class_docstr: The linear head of Segmenter.
  Args:
      num_classes (int): The unique number of target classes.
      in_dim (int): The embed dim of input.
code: def __init__(self, num_classes, in_dim):
      super().__init__()
      self.head = nn.Linear(in_dim, num_classes)
      self.apply(transformer_utils.init_weights)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  from paddleseg.utils import utils
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models.backbones import vision_transformer, transformer_utils
label_desc: Use image node_id 1 to create a new SegmenterLinearHead object from inherited base classes: nn with example: obj = SegmenterLinearHead(num_classes, in_dim)