code: def test_sample_neighbors_with_0deg(fused):
      if fused and (
          F._default_context_str == "gpu" or F.backend_name != "pytorch"
      ):
          pytest.skip(
              "Fused sampling support CPU with backend PyTorch."
          )
      g = dgl.graph(([], []), num_nodes=5).to(F.ctx())
      sg = sample_neighbors_fusing_mode[fused](
          g,
          F.tensor([1, 2], dtype=F.int64),
          2,
          edge_dir="in",
          replace=False,
      )
      assert sg.num_edges() == 0
      sg = sample_neighbors_fusing_mode[fused](
          g,
          F.tensor([1, 2], dtype=F.int64),
          2,
          edge_dir="in",
          replace=True,
      )
      assert sg.num_edges() == 0
      sg = sample_neighbors_fusing_mode[fused](
          g,
          F.tensor([1, 2], dtype=F.int64),
          2,
          edge_dir="out",
          replace=False,
      )
      assert sg.num_edges() == 0
      sg = sample_neighbors_fusing_mode[fused](
          g,
          F.tensor([1, 2], dtype=F.int64),
          2,
          edge_dir="out",
          replace=True,
      )
      assert sg.num_edges() == 0
  
imports: import unittest
  import warnings
  import backend
  import dgl
  import numpy
  import pytest
label_desc: Use image node_id 22 for calling a global function with example usage: test_sample_neighbors_with_0deg(fused) without return types