code: def forward(self, x):
      mask_features, transformer_encoder_features = self.pixel_decoder(
          x
      )
      predictions = self.predictor(
          x[self.transformer_in_feature], mask_features
      )
  
      return predictions
  
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 2 for calling the MaskFormerHead obj's underlying member method code with example usage: obj.forward(x) and returns: predictions