code: def __init__(self, dim_model, rnn_layers=2):
      super().__init__()
  
      self.dim_model = dim_model
  
      self.rnn = nn.LSTM(
          input_size=dim_model,
          hidden_size=dim_model,
          num_layers=rnn_layers,
          time_major=False,
      )
  
      self.mixer = nn.Sequential(
          nn.Conv2D(
              dim_model, dim_model, kernel_size=3, stride=1, padding=1
          ),
          nn.ReLU(),
          nn.Conv2D(
              dim_model, dim_model, kernel_size=3, stride=1, padding=1
          ),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import ParamAttr
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new PositionAwareLayer object from inherited base classes: nn with example: obj = PositionAwareLayer(dim_model, rnn_layers)