original_docstring: 
      Loads a tensorflow dataset from a list of `*.tfrecord` files with serialized examples.
      This function is the counterpart for write_dataset_to_file() (see above) and its only valid for TFRecords that
      follow the serialization format of that function (two fixed length features, 'data' (with shape = data_shape)
      and 'label' (scalar value)).
  
      :param file_paths: List of paths to the `*.tfrecord` files that contain the serialized examples.
      :type file_paths: list[str]
      :param data_shape: Original shape of the example data. Since they are serialized, this metadata is needed
          to reconstruct the tensor.
      :type data_shape: tuple[int]
      :param data_type: Type of each data point in the example or the example itself if it is bytes or str, before
          serialization. It is needed to parse the example. Optional, default: np.float32
      :type data_type: type
      :param label_type: Type of the label (if any). If there is no label, this must be specified by setting this
          parameter to None. Optional, default: int.
      :type label_type: type
      :return: Tensorflow dataset of parsed examples (as tuples of tensors with example data and optionally a label).
      :rtype: tf.data.Dataset
      
docstring: Loads a tensorflow dataset from a list of `*.tfrecord` files with serialized examples.
  This function is the counterpart for write_dataset_to_file()  and its only valid for TFRecords that
  follow the serialization format of that function (two fixed length features, 'data' (with shape = data_shape)
  and 'label' (scalar value)).
docstring_tokens: Loads a tensorflow dataset from a list of ` * . tfrecord ` files with serialized examples . This function is the counterpart for write_dataset_to_file () and its only valid for TFRecords that follow the serialization format of that function ( two fixed length features ' data ' ( with shape = data_shape ) and ' label ' ( scalar value )) .
code: def load_dataset_from_files(file_paths, data_shape, data_type=np.float32, label_type=int):
      """
      Loads a tensorflow dataset from a list of `*.tfrecord` files with serialized examples.
      This function is the counterpart for write_dataset_to_file() (see above) and its only valid for TFRecords that
      follow the serialization format of that function (two fixed length features, 'data' (with shape = data_shape)
      and 'label' (scalar value)).
  
      :param file_paths: List of paths to the `*.tfrecord` files that contain the serialized examples.
      :type file_paths: list[str]
      :param data_shape: Original shape of the example data. Since they are serialized, this metadata is needed
          to reconstruct the tensor.
      :type data_shape: tuple[int]
      :param data_type: Type of each data point in the example or the example itself if it is bytes or str, before
          serialization. It is needed to parse the example. Optional, default: np.float32
      :type data_type: type
      :param label_type: Type of the label (if any). If there is no label, this must be specified by setting this
          parameter to None. Optional, default: int.
      :type label_type: type
      :return: Tensorflow dataset of parsed examples (as tuples of tensors with example data and optionally a label).
      :rtype: tf.data.Dataset
      """
      raw_dataset = tf.data.TFRecordDataset(file_paths)
      return raw_dataset.map(
          lambda raw_ex: _parse_example(raw_ex, data_shape, data_type, label_type),
          num_parallel_calls=tf.data.AUTOTUNE
      )
code_tokens: def load_dataset_from_files ( file_paths , data_shape , data_type = np . float32 , label_type = int ) : raw_dataset = tf . data . TFRecordDataset ( file_paths ) return raw_dataset . map ( lambda raw_ex : _parse_example ( raw_ex , data_shape , data_type , label_type ) , num_parallel_calls = tf . data . AUTOTUNE )
short_docstring: Loads a tensorflow dataset from a list of `*.tfrecord` files with serialized examples.
short_docstring_tokens: Loads a tensorflow dataset from a list of ` * . tfrecord ` files with serialized examples .
comment: """
      Loads a tensorflow dataset from a list of `*.tfrecord` files with serialized examples.
      This function is the counterpart for write_dataset_to_file() (see above) and its only valid for TFRecords that
      follow the serialization format of that function (two fixed length features, 'data' (with shape = data_shape)
      and 'label' (scalar value)).
  
      :param file_paths: List of paths to the `*.tfrecord` files that contain the serialized examples.
      :type file_paths: list[str]
      :param data_shape: Original shape of the example data. Since they are serialized, this metadata is needed
          to reconstruct the tensor.
      :type data_shape: tuple[int]
      :param data_type: Type of each data point in the example or the example itself if it is bytes or str, before
          serialization. It is needed to parse the example. Optional, default: np.float32
      :type data_type: type
      :param label_type: Type of the label (if any). If there is no label, this must be specified by setting this
          parameter to None. Optional, default: int.
      :type label_type: type
      :return: Tensorflow dataset of parsed examples (as tuples of tensors with example data and optionally a label).
      :rtype: tf.data.Dataset
      """