code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      downsample=None,
      dilation=(1, 1),
      residual=True,
  ):
      super(BasicBlock, self).__init__()
      self.conv1 = conv3x3(
          inplanes,
          planes,
          stride,
          padding=dilation[0],
          dilation=dilation[0],
      )
      self.bn1 = BatchNorm(planes)
      self.relu = nn.ReLU(inplace=True)
      self.conv2 = conv3x3(
          planes, planes, padding=dilation[1], dilation=dilation[1]
      )
      self.bn2 = BatchNorm(planes)
      self.downsample = downsample
      self.stride = stride
      self.residual = residual
  
imports: import numpy
  import torch
  from torch.autograd import Variable
  from pytorch2keras.converter import pytorch_to_keras
  import torch.nn
  import math
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, dilation, residual)