src/transformers/models/fnet/modeling_fnet.py/FNetLMPredictionHead/__init__
class FNetLMPredictionHead:    def __init__(self, config):
        super().__init__()
        self.transform = FNetPredictionHeadTransform(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)

        self.bias = nn.Parameter(torch.zeros(config.vocab_size))
        self.decoder.bias = self.bias