src/transformers/models/groupvit/modeling_tf_groupvit.py/TFGroupViTTextMainLayer/call
class TFGroupViTTextMainLayer:    def call(
        self,
        input_ids: Optional[TFModelInputType] = None,
        attention_mask: Optional[Union[np.ndarray, tf.Tensor]] = None,
        position_ids: Optional[Union[np.ndarray, tf.Tensor]] = None,
        output_attentions: Optional[bool] = None,
        output_hidden_states: Optional[bool] = None,
        return_dict: Optional[bool] = None,
        training: bool = False,
    ) -> Union[TFBaseModelOutputWithPooling, Tuple[tf.Tensor]]:
        if input_ids is None:
            raise ValueError("You have to specify input_ids")

        input_shape = shape_list(input_ids)

        if attention_mask is None:
            attention_mask = tf.fill(dims=input_shape, value=1)

        text_model_outputs = self.text_model(
            input_ids=input_ids,
            attention_mask=attention_mask,
            position_ids=position_ids,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
            training=training,
        )

        return text_model_outputs