code: def decoder_layer(
      in_c,
      out_c,
      k=3,
      s=1,
      p=1,
      mode="nearest",
      scale_factor=None,
      size=None,
  ):
      align_corners = False if mode == "nearest" else True
      return nn.Sequential(
          nn.Upsample(
              size=size,
              scale_factor=scale_factor,
              mode=mode,
              align_corners=align_corners,
          ),
          nn.Conv2D(in_c, out_c, k, s, p),
          nn.BatchNorm2D(out_c),
          nn.ReLU(),
      )
  
imports: import math
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from paddle.nn import LayerList
  from ppocr.modeling.heads.rec_nrtr_head import TransformerBlock, PositionalEncoding
label_desc: Use image node_id 2 for calling a global function with example usage: decoder_layer(in_c, out_c, k, s, p, mode, scale_factor, size) and returns: nn