class_docstr: Feature extraction in Mask head
  
  Args:
      in_channel (int): Input channels
      out_channel (int): Output channels
      num_convs (int): The number of conv layers, default 4
      norm_type (string | None): Norm type, bn, gn, sync_bn are available,
          default None
class_docstr_tok: ["Feature","extraction","in","Mask","head","Args",":","in_channel","(","int",")",":","Input","channels","out_channel","(","int",")",":","Output","channels","num_convs","(","int",")",":","The","number","of","conv","layers",",","default","4","norm_type","(","string","|","None",")",":","Norm","type",",","bn",",","gn",",","sync_bn","are","available",",","default","None"]
code: def forward(self, feats):
      return self.upsample(feats)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import KaimingNormal
  from ppdet.core.workspace import register, create
  from ppdet.modeling.layers import ConvNormLayer
  from .roi_extractor import RoIAlign
  from ..cls_utils import _get_class_default_kwargs
label_desc: Use image node_id 4 for calling the MaskFeat obj's underlying member method code with example usage: obj.forward(feats) and returns: self