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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _split_generators(self, dl_manager):
 """Returns SplitGenerators from the folder names."""

    # At data creation time, parse the folder to deduce number of splits,
    # labels, image size,

    # The splits correspond to the high level folders
    split_names = list_folders(dl_manager.manual_dir)

    # Extract all label names and associated images
    split_label_images = {}  # dict[split_name][label_name] = list(img_paths)
    for split_name in split_names:
      split_dir = os.path.join(dl_manager.manual_dir, split_name)
      split_label_images[split_name] = {
          label_name: list_imgs(os.path.join(split_dir, label_name))
          for label_name in list_folders(split_dir)
      }

    # Merge all label names from all splits to get the final list of labels
    # Sorted list for determinism
    labels = [split.keys() for split in split_label_images.values()]
    labels = list(sorted(set(itertools.chain(*labels))))

    # Could improve the automated encoding format detection
    # Extract the list of all image paths
    image_paths = [
        image_paths
        for label_images in split_label_images.values()
        for image_paths in label_images.values()
    ]
    if any(f.lower().endswith(".png") for f in itertools.chain(*image_paths)):
      encoding_format = "png"
    else:
      encoding_format = "jpeg"

    # Update the info.features. Those info will be automatically resored when
    # the dataset is re-created
    self.info.features["image"].set_encoding_format(encoding_format)
    self.info.features["label"].names = labels

    def num_examples(label_images):
      return sum(len(imgs) for imgs in label_images.values())

    # Define the splits
    return [
        tfds.core.SplitGenerator(
            name=split_name,
            # The number of shards is a dynamic function of the total
            # number of images (between 0-10)
            num_shards=min(10, max(num_examples(label_images) // 1000, 1)),
            gen_kwargs=dict(label_images=label_images,),
        ) for split_name, label_images in split_label_images.items()
    ]