src/transformers/models/roc_bert/modeling_roc_bert.py/RoCBertLMPredictionHead/__init__
class RoCBertLMPredictionHead:    def __init__(self, config):
        super().__init__()
        self.transform = RoCBertPredictionHeadTransform(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