code: def _make_layer(self, block, planes, blocks, stride, reduction):
      strides = [stride] + [1] * (blocks - 1)
      layers = []
      for stride in strides:
          layers.append(block(self.inplane, planes, stride, reduction))
          self.inplane = planes
  
      return nn.Sequential(*layers)
  
imports: import numpy
  import torch
  from torch import nn
  from torch.autograd import Variable
  from torchvision.models import ResNet
  from pytorch2keras.converter import pytorch_to_keras
label_desc: Use image node_id 3 for calling the CifarSEResNet obj's underlying member method code with example usage: obj._make_layer(block, planes, blocks, stride, reduction) and returns: nn