code: def __init__(self):
      super(FeatureEnhancer, self).__init__()
  
      self.multihead = MultiHeadedAttention(
          h=4, d_model=128, dropout=0.1
      )
      self.mul_layernorm1 = LayerNorm(features=128)
  
      self.pff = PositionwiseFeedForward(128, 128)
      self.mul_layernorm3 = LayerNorm(features=128)
  
      self.linear = nn.Linear(128, 64)
  
imports: import math
  import warnings
  import numpy
  import paddle
  from paddle import nn
  import string
  from .tps_spatial_transformer import TPSSpatialTransformer
  from .stn import STN
  from .tsrn import GruBlock, mish, UpsampleBLock
  from ppocr.modeling.heads.sr_rensnet_transformer import Transformer, LayerNorm, PositionwiseFeedForward, MultiHeadedAttention
label_desc: Use image node_id 1 to create a new FeatureEnhancer object from inherited base classes: nn with example: obj = FeatureEnhancer()