code: def forward(self, input: torch.Tensor) -> torch.Tensor:
      hidden_state = input
      for layer in self.layers:
          hidden_state = layer(hidden_state)
      return hidden_state
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from ...None import AutoBackbone
  from ...modeling_outputs import SemanticSegmenterOutput
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from .configuration_upernet import UperNetConfig
label_desc: Use image node_id 2 for calling the UperNetPyramidPoolingBlock obj's underlying member method code with example usage: obj.forward(input) and returns: hidden_state