code: def __init__(self, in_channels, hidden_size):
      super(EncoderWithFC, self).__init__()
      self.out_channels = hidden_size
      weight_attr, bias_attr = get_para_bias_attr(
          l2_decay=0.00001, k=in_channels
      )
      self.fc = nn.Linear(
          in_channels,
          hidden_size,
          weight_attr=weight_attr,
          bias_attr=bias_attr,
          name="reduce_encoder_fea",
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle import nn
  from ppocr.modeling.heads.rec_ctc_head import get_para_bias_attr
  from ppocr.modeling.backbones.rec_svtrnet import Block, ConvBNLayer, trunc_normal_, zeros_, ones_
label_desc: Use image node_id 1 to create a new EncoderWithFC object from inherited base classes: nn with example: obj = EncoderWithFC(in_channels, hidden_size)