src/transformers/models/regnet/modeling_tf_regnet.py/TFRegNetModel/call
class TFRegNetModel:    def call(
        self,
        pixel_values: tf.Tensor,
        output_hidden_states: Optional[bool] = None,
        return_dict: Optional[bool] = None,
        training=False,
    ) -> Union[TFBaseModelOutputWithPoolingAndNoAttention, Tuple[tf.Tensor]]:
        output_hidden_states = (
            output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
        )
        return_dict = return_dict if return_dict is not None else self.config.use_return_dict

        outputs = self.regnet(
            pixel_values=pixel_values,
            output_hidden_states=output_hidden_states,
            return_dict=return_dict,
            training=training,
        )
        if not return_dict:
            return (outputs[0],) + outputs[1:]

        return TFBaseModelOutputWithPoolingAndNoAttention(
            last_hidden_state=outputs.last_hidden_state,
            pooler_output=outputs.pooler_output,
            hidden_states=outputs.hidden_states,
        )