src/transformers/models/big_bird/modeling_flax_big_bird.py/FlaxBigBirdForQuestionAnsweringModule/__call__
class FlaxBigBirdForQuestionAnsweringModule:    def __call__(
        self,
        input_ids,
        attention_mask,
        token_type_ids,
        position_ids,
        head_mask,
        logits_mask=None,
        deterministic: bool = True,
        output_attentions: bool = False,
        output_hidden_states: bool = False,
        return_dict: bool = True,
    ):
        # Model
        outputs = self.bert(
            input_ids,
            attention_mask,
            token_type_ids,
            position_ids,
            head_mask,
            deterministic=deterministic,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
        )

        hidden_states = outputs[0]
        pooled_output = outputs[1] if self.add_pooling_layer else None
        logits = self.qa_classifier(hidden_states, deterministic=deterministic)

        if logits_mask is not None:
            # removing question tokens from the competition
            logits = logits - logits_mask * 1e6

        start_logits, end_logits = logits.split(self.config.num_labels, axis=-1)
        start_logits = start_logits.squeeze(-1)
        end_logits = end_logits.squeeze(-1)

        if not return_dict:
            return (start_logits, end_logits) + outputs[1:]

        return FlaxBigBirdForQuestionAnsweringModelOutput(
            start_logits=start_logits,
            end_logits=end_logits,
            pooled_output=pooled_output,
            hidden_states=outputs.hidden_states,
            attentions=outputs.attentions,
        )