hat are **masked**.

                [What are attention masks?](../glossary#attention-mask)
            context_input_ids (`tf.Tensor` of shape `(batch_size * config.n_docs, config.max_combined_length)`, *optional*, returned when *output_retrieved=True*):
                Input IDs post-processed from the retrieved documents and the question encoder `input_ids` by the
                retriever.

                If the model has is not initialized with a `retriever`, `context_input_ids` has to be provided to the
                forward pass. `context_input_ids` are returned by [`~RagRetriever.__call__`].
            context_attention_mask (`tf.Tensor` of shape `(batch_size * config.n_docs, config.max_combined_length)`, *optional*, returned when *output_retrieved=True*):
                Attention mask post-processed from the retrieved documents and the question encoder `input_ids` by the
                retriever.

                If the model has is not initialized with a `retriever`, `context_input_ids` has to be provided to the
                forward pass. `context_input_ids` are returned by [`~RagRetriever.__call__`].
            doc_scores (`tf.Tensor` of shape `(batch_size, config.n_docs)`):
                Score between each retrieved document embeddings (see `retrieved_doc_embeds`) and
                `question_encoder_last_hidden_state`.

                If the model has is not initialized with a `retriever`, `context_input_ids` has to be provided to the
                forward pass. `context_input_ids` are returned by [`~RagRetriever.__call__`].
            n_docs (`int`, *optional*, defaults to `config.n_docs`)
                Number of documents to retrieve and/or number of documents for which to generate an answer.
            generation_config (`~generation.GenerationConfig`, *optional*):
                The generation configuration to be used as base parametrization for the generation call. `**kwargs`
                passed to generate matching the attributes of `generation_config` will override them. If
                `generation_config` is not provided, the default will be used, which had the following loading
                priority: 1) from the `generation_config.json` model file, if it exists; 2) from the model
                configuration. Please note that unspecified parameters will inherit [`~generation.GenerationConfig`]'s
                default values, whose documentation should be checked to parameterize generation.
            logits_processor (`TFLogitsProcessorList`, *optional*):
                Custom logits processors that complement the default logits processors built from arguments and a
                model's config. If a logit processor is passed that is already created with the arguments or a model's
                config an error is thrown.
            kwargs (`Dict[str, Any]`, *optional*):
                Ad hoc parametrization of `generate_config` and/or additional model-specific kwargs that will be
                forwarded to the `forward` function of the model.

        Return:
            `tf.Tensor` of shape `(batch_size * num_return_sequences, sequence_length)`: The generated sequences. The
            second dimension (sequence_length) is either equal to `max_length` or shorter if all batches finished early
            due to the `eos_token_id`.
        NŠ