code: def test_pna_conv_get_degree_histogram_neighbor_loader():
      edge_index = torch.tensor(
          [[0, 0, 0, 1, 1, 2, 3], [1, 2, 3, 2, 0, 0, 0]]
      )
      data = Data(num_nodes=5, edge_index=edge_index)
      loader = NeighborLoader(
          data,
          num_neighbors=[-1],
          input_nodes=None,
          batch_size=5,
          shuffle=False,
      )
      deg_hist = PNAConv.get_degree_histogram(loader)
      assert torch.equal(deg_hist, torch.tensor([1, 2, 1, 1]))
  
file_path: pytorch_geometric/test/nn/conv/test_pna_conv.py
imports: import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.data import Data
  from torch_geometric.loader import DataLoader, NeighborLoader
  from torch_geometric.nn import PNAConv
  from torch_geometric.testing import is_full_test, onlyNeighborSampler
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: test_pna_conv_get_degree_histogram_neighbor_loader() without return types