code: def test_filter(self):
      pyg_dataset = TUDataset("./enzymes", "ENZYMES")
      graphs = GraphDataset.pyg_to_graphs(pyg_dataset)
      dataset = GraphDataset(graphs, task="graph")
      thresh = 90
  
      orig_dataset_size = len(dataset)
      num_graphs_large = 0
      for graph in dataset:
          if len(graph.G) >= thresh:
              num_graphs_large += 1
  
      dataset = dataset.filter(
          lambda graph: len(graph.G) < thresh, deep_copy=False
      )
      filtered_dataset_size = len(dataset)
  
      self.assertEqual(
          orig_dataset_size - filtered_dataset_size,
          num_graphs_large,
      )
  
imports: import random
  import torch
  import unittest
  from torch_geometric.datasets import TUDataset, Planetoid
  from copy import deepcopy
  from deepsnap.graph import Graph
  from deepsnap.hetero_graph import HeteroGraph
  from deepsnap.dataset import GraphDataset, Generator, EnsembleGenerator
  from tests.utils import simple_networkx_graph, simple_networkx_small_graph, simple_networkx_graph_alphabet, simple_networkx_dense_graph, simple_networkx_dense_multigraph, simple_networkx_multigraph, generate_dense_hete_dataset, generate_simple_small_hete_graph, generate_simple_dense_hete_graph, generate_simple_dense_hete_multigraph, generate_dense_hete_multigraph, gen_graph
label_desc: Use image node_id 9 for calling the TestDataset obj's underlying member method code with example usage: obj.test_filter() without return types