code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      downsample=None,
      groups=1,
      base_width=64,
      dilation=1,
      norm_layer=None,
  ):
      super(BasicBlock, self).__init__()
      if norm_layer is None:
          norm_layer = nn.BatchNorm2D
  
      if dilation > 1:
          raise NotImplementedError(
              "Dilation > 1 not supported in BasicBlock"
          )
  
      self.conv1 = nn.Conv2D(
          inplanes, planes, 3, padding=1, stride=stride, bias_attr=False
      )
      self.bn1 = norm_layer(planes)
      self.relu = nn.ReLU()
      self.conv2 = nn.Conv2D(
          planes, planes, 3, padding=1, bias_attr=False
      )
      self.bn2 = norm_layer(planes)
      self.downsample = downsample
      self.stride = stride
  
imports: from __future__ import print_function
  import paddle
  import paddle.nn
  from paddle.utils.download import get_weights_path_from_url
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, groups, base_width, dilation, norm_layer)