src/transformers/models/tapas/modeling_tf_tapas.py/TFTapasForQuestionAnswering/__init__
class TFTapasForQuestionAnswering:    def __init__(self, config: TapasConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

        # base model
        self.tapas = TFTapasMainLayer(config, name="tapas")

        # dropout
        self.dropout = tf.keras.layers.Dropout(config.hidden_dropout_prob)

        self.compute_token_logits = TFTapasComputeTokenLogits(config, name="compute_token_logits")

        self.compute_column_logits = TFTapasComputeColumnLogits(config, name="compute_column_logits")

        if config.num_aggregation_labels > 0:
            self.aggregation_classifier = tf.keras.layers.Dense(
                config.num_aggregation_labels,
                kernel_initializer=get_initializer(config.initializer_range),
                name="aggregation_classifier",
            )
        self.config = config