src/transformers/models/mpnet/modeling_tf_mpnet.py/TFMPNetModel/call
class TFMPNetModel:    def call(
        self,
        input_ids: Optional[TFModelInputType] = None,
        attention_mask: Optional[Union[np.array, tf.Tensor]] = None,
        position_ids: Optional[Union[np.array, tf.Tensor]] = None,
        head_mask: Optional[Union[np.array, tf.Tensor]] = None,
        inputs_embeds: Optional[tf.Tensor] = None,
        output_attentions: Optional[bool] = None,
        output_hidden_states: Optional[bool] = None,
        return_dict: Optional[bool] = None,
        training: bool = False,
    ) -> Union[TFBaseModelOutput, Tuple[tf.Tensor]]:
        outputs = self.mpnet(
            input_ids=input_ids,
            attention_mask=attention_mask,
            position_ids=position_ids,
            head_mask=head_mask,
            inputs_embeds=inputs_embeds,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
            training=training,
        )
        return outputs