src/transformers/models/flaubert/modeling_tf_flaubert.py/TFFlaubertPredLayer/__init__
class TFFlaubertPredLayer:    def __init__(self, config, input_embeddings, **kwargs):
        super().__init__(**kwargs)

        self.asm = config.asm
        self.n_words = config.n_words
        self.pad_index = config.pad_index

        if config.asm is False:
            self.input_embeddings = input_embeddings
        else:
            raise NotImplementedError
            # self.proj = nn.AdaptiveLogSoftmaxWithLoss(
            #     in_features=dim,
            #     n_classes=config.n_words,
            #     cutoffs=config.asm_cutoffs,
            #     div_value=config.asm_div_value,
            #     head_bias=True,  # default is False
            # )