code: def __init__(
      self, inplanes, planes, stride=1, dilation=1, downsample=None
  ):
      super(BasicBlock, self).__init__()
      self.conv1 = conv3x3(inplanes, planes, stride=stride)
      self.bn1 = nn.BatchNorm2d(planes, affine=affine_par)
      self.relu = nn.ReLU(inplace=True)
  
      padding = dilation
      self.conv2 = conv3x3(
          planes, planes, stride=1, padding=padding, dilation=dilation
      )
      self.bn2 = nn.BatchNorm2d(planes, affine=affine_par)
      self.downsample = downsample
      self.stride = stride
  
imports: import math
  import torch
  import torch.nn
  from torch.nn.parameter import Parameter
  import torch.nn.functional
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, dilation, downsample)