original_docstring: 
      Tensorflow wrapper for "serialize_example" to be used with the tf.data interface.
  
      :param example: An example consists of a file path (str) and optionally a label (str).
      :type example: tensorflow.Tensor
      :param data_preprocessing_function: Function to be applied on the first column of each example (file path), which
          is supposed to load the example data and perform any additional preprocessing. It must return the data
          in any of the supported formats for serialization (bytes or list of numbers), along with the
          data type (after loading and preprocessing) and the original data shape (after loading and preprocessing but
          before flattening). It will also return an example ID, used to identify the example (for instance, the original
          file name). This ID is not used internally but it is useful for further usages of the dataset.
          Optional, default: npy_data_preprocessor (see above).
      :type data_preprocessing_function: (str) -> tuple[Union[bytes, list[float], list[int]], type, tuple[int], str]
      :param label_type: Type of the label, usually an integer. If there is no label, it is ignored.
          Optional, default: int
      :type label_type: type
      :raises ValueError: If the label type conversion is not possible.
      :raises OSError: If there is a problem reading the example data from the file path.
  
      :return: A binary string representation of the example.
      :rtype: tensorflow.Tensor
      
docstring: Tensorflow wrapper for "serialize_example" to be used with the tf.data interface.
docstring_tokens: Tensorflow wrapper for " serialize_example " to be used with the tf . data interface .
code: def _tf_serialize_example(
          example,
          data_preprocessing_function=npy_data_preprocessor,
          label_type=int):
      """
      Tensorflow wrapper for "serialize_example" to be used with the tf.data interface.
  
      :param example: An example consists of a file path (str) and optionally a label (str).
      :type example: tensorflow.Tensor
      :param data_preprocessing_function: Function to be applied on the first column of each example (file path), which
          is supposed to load the example data and perform any additional preprocessing. It must return the data
          in any of the supported formats for serialization (bytes or list of numbers), along with the
          data type (after loading and preprocessing) and the original data shape (after loading and preprocessing but
          before flattening). It will also return an example ID, used to identify the example (for instance, the original
          file name). This ID is not used internally but it is useful for further usages of the dataset.
          Optional, default: npy_data_preprocessor (see above).
      :type data_preprocessing_function: (str) -> tuple[Union[bytes, list[float], list[int]], type, tuple[int], str]
      :param label_type: Type of the label, usually an integer. If there is no label, it is ignored.
          Optional, default: int
      :type label_type: type
      :raises ValueError: If the label type conversion is not possible.
      :raises OSError: If there is a problem reading the example data from the file path.
  
      :return: A binary string representation of the example.
      :rtype: tensorflow.Tensor
      """
      tf_string = tf.py_function(
          lambda ex: _serialize_example(ex, data_preprocessing_function, label_type),
          (example,),
          tf.string
      )
      return tf.reshape(tf_string, ())
code_tokens: def _tf_serialize_example ( example , data_preprocessing_function = npy_data_preprocessor , label_type = int ) : tf_string = tf . py_function ( lambda ex : _serialize_example ( ex , data_preprocessing_function , label_type ) , ( example , ) , tf . string ) return tf . reshape ( tf_string , ( ) )
short_docstring: Tensorflow wrapper for "serialize_example" to be used with the tf.data interface.
short_docstring_tokens: Tensorflow wrapper for " serialize_example " to be used with the tf . data interface .
comment: """
      Tensorflow wrapper for "serialize_example" to be used with the tf.data interface.
  
      :param example: An example consists of a file path (str) and optionally a label (str).
      :type example: tensorflow.Tensor
      :param data_preprocessing_function: Function to be applied on the first column of each example (file path), which
          is supposed to load the example data and perform any additional preprocessing. It must return the data
          in any of the supported formats for serialization (bytes or list of numbers), along with the
          data type (after loading and preprocessing) and the original data shape (after loading and preprocessing but
          before flattening). It will also return an example ID, used to identify the example (for instance, the original
          file name). This ID is not used internally but it is useful for further usages of the dataset.
          Optional, default: npy_data_preprocessor (see above).
      :type data_preprocessing_function: (str) -> tuple[Union[bytes, list[float], list[int]], type, tuple[int], str]
      :param label_type: Type of the label, usually an integer. If there is no label, it is ignored.
          Optional, default: int
      :type label_type: type
      :raises ValueError: If the label type conversion is not possible.
      :raises OSError: If there is a problem reading the example data from the file path.
  
      :return: A binary string representation of the example.
      :rtype: tensorflow.Tensor
      """