er.
            query_position_embeddings (`torch.FloatTensor` of shape `(num_queries, batch_size, hidden_size)`):
                , *optional*): Position embeddings that are added to the queries and keys in each self-attention layer.
            encoder_hidden_states (`torch.FloatTensor` of shape `(batch_size, encoder_sequence_length, hidden_size)`):
                Sequence of hidden-states at the output of the last layer of the encoder. Used in the
                cross(masked)-attention of the decoder.
            feature_size_list (`List[torch.Size]` ):
                This is a list containing shapes (height & width) of multi-scale features from the Pixel Decoder.
            output_attentions (`bool`, *optional*):
                Whether or not to return the attentions tensors of all attention layers. See `attentions` under
                returned tensors for more detail.
            output_hidden_states (`bool`, *optional*):
                Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors
                for more detail.
            return_dict (`bool`, *optional*):
                Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
        Nr$