src/transformers/models/mobilebert/modeling_mobilebert.py/MobileBertLMPredictionHead/__init__
class MobileBertLMPredictionHead:    def __init__(self, config):
        super().__init__()
        self.transform = MobileBertPredictionHeadTransform(config)
        # The output weights are the same as the input embeddings, but there is
        # an output-only bias for each token.
        self.dense = nn.Linear(config.vocab_size, config.hidden_size - config.embedding_size, bias=False)
        self.decoder = nn.Linear(config.embedding_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