code: def __init__(self, inplanes, planes, stride=1, downsample=None):
      super(BasicBlock, self).__init__()
      self.conv1 = conv3x3(inplanes, planes, stride)
      self.bn1 = N2d(planes)
      self.relu = nn.ReLU(inplace=True)
      self.conv2 = conv3x3(planes, planes)
      self.bn2 = N2d(planes)
      self.downsample = downsample
      self.stride = stride
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
          elif isinstance(m, nn.BatchNorm2d):
              nn.init.constant_(m.weight, 1)
              nn.init.constant_(m.bias, 0)
  
imports: import torch.nn
  import math
  import torch.utils.model_zoo
  from .mynn import Norm2d
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: nn with example: obj = BasicBlock(inplanes, planes, stride, downsample)