code: def conv(kernel, planes):
      if kernel == 3:
          _conv = conv3x3
      elif kernel == 5:
          _conv = conv5x5
      else:
          raise NotImplemented(f"Unkown kernel size: {kernel}")
  
      return nn.Sequential(
          nn.ReLU(inplace=True),
          _conv(planes, planes),
          nn.BatchNorm2d(planes),
      )
  
file_path: ENAS-pytorch/models/shared_cnn.py
imports: import numpy
  from collections import defaultdict, deque
  import torch
  from torch import nn
  import torch.nn.functional
  from torch.autograd import Variable
  from models.shared_base import *
  from utils import get_logger, get_variable, keydefaultdict
label_desc: Use image node_id 3 for calling a global function with example usage: conv(kernel, planes) and returns: nn