class_docstr: Class for training a Masked Language Model. It also supports an
  additional sentence level prediction if the sent-loss argument is set.
class_docstr_tok: ["Class","for","training","a","Masked","Language","Model",".","It","also","supports","an","additional","sentence","level","prediction","if","the","sent-loss","argument","is","set","."]
code: def forward(self, src_tokens, segment_labels=None, **kwargs):
      return self.encoder(
          src_tokens, segment_labels=segment_labels, **kwargs
      )
  
imports: import logging
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderModel, register_model, register_model_architecture
  from fairseq.modules import LayerNorm, SinusoidalPositionalEmbedding, TransformerSentenceEncoder
  from fairseq.modules.transformer_sentence_encoder import init_bert_params
  from fairseq.utils import safe_hasattr
label_desc: Use image node_id 3 for calling the MaskedLMModel obj's underlying member method code with example usage: obj.forward(src_tokens, segment_labels) and returns: self