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,
          batch_first=True,
      )
  
      self.mixer = nn.Sequential(
          nn.Conv2d(
              dim_model, dim_model, kernel_size=3, stride=1, padding=1
          ),
          nn.ReLU(True),
          nn.Conv2d(
              dim_model, dim_model, kernel_size=3, stride=1, padding=1
          ),
      )
  
imports: import torch.nn
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)