ixel_values` are present):
            The output of the [`FlavaImageModel`].
        text_embeddings (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*, returned when `input_ids` are present):
            The text embeddings which are basically the pooled output of [`FlavaTextModel`].
        text_output (`BaseModelOutputWithPooling`, *optional*, returned when `input_ids` are present):
            The output of the [`FlavaTextModel`].
        multimodal_embeddings (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*, returned when `input_ids` and `pixel_values` are present and `skip_unmasked_multimodal_encoder` is `None` or `False`):
            The multimodal embeddings which are basically the pooled output of [`FlavaTextModel`].
        multimodal_output (`BaseModelOutputWithPooling`, returned when `input_ids` and `pixel_values` are present and `skip_unmasked_multimodal_encoder` is `None` or `False`):
            The output of the [`FlavaMultimodalModel`].

        image_masked_embeddings (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*, returned when `pixel_values` are present):
            The image embeddings which are basically the pooled output of [`FlavaImageModel`]. Uses `bool_masked_pos`
            to create masked images.
        image_masked_output (`BaseModelOutputWithPooling`, *optional*, returned when `pixel_values` are present):
            The output of the [`FlavaImageModel`]. Uses `bool_masked_pos` to create masked images.
        text_masked_embeddings (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*, returned when `input_ids_masked` are present):
            The text embeddings which are basically the pooled output of [`FlavaTextModel`].
        text_masked_output (`BaseModelOutputWithPooling`, *optional*, returned when `input_ids_masked` are present):
            The output of the [`FlavaTextModel`].
        multimodal_masked_embeddings (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*, returned when `input_ids` and `pixel_values` are present):
            The multimodal embeddings which are basically the pooled output of [`FlavaTextModel`].
        multimodal_masked_output (`BaseModelOutputWithPooling`, returned when `input_ids_masked` and `pixel_values` are present):
            The output of the [`FlavaMultimodalModel`].

        mim_logits (`torch.FloatTensor` of shape `(batch_size, num_image_patches, image_vocab_size)` or of shape `(total_masked_patches, image_vocab_size)` , *optional*, returned when `pixel_values` are present and `input_ids_masked` are not):
                The logits for MIM unimodal loss. Uses `book_masked_pos` to get masked patches. The flattened output is
                returned when `bool_masked_pos` has some of the patches masked.
        mlm_logits (`torch.FloatTensor` of shape `(batch_size, text_seq_length, text_vocab_size)` or of shape `(total_masked_seq_length, text_vocab_size)`, *optional*, returned when `input_ids_masked` are present and `pixel_values` are not):
                The logits for MLM unimodal loss. The flattened output is returned when `input_ids_masked` has some of
                the tokens masked.
        itm_logits (`torch.FloatTensor` of shape `(batch_size, 2)`, *optional*, returned when `input_ids_masked` and `pixel_values` are present):
                The logits for ITM loss. Note that ITM loss is calculated on masked pairs in FLAVA.
        mmm_image_logits (`torch.FloatTensor` of shape `(batch_size, num_image_patches, image_vocab_size)` or of shape`(total_masked_patches, image_vocab_size)`, *optional*, returned when `pixel_values` and `input_ids_masked` are present):
                The logits for MMM image multimodal loss. Uses `book_masked_pos` to get masked patches. The flattened
                output is returned when `bool_masked_pos` has some of the patches masked.
        mmm_text_logits (`torch.FloatTensor` of shape `(batch_size, text_seq_length, text_vocab_size)` or of shape `(`(total_masked_seq_length, text_vocab_size)`), *optional*, returned when `pixel_values` and `input_ids_masked` are present):
                The logits for MMM text multimodal loss. The flattened output is returned when `input_ids_masked` has
                some of the tokens masked.
        contrastive_logits_per_image (`torch.FloatTensor` of shape `(image_batch_size, text_batch_size)`):
            The scaled dot product scores between `image_embeddings` and `text_embeddings` but passed through FLAVA's
            `image_projection` and `text_projection` layers respectively. This represents the image-text similarity
            scores. This is calculated on unmasked images and texts.
        contrastive_logits_per_text (`torch.FloatTensor` of shape `(text_batch_size, image_batch_size)`):
            The scaled dot product scores between `text_embeddings` and `image_embeddings` but passed through FLAVA's
            `text_projection` and `image_projection` layers respectively. This is calculated on unmasked images and
            texts.
    N