code: def __init__(self, input_dim=1024, output_dim=1024, num_layers=2):
      super().__init__()
      transformer_layer = nn.TransformerEncoderLayer(
          d_model=input_dim,
          nhead=4,
          dim_feedforward=input_dim,
          dropout=0.1,
          activation="relu",
      )
      self.transformer_encoder = nn.TransformerEncoder(
          transformer_layer, num_layers=num_layers
      )
      if input_dim != output_dim:
          self.proj = nn.Linear(input_dim, output_dim)
      else:
          self.proj = None
  
imports: from torch import nn
label_desc: Use image node_id 1 to create a new TransformerPooling object from inherited base classes: nn with example: obj = TransformerPooling(input_dim, output_dim, num_layers)