code: def __init__(
      self, inplanes, planes, stride=1, downsample=None, dcn=None
  ):
      super(BasicBlock, self).__init__()
      self.with_dcn = dcn is not None
      self.conv1 = conv3x3(inplanes, planes, stride)
      self.bn1 = BatchNorm2d(planes, momentum=0.1)
      self.relu = nn.ReLU()
      self.with_modulated_dcn = False
      if not self.with_dcn:
          self.conv2 = nn.Conv2D(
              planes, planes, kernel_size=3, padding=1, bias_attr=False
          )
      else:
          from paddle.version.ops import DeformConv2D
  
          deformable_groups = dcn.get("deformable_groups", 1)
          offset_channels = 18
          self.conv2_offset = nn.Conv2D(
              planes,
              deformable_groups * offset_channels,
              kernel_size=3,
              padding=1,
          )
          self.conv2 = DeformConv2D(
              planes, planes, kernel_size=3, padding=1, bias_attr=False
          )
      self.bn2 = BatchNorm2d(planes, momentum=0.1)
      self.downsample = downsample
      self.stride = stride
  
imports: import math
  import paddle
  from paddle import nn
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, dcn)