code: def test_homo_neighbor_loader_sampled_info():
      edge_index = torch.tensor(
          [
              [2, 3, 4, 5, 7, 7, 10, 11, 12, 13],
              [0, 1, 2, 3, 2, 3, 7, 7, 7, 7],
          ]
      )
  
      data = Data(edge_index=edge_index, num_nodes=14)
  
      loader = NeighborLoader(
          data,
          num_neighbors=[1, 2, 4],
          batch_size=2,
          shuffle=False,
      )
      batch = next(iter(loader))
  
      assert batch.num_sampled_nodes == [2, 2, 3, 4]
      assert batch.num_sampled_edges == [2, 4, 4]
  
imports: import os.path
  import numpy
  import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import GraphConv, to_hetero
  from torch_geometric.sampler.base import SubgraphType
  from torch_geometric.testing import MyFeatureStore, MyGraphStore, get_random_edge_index, get_random_tensor_frame, onlyLinux, onlyNeighborSampler, onlyOnline, withCUDA, withPackage
  from torch_geometric.typing import WITH_EDGE_TIME_NEIGHBOR_SAMPLE, WITH_PYG_LIB, WITH_TORCH_SPARSE, WITH_WEIGHTED_NEIGHBOR_SAMPLE, TensorFrame
  from torch_geometric.utils import is_undirected, sort_edge_index, to_torch_csr_tensor, to_undirected
label_desc: Use image node_id 13 for calling a global function with example usage: test_homo_neighbor_loader_sampled_info() without return types