src/transformers/models/reformer/modeling_reformer.py/ReformerOnlyLMHead/__init__
class ReformerOnlyLMHead:    def __init__(self, config):
        super().__init__()
        # Reformer is using Rev Nets, thus last layer outputs are concatenated and
        # Layer Norm is done over 2 * hidden_size
        self.seq_len_dim = 1
        self.chunk_size_lm_head = config.chunk_size_lm_head
        self.decoder = nn.Linear(2 * config.hidden_size, config.vocab_size, bias=False)
        self.bias = nn.Parameter(torch.zeros(config.vocab_size))
        self.decoder.bias = self.bias