class_docstr: Dataset for Style transfer. The dataset contains 2001 images for training set and 200 images for testing set.
  They are derived form COCO2014. Meanwhile, it contains 21 different style pictures in file "21styles".
  
  Args:
     transform(callmethod) : The method of preprocess images.
     mode(str): The mode for preparing dataset.
  
  Returns:
      DataSet: An iterable object for data iterating
code: def __init__(self, transform: Callable, mode: str = "train"):
      self.mode = mode
      self.transform = transform
  
      if self.mode == "train":
          self.file = "train"
      elif self.mode == "test":
          self.file = "test"
      self.file = os.path.join(hubenv.DATA_HOME, "minicoco", self.file)
      self.style_file = os.path.join(
          hubenv.DATA_HOME, "minicoco", "21styles"
      )
      self.data = get_img_file(self.file)
      self.style = get_img_file(self.style_file)
  
file_path: PaddleHub/paddlehub/datasets/minicoco.py
imports: import os
  from typing import Callable
  import paddle
  import numpy
  import paddlehub.env
  from paddlehub.vision.utils import get_img_file
  from paddlehub.utils.download import download_data
label_desc: Use image node_id 1 to create a new MiniCOCO object from inherited base classes: paddle.io with example: obj = MiniCOCO(transform, mode)