<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def get_bottleneck_path(image_lists, label_name, index, bottleneck_dir, category, module_name):
 """Returns a path to a bottleneck file for a label at the given index. Args: image_lists: OrderedDict of training images for each label. label_name: Label string we want to get an image for. index: Integer offset of the image we want. This will be moduloed by the available number of images for the label, so it can be arbitrarily large. bottleneck_dir: Folder string holding cached files of bottleneck values. category: Name string of set to pull images from - training, testing, or validation. module_name: The name of the image module being used. Returns: File system path string to an image that meets the requested parameters. """

  module_name = (module_name.replace('://', '~')  # URL scheme.
                 .replace('/', '~')  # URL and Unix paths.
                 .replace(':', '~').replace('\\', '~'))  # Windows paths.
  return get_image_path(image_lists, label_name, index, bottleneck_dir,
                        category) + '_' + module_name + '.txt'