src/transformers/models/vit_mae/modeling_tf_vit_mae.py/TFViTMAEEmbeddings/call
class TFViTMAEEmbeddings:    def call(self, pixel_values: tf.Tensor, noise: tf.Tensor = None) -> tf.Tensor:
        embeddings = self.patch_embeddings(pixel_values)

        # add position embeddings w/o cls token
        embeddings = embeddings + self.position_embeddings[:, 1:, :]

        # masking: length -> length * config.mask_ratio
        embeddings, mask, ids_restore = self.random_masking(embeddings, noise)

        # append cls token
        cls_token = self.cls_token + self.position_embeddings[:, :1, :]
        cls_tokens = tf.tile(cls_token, (shape_list(embeddings)[0], 1, 1))
        embeddings = tf.concat([cls_tokens, embeddings], axis=1)

        return embeddings, mask, ids_restore