code: def __init__(
      self, input_shape, num_classes, transformer_in_feature="res5"
  ):
      super(MaskFormerHead, self).__init__()
      self.transformer_in_feature = transformer_in_feature
      self.input_shape = input_shape
      self.pixel_decoder = BasePixelDecoder(input_shape)
      self.predictor = TransformerPredictor(
          input_shape[transformer_in_feature]["channels"],
          mask_classification=True,
          num_classes=num_classes,
      )
  
imports: import math
  import copy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from paddleseg.core.train import check_logits_losses
label_desc: Use image node_id 1 to create a new MaskFormerHead object from inherited base classes: nn with example: obj = MaskFormerHead(input_shape, num_classes, transformer_in_feature)