def call(
        self,
        pixel_values: tf.Tensor | None = None,
        output_hidden_states: Optional[bool] = None,
        return_dict: Optional[bool] = None,
        training: Optional[bool] = False,
    ) -> Union[TFBaseModelOutputWithCLSToken, Tuple[tf.Tensor]]:
        r"""
        Returns:

        Examples:

        ```python
        >>> from transformers import AutoImageProcessor, TFCvtModel
        >>> from PIL import Image
        >>> import requests

        >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
        >>> image = Image.open(requests.get(url, stream=True).raw)

        >>> image_processor = AutoImageProcessor.from_pretrained("microsoft/cvt-13")
        >>> model = TFCvtModel.from_pretrained("microsoft/cvt-13")

        >>> inputs = image_processor(images=image, return_tensors="tf")
        >>> outputs = model(**inputs)
        >>> last_hidden_states = outputs.last_hidden_state
        ```"""

        if pixel_values is None:
            raise ValueError("You have to specify pixel_values")

        outputs = self.cvt(
            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 TFBaseModelOutputWithCLSToken(
            last_hidden_state=outputs.last_hidden_state,
            cls_token_value=outputs.cls_token_value,
            hidden_states=outputs.hidden_states,
        )

        Returns:

        Examples:

        ```python
        >>> from transformers import AutoImageProcessor, TFCvtModel
        >>> from PIL import Image
        >>> import requests

        >>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
        >>> image = Image.open(requests.get(url, stream=True).raw)

        >>> image_processor = AutoImageProcessor.from_pretrained("microsoft/cvt-13")
        >>> model = TFCvtModel.from_pretrained("microsoft/cvt-13")

        >>> inputs = image_processor(images=image, return_tensors="tf")
        >>> outputs = model(**inputs)
        >>> last_hidden_states = outputs.last_hidden_state
        ```
dpkd/transformers/src/transformers/models/cvt/modeling_tf_cvt.py