code: def __init__(
      self, in_channels, out_channels, kernel_size=3, deform_groups=4
  ):
      super(FeatureAlign, self).__init__()
      offset_channels = kernel_size * kernel_size * 2
      self.conv_offset = nn.Conv2d(
          4, deform_groups * offset_channels, 1, bias=False
      )
      self.conv_adaption = DeformConv2d(
          in_channels,
          out_channels,
          kernel_size=kernel_size,
          padding=(kernel_size - 1) // 2,
          deform_groups=deform_groups,
      )
      self.relu = nn.ReLU(inplace=True)
  
imports: import torch
  import torch.nn
  from mmcv.cnn import ConvModule, normal_init
  from mmcv.ops import DeformConv2d
  from mmdet.core import multi_apply, multiclass_nms
  from ..builder import HEADS
  from .anchor_free_head import AnchorFreeHead
label_desc: Use image node_id 1 to create a new FeatureAlign object from inherited base classes: nn with example: obj = FeatureAlign(in_channels, out_channels, kernel_size, deform_groups)