class_docstr: Fully Convolution Networks for Semantic Segmentation. This head is the implementation of
  [FCNNet](https://arxiv.org/abs/1411.4038>).
  
  Args:
      config:
          Configuration.
      in_channels (int):
          Number of input channels.
      kernel_size (int):
          The kernel size for convs in the head. Default: 3.
      dilation (int):
          The dilation rate for convs in the head. Default: 1.
code: def init_weights(self):
      self.apply(self._init_weights)
  
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 UperNetFCNHead obj's underlying member method code with example usage: obj.init_weights() without return types