class_docstr: The Fashion-MNIST database of Zalando's fashion article images.
  
  The dataset consists of 70,000 28 x 28 grayscale images in 10 classes.
  There are 60,000 training images and 10,000 test images.
  
  Example usage::
  
      import fiftyone as fo
      import fiftyone.zoo as foz
  
      dataset = foz.load_zoo_dataset("fashion-mnist", split="test")
  
      session = fo.launch_app(dataset)
  
  Dataset size
      36.42 MB
  
  Source
      https://github.com/zalandoresearch/fashion-mnist
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code: def _download_and_prepare(self, dataset_dir, scratch_dir, split):
      def download_fcn(download_dir):
          return tfds.load(
              "fashion_mnist",
              split=split,
              data_dir=download_dir,
              download=True,
              with_info=True,
          )
  
      get_classes_fcn = lambda info: info.features["label"].names
      get_num_samples_fcn = lambda info: info.splits[split].num_examples
      sample_parser = _TFDSImageClassificationSampleParser()
      return _download_and_prepare(
          dataset_dir,
          scratch_dir,
          download_fcn,
          get_classes_fcn,
          get_num_samples_fcn,
          sample_parser,
      )
  
imports: import fiftyone.core.labels
  import fiftyone.core.utils
  import fiftyone.types
  import fiftyone.utils.imagenet
  import fiftyone.utils.data
  import fiftyone.zoo.datasets
label_desc: Use image node_id 4 for calling the FashionMNISTDataset obj's underlying member method code with example usage: obj._download_and_prepare(dataset_dir, scratch_dir, split) and returns: _download_and_prepare, tfds