src/transformers/models/reformer/modeling_reformer.py/ReformerForMaskedLM/__init__
class ReformerForMaskedLM:    def __init__(self, config):
        super().__init__(config)
        assert not config.is_decoder, (
            "If you want to use `ReformerForMaskedLM` make sure `config.is_decoder=False` for bi-directional"
            " self-attention."
        )
        self.reformer = ReformerModel(config)
        self.lm_head = ReformerOnlyLMHead(config)

        # Initialize weights and apply final processing
        self.post_init()