, c4
  
file_path: pywick/pywick/models/segmentation/testnets/tkcnet/base.py
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from .resnet import *
label_desc: Use image node_id 2 for calling the BaseNet obj's underlying member method code with example usage: obj.base_forward(x) and returns: c1,  c2,  c3,  c4