code: def __init__(
      self,
      in_channels,
      out_channels,
      stride=1,
      downsample=None,
      no_relu=False,
  ):
      super().__init__()
      self.conv1 = conv2d(in_channels, out_channels, 3, stride, 1)
      self.bn1 = bn2d(out_channels)
      self.relu = nn.ReLU()
      self.conv2 = conv2d(out_channels, out_channels, 3, 1, 1)
      self.bn2 = bn2d(out_channels)
      self.downsample = downsample
      self.stride = stride
      self.no_relu = no_relu
  
imports: from functools import partial
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
  from paddleseg.models.backbones.transformer_utils import DropPath, Identity
  from paddleseg.cvlibs.param_init import constant_init, kaiming_normal_init, trunc_normal_init
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: nn with example: obj = BasicBlock(in_channels, out_channels, stride, downsample, no_relu)