class_docstr: A wrapper around `Transformer` turning it into an Encoder by setting the following:
      - is_decoder=False
      - seq_length=0
      - encoder_output=None
class_docstr_tok: ["A","wrapper","around","`","Transformer","`","turning","it","into","an","Encoder","by","setting","the","following",":","-","is_decoder=False","-","seq_length=0","-","encoder_output=None"]
code: def forward(self, input: Tensor) -> Tensor:
      return super().forward(input, encoder_output=None)
  
imports: from functools import partial
  from typing import Callable, Optional
  import torch
  import torch.nn
  from torch import Tensor
  from .layers_utils import MLP, StochasticDepth, WindowMultiHeadAttention
label_desc: Use image node_id 2 for calling the EncoderSection obj's underlying member method code with example usage: obj.forward(input) and returns: super