class_docstr: Synthetic dataset class. Mean image is returned always. This dataset
  is used/recommended to use for testing purposes only.
  
  Args:
      path (string): can be "" [not used]
      split (string): specify split for the dataset.
          Usually train/val/test. Used to read images if
          reading from a folder `path' and retrieve settings for that split
          from the config path [not used]
      dataset_name (string): name of dataset. For information only. [not used]
      data_source (string, Optional): data source ("synthetic") [not used]
code: def __init__(
      self,
      cfg,
      path: str,
      split: str,
      dataset_name: str,
      data_source="synthetic",
  ):
      super(SyntheticImageDataset, self).__init__()
      self.cfg = cfg
      self.split = split
      self.data_source = data_source
      self._num_samples = max(
          self.DEFAULT_SIZE, cfg.DATA[split].DATA_LIMIT
      )
  
file_path: vissl/vissl/data/synthetic_dataset.py
imports: from typing import List
  import numpy
  from PIL import Image, ImageFilter
  from torch.utils.data import Dataset
  from vissl.data.data_helper import get_mean_image
label_desc: Use image node_id 1 to create a new SyntheticImageDataset object from inherited base classes: Dataset with example: obj = SyntheticImageDataset(cfg, path, split, dataset_name, data_source)