code: def _stack_normal_conv(
      in_ch,
      out_ch,
      kernel_size,
      skip,
      dconv,
      stride,
      repeats,
      bn_momentum,
  ):
      assert repeats >= 1
      stack = []
      for i in range(repeats):
          s = stride if i == 0 else 1
          if dconv:
              modules = [
                  nn.Conv2d(
                      in_ch,
                      in_ch,
                      kernel_size,
                      padding=kernel_size // 2,
                      stride=s,
                      groups=in_ch,
                      bias=False,
                  ),
                  nn.BatchNorm2d(in_ch, momentum=bn_momentum),
                  nn.ReLU(inplace=True),
                  nn.Conv2d(
                      in_ch, out_ch, 1, padding=0, stride=1, bias=False
                  ),
                  nn.BatchNorm2d(out_ch, momentum=bn_momentum),
              ]
          else:
              modules = [
                  nn.Conv2d(
                      in_ch,
                      out_ch,
                      kernel_size,
                      padding=kernel_size // 2,
                      stride=s,
                      bias=False,
                  ),
                  nn.ReLU(inplace=True),
                  nn.BatchNorm2d(out_ch, momentum=bn_momentum),
              ]
          if skip and in_ch == out_ch and s == 1:
              # use different implementation for skip and noskip to align with pytorch
              stack.append(_ResidualBlock(nn.Sequential(*modules)))
          else:
              stack += modules
          in_ch = out_ch
      return stack
  
imports: from nni.retiarii import basic_unit
  import nni.retiarii.nn.pytorch
  import warnings
  import torch
  import torch.nn
  import torch.nn.functional
  from nni.retiarii import model_wrapper
  import sys
  from pathlib import Path
label_desc: Use image node_id 2 for calling a global function with example usage: _stack_normal_conv(in_ch, out_ch, kernel_size, skip, dconv, stride, repeats, bn_momentum) and returns: stack