code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      downsample=None,
      cardinality=1,
      base_width=64,
      reduce_first=1,
      dilation=1,
      first_dilation=None,
      act_layer=nn.ReLU,
      norm_layer=nn.BatchNorm2d,
      attn_layer=None,
      aa_layer=None,
      drop_block=None,
      drop_path=None,
  ):
      super(BasicBlock, self).__init__()
  
      assert (
          cardinality == 1
      ), "BasicBlock only supports cardinality of 1"
      assert (
          base_width == 64
      ), "BasicBlock does not support changing base width"
      first_planes = planes // reduce_first
      outplanes = planes * self.expansion
      first_dilation = first_dilation or dilation
      use_aa = aa_layer is not None and (
          stride == 2 or first_dilation != dilation
      )
  
      self.conv1 = nn.Conv2d(
          inplanes,
          first_planes,
          kernel_size=3,
          stride=1 if use_aa else stride,
          padding=first_dilation,
          dilation=first_dilation,
          bias=False,
      )
      self.bn1 = norm_layer(first_planes)
      self.drop_block = (
          drop_block() if drop_block is not None else nn.Identity()
      )
      self.act1 = act_layer(inplace=True)
      self.aa = create_aa(
          aa_layer, channels=first_planes, stride=stride, enable=use_aa
      )
  
      self.conv2 = nn.Conv2d(
          first_planes,
          outplanes,
          kernel_size=3,
          padding=dilation,
          dilation=dilation,
          bias=False,
      )
      self.bn2 = norm_layer(outplanes)
  
      self.se = create_attn(attn_layer, outplanes)
  
      self.act2 = act_layer(inplace=True)
      self.downsample = downsample
      self.stride = stride
      self.dilation = dilation
      self.drop_path = drop_path
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.models.helpers import build_model_with_cfg
  from timm.models.layers import DropBlock2d, DropPath, AvgPool2dSame, BlurPool2d, GroupNorm, create_attn, get_attn, create_classifier
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, cardinality, base_width, reduce_first, dilation, first_dilation, act_layer, norm_layer, attn_layer, aa_layer, drop_block, drop_path)