class_docstr: Flickr dataset implementation
  
  Args:
      name: The name of the dataset.
  
      symmetry_edges: Whether to create symmetry edges.
  
      self_loop:  Whether to contain self loop edges.
  
      train_percentage: The percentage of nodes to be trained in multi class task.
  
  Attributes:
      graph: The :code:`Graph` data object.
  
      num_groups: Number of classes.
  
      train_index: The index for nodes in training set.
  
      test_index: The index for nodes in validation set.
code: def __init__(
      self,
      data_path,
      symmetry_edges=False,
      self_loop=False,
      train_percentage=0.5,
  ):
      self.path = data_path
      #  self.name = name
      self.num_groups = 5
      self.symmetry_edges = symmetry_edges
      self.self_loop = self_loop
      self.train_percentage = train_percentage
      self._load_data()
  
file_path: PGL/legacy/examples/line/data_loader.py
imports: import os
  import io
  import sys
  import numpy
  from pgl import graph
  from pgl.utils.logger import log
label_desc: Use image node_id 1 to create a new FlickrDataset object from inherited base classes: object with example: obj = FlickrDataset(data_path, symmetry_edges, _loop, train_percentage)