code: def __init__(self, config):
      super().__init__()
      self.transform = BertPredictionHeadTransform(config)
      # The output weights are the same as the input embeddings, but there is
      # an output-only bias for each token.
      self.decoder = nn.Linear(
          config.hidden_size, config.vocab_size, bias=False
      )
  
      self.bias = nn.Parameter(torch.zeros(config.vocab_size))
  
      # Need a link between the two variables so that the bias is correctly
      # resized with `resize_token_embeddings`
      self.decoder.bias = self.bias
  
imports: import torch
  from torch import nn
  from ..modules import VideoTokenMLP, MMBertEmbeddings
label_desc: Use image node_id 1 to create a new BertMFMMLMPredictionHead object from inherited base classes: nn with example: obj = BertMFMMLMPredictionHead(config)