I am trying to write a custom TFDS dataset.

Here is the file my_dataset_dataset_builder.py:

"""my_dataset dataset."""

import tensorflow_datasets as tfds


class Builder(tfds.core.GeneratorBasedBuilder):
  """DatasetBuilder for my_dataset dataset."""

  VERSION = tfds.core.Version('1.0.0')
  RELEASE_NOTES = {
      '1.0.0': 'Initial release.',
  }

  def _info(self) -> tfds.core.DatasetInfo:
    """Returns the dataset metadata."""
    # TODO(my_dataset): Specifies the tfds.core.DatasetInfo object
    return self.dataset_info_from_configs(
        features=tfds.features.FeaturesDict({
            # These are the features of your dataset like images, labels ...
            'image': tfds.features.Image(shape=(256, 256, 3)),
            #'label': tfds.features.ClassLabel(names=['no', 'yes']),
            'label': tfds.features.ClassLabel(names=['actinic keratosis', 'basal cell carcinoma', 'benign keratosis', 'dermatofibroma', 'melanocytic nevus', 'melanoma', 'vascular lesion']),
        }),
        # If there's a common (input, target) tuple from the
        # features, specify them here. They'll be used if
        # `as_supervised=True` in `builder.as_dataset`.
        supervised_keys=('image', 'label'),  # Set to `None` to disable
    )
    
  def _split_generators(self, dl_manager: tfds.download.DownloadManager):
    """Download the data and define splits."""
    extracted_path = '/home/user/Documents/data_formatted.zip'
    return {
        'train': self._generate_examples(path=extracted_path / 'train_images'),
        'test': self._generate_examples(path=extracted_path / 'test_images'),
    }

  def _generate_examples(self, path):
    """Generator of examples for each split."""
    for img_path in path.glob('*.jpeg'):
      # Yields (key, example)
      yield img_path.name, {
          'image': img_path,
          'label': 'actinic keratosis' if img_path.name.startswith('akiec_') else 'unknown',
      }

I am getting the error:

TypeError: unsupported operand type(s) for /: ‘str’ and ‘str’

Says the problem is with this line: 

‘train’: self._generate_examples(path=extracted_path / ‘train_images’),

Any help or advice would be appreciated. Thanks.