src/transformers/models/rembert/modeling_tf_rembert.py/TFRemBertLMPredictionHead/__init__
class TFRemBertLMPredictionHead:    def __init__(self, config: RemBertConfig, input_embeddings: tf.keras.layers.Layer, **kwargs):
        super().__init__(**kwargs)

        self.config = config
        self.initializer_range = config.initializer_range
        self.output_embedding_size = config.output_embedding_size
        self.dense = tf.keras.layers.Dense(
            config.output_embedding_size, kernel_initializer=get_initializer(self.initializer_range), name="dense"
        )
        if isinstance(config.hidden_act, str):
            self.activation = get_tf_activation(config.hidden_act)
        else:
            self.activation = config.hidden_act
        self.LayerNorm = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_eps, name="LayerNorm")