code: def __init__(self, in_channels, out_channels, kernel_size, stride=1):
      super(ReluConvBn, self).__init__()
      self.relu = nn.ReLU()
      self.conv = nn.Conv2d(
          in_channels,
          out_channels,
          kernel_size=kernel_size,
          stride=stride,
          bias=False,
      )
      self.bn = nn.BatchNorm2d(out_channels, eps=0.001)
  
imports: from collections import OrderedDict
  import torch
  import torch.nn
  import torch.utils.model_zoo
label_desc: Use image node_id 1 to create a new ReluConvBn object from inherited base classes: nn with example: obj = ReluConvBn(in_channels, out_channels, kernel_size, stride)