src/transformers/models/vit_mae/modeling_tf_vit_mae.py/TFViTMAEAttention/call
class TFViTMAEAttention:    def call(
        self,
        input_tensor: tf.Tensor,
        head_mask: tf.Tensor,
        output_attentions: bool,
        training: bool = False,
    ) -> Tuple[tf.Tensor]:
        self_outputs = self.self_attention(
            hidden_states=input_tensor, head_mask=head_mask, output_attentions=output_attentions, training=training
        )
        attention_output = self.dense_output(
            hidden_states=self_outputs[0], input_tensor=input_tensor, training=training
        )
        outputs = (attention_output,) + self_outputs[1:]  # add attentions if we output them

        return outputs