code: def test_dataset_basic(self):
      (
          _,
          x,
          y,
          edge_x,
          edge_y,
          edge_index,
          graph_x,
          graph_y,
      ) = simple_networkx_graph()
  
      G = Graph(
          node_feature=x,
          node_label=y,
          edge_index=edge_index,
          edge_feature=edge_x,
          edge_label=edge_y,
          graph_feature=graph_x,
          graph_label=graph_y,
          directed=True,
      )
  
      H = deepcopy(G)
  
      dataset = GraphDataset([G, H])
      self.assertEqual(len(dataset), 2)
  
imports: import copy
  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 pyg_to_dicts, simple_networkx_graph, simple_networkx_small_graph, simple_networkx_graph_alphabet, simple_networkx_multigraph, generate_dense_hete_dataset, generate_simple_small_hete_graph, gen_graph
label_desc: Use image node_id 1 for calling the TestDatasetTensorBackend obj's underlying member method code with example usage: obj.test_dataset_basic() without return types