code: def test_induced_set_attention_block():
      x = torch.randn(2, 4, 8)
      mask = torch.tensor(
          [[1, 1, 1, 1], [1, 1, 0, 0]], dtype=torch.bool
      )
  
      block = InducedSetAttentionBlock(8, num_induced_points=2, heads=2)
      assert str(block) == (
          "InducedSetAttentionBlock(8, num_induced_points=2, "
          "heads=2, layer_norm=True, dropout=0.0)"
      )
  
      out = block(x, mask)
      assert out.size() == (2, 4, 8)
  
      jit = torch.jit.script(block)
      assert torch.allclose(jit(x, mask), out)
  
imports: import torch
  from torch_geometric.nn.aggr.utils import InducedSetAttentionBlock, MultiheadAttentionBlock, PoolingByMultiheadAttention, SetAttentionBlock
label_desc: Use image node_id 4 for calling a global function with example usage: test_induced_set_attention_block() without return types