class_docstr: Optionaly seg decoder
class_docstr_tok: ["Optionaly","seg","decoder"]
code: def __init__(
      self,
      image_height,
      image_width,
      num_class,
      prior_feat_channels=64,
      refine_layers=3,
  ):
      super().__init__()
      self.dropout = nn.Dropout2D(0.1)
      self.conv = nn.Conv2D(
          prior_feat_channels * refine_layers, num_class, 1
      )
      self.image_height = image_height
      self.image_width = image_width
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.modeling.initializer import constant_
  from paddle.nn.initializer import KaimingNormal
  import paddle.nn
label_desc: Use image node_id 1 to create a new SegDecoder object from inherited base classes: nn with example: obj = SegDecoder(image_height, image_width, num_class, prior_feat_channels, refine_layers)