code: def __init__(self, in_channels, channels, stride=1, downsample=None):
      super().__init__()
      self.conv1 = conv1x1(in_channels, channels)
      self.bn1 = nn.BatchNorm2D(channels)
      self.relu = nn.ReLU()
      self.conv2 = conv3x3(channels, channels, stride)
      self.bn2 = nn.BatchNorm2D(channels)
      self.downsample = downsample
      self.stride = stride
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle import ParamAttr
  from paddle.nn.initializer import KaimingNormal
  import paddle.nn
  import paddle.nn.functional
  import numpy
  import math
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: nn with example: obj = BasicBlock(in_channels, channels, stride, downsample)